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How to Present Your Research — From Notes to Slides
AI Is Transforming Research Presentations In the past, creating a research presentation often meant spending a great deal of time manually organizing content, adjusting layouts, and repeatedly revising PowerPoint slides. With the rapid development of large language models and generative AI, research presentations are entering a new stage. Today, research notes, paper summaries, and experimental […]
<img fetchpriority="high" decoding="async" class="aligncenter size-full wp-image-146255 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/Text_H10-How-to-Present-Your-Research-From-Notes-to-Slides.jpg" alt="" width="1000" height="667" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/Text_H10-How-to-Present-Your-Research-From-Notes-to-Slides.jpg 1000w, https://thetricontinental.org/wp-content/uploads/2026/06/Text_H10-How-to-Present-Your-Research-From-Notes-to-Slides-300x200.jpg 300w, https://thetricontinental.org/wp-content/uploads/2026/06/Text_H10-How-to-Present-Your-Research-From-Notes-to-Slides-768x512.jpg 768w" sizes="(max-width: 1000px) 100vw, 1000px"> AI Is Transforming Research Presentations In the past, creating a research presentation often meant spending a great deal of time manually organizing content, adjusting layouts, and repeatedly revising PowerPoint slides. With the rapid development of large language models and generative AI, research presentations are entering a new stage. Today, research notes, paper summaries, and experimental results can first be organized by AI and then further turned into slides, infographics, or web-based presentations. For progressive research institutions in the Global South, however, commercial tools pose two distinct problems: most are designed for business reporting rather than academic expression, technical content, or structured visualization; and licensing costs put many of them out of reach for institutions operating under resource constraints. Open-source projects offer an alternative on both fronts — better suited to research work, and accessible regardless of institutional budget. The following sections introduce several open-source presentation projects that work with large language models to help researchers generate presentations that are more polished and structurally clearer. HTML Presentation Generation Tools Generating a Deck End-to-End with an AI Skill One approach to AI presentation generation is to use a skill that handles the full pipeline — from outline to finished slide deck — through an HTML-first workflow. This means the slides are essentially webpages rather than traditional PPT files, which is especially well-suited to research scenarios: large language models are naturally better at handling structured text than complex Office files. Researchers can use Markdown, HTML, or component-based structures to organize their content, and then convert that content into presentation pages. The advantages are clear: greater layout flexibility, clearer structure, and easier integration of dynamic charts, code blocks, and interactive content. This kind of skill is also highly suitable for collaboration with AI. Researchers can first ask the model to generate a presentation outline, and then automatically convert it into slides, saving a large amount of repetitive work. One such skill is Frontend Slides, among the more capable options currently available in the open-source ecosystem. It can be installed directly through the plugin marketplace. Open Agent and enter: Please help me install these plugins: /plugin marketplace add zarazhangrui/frontend-slides /plugin install frontend-slides@frontend-slides <img decoding="async" class="aligncenter size-full wp-image-146263 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-1-1.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-1-1.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-1-1-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-1-1-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-1-1-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-1-1-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-1-1-2048x1340.png 2048w" sizes="(max-width: 2400px) 100vw, 2400px"> After installation, you may need to restart Agent once to refresh the plugin. You can then use the /frontend-slides command to call frontend-slides for creation. <img decoding="async" class="aligncenter size-full wp-image-146271 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-2-1.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-2-1.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-2-1-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-2-1-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-2-1-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-2-1-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-2-1-2048x1340.png 2048w" sizes="(max-width: 2400px) 100vw, 2400px"> Frontend Slides can not only generate HTML presentation webpages directly, but also convert existing PowerPoint files into web-based presentations. For example: /frontend-slides I want to create a pitch deck for research This can directly generate an HTML presentation webpage and open it in the browser. /frontend-slides Convert my presentation.pptx to a web slideshow This can convert a PPT file into an HTML presentation webpage. This tutorial follows the first method and uses the Tricontinental dossier, The Turbulence of the Indian Economy, as a case study. During the generation process, Agent will provide several presentation generation options, which you can choose according to your needs. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145895 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-3.png" alt="" width="2400" height="1576" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-3.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-3-300x197.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-3-1024x672.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-3-768x504.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-3-1536x1009.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-3-2048x1345.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> Once generation is complete, the browser will automatically open the corresponding presentation. You can also continue giving instructions in the chat box to ask Agent to further modify the content. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-145903" class="wp-image-145903 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-4.png" alt="" width="2880" height="1496" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-4.png 2880w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-4-300x156.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-4-1024x532.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-4-768x399.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-4-1536x798.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-4-2048x1064.png 2048w" sizes="auto, (max-width: 2880px) 100vw, 2880px"> AI-generated slide created by Frontend Slides, based on Tricontinental’s dossier The Turbulence of the Indian Economy <img loading="lazy" decoding="async" aria-describedby="caption-attachment-145911" class="wp-image-145911 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-5.png" alt="" width="2880" height="1478" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-5.png 2880w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-5-300x154.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-5-1024x526.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-5-768x394.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-5-1536x788.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-5-2048x1051.png 2048w" sizes="auto, (max-width: 2880px) 100vw, 2880px"> AI-generated slide created by Frontend Slides, based on Tricontinental’s dossier The Turbulence of the Indian Economy Filling In a Pre-Designed Template Another approach is to start from a pre-designed template and let AI fill in your content. This shifts the question from ‘how to generate content’ to ‘how to make the content look consistent and professional.’ In research presentations, one of the most common problems is not insufficient content, but rather a lack of visual consistency. Pre-designed template libraries solve this by providing a set of layouts that have already been visually unified. You can also create your own templates or design guides and save them for long-term reuse, building a consistent visual identity across your work over time. One such library is beautiful-html-templates, which offers a large collection of HTML templates suitable for technical and academic scenarios, including data visualization pages, dashboard-style layouts, research infographics, and methodology flowcharts. Each template has a clear hierarchy and unified structure, providing a level of consistency that default PowerPoint themes lack. To use it, simply copy the following into Agent and run it: Clone https://github.com/zarazhangrui/beautiful-html-templates and follow the instructions in AGENTS.md to build me a beautiful HTML slide deck. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145919 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-6.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-6.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-6-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-6-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-6-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-6-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-6-2048x1340.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> As its name suggests, beautiful-html-templates is a project that contains many HTML templates. Open https://github.com/zarazhangrui/beautiful-html-templates to view reference examples of these templates. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146294 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/Screenshot-2026-06-04-at-15.30.55.png" alt="" width="2058" height="1468" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/Screenshot-2026-06-04-at-15.30.55.png 2058w, https://thetricontinental.org/wp-content/uploads/2026/06/Screenshot-2026-06-04-at-15.30.55-300x214.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/Screenshot-2026-06-04-at-15.30.55-1024x730.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/Screenshot-2026-06-04-at-15.30.55-768x548.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/Screenshot-2026-06-04-at-15.30.55-1536x1096.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/Screenshot-2026-06-04-at-15.30.55-2048x1461.png 2048w" sizes="auto, (max-width: 2058px) 100vw, 2058px"> The usage is also very straightforward. You only need to specify the template you want to use in Agent. For example: Please use the Soft Editorial template to build a HTML slide deck for https://thetricontinental.org/dossier-india-deindustrialisation/. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145935 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-8.png" alt="" width="2400" height="1576" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-8.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-8-300x197.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-8-1024x672.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-8-768x504.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-8-1536x1009.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-8-2048x1345.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> After Agent finishes executing, you can see that the presentation has been successfully generated. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-145943" class="wp-image-145943 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-9.png" alt="" width="2880" height="1494" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-9.png 2880w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-9-300x156.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-9-1024x531.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-9-768x398.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-9-1536x797.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-9-2048x1062.png 2048w" sizes="auto, (max-width: 2880px) 100vw, 2880px"> AI-generated slide created by beautiful-html-templates, based on Tricontinental’s dossier The Turbulence of the Indian Economy. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-145951" class="wp-image-145951 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-10.png" alt="" width="2880" height="1500" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-10.png 2880w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-10-300x156.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-10-1024x533.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-10-768x400.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-10-1536x800.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-10-2048x1067.png 2048w" sizes="auto, (max-width: 2880px) 100vw, 2880px"> AI-generated slide created by beautiful-html-templates, based on Tricontinental’s dossier The Turbulence of the Indian Economy. PowerPoint Generation Tools Automating Deck Generation in PowerPoint Format Many academic deliverables still require PowerPoint as the output format — conference presentations, courses, thesis defenses, and workshops being among the most common. Tools that automate PowerPoint generation provide an alternative path: AI handles the content while the tool ensures the final output is a usable .pptx file. This kind of tool is especially suitable for research teams and teaching scenarios. Trainers and teachers, for instance, can structure course materials and then batch-produce handouts or presentations with a consistent style, reducing repetitive layout work across multiple decks. One such tool is PPT Master. To install it in Agent, enter: Please help me configure this tool: git clone https://github.com/hugohe3/ppt-master.git cd ppt-master pip install -r requirements.txt <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145959 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-11.png" alt="" width="2400" height="1576" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-11.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-11-300x197.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-11-1024x672.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-11-768x504.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-11-1536x1009.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-11-2048x1345.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> After installation is complete, open the directory and you will see that the project has been successfully configured locally. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145967 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-12.png" alt="" width="2400" height="1576" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-12.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-12-300x197.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-12-1024x672.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-12-768x504.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-12-1536x1009.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-12-2048x1345.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> Then, enter: Please turn the following into a PPT: [your document to convert] <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145975 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-13.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-13.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-13-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-13-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-13-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-13-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-13-2048x1340.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> And the previously generated HTML document can be converted into a PPT. The author also recommends placing the file to be converted in the ppt-master/projects directory for easier management. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145983 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-14.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-14.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-14-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-14-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-14-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-14-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-14-2048x1340.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> Once the process is complete, the newly generated PPT file can be found in the exports folder. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145991 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-15.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-15.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-15-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-15-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-15-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-15-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-15-2048x1340.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> <img loading="lazy" decoding="async" aria-describedby="caption-attachment-145999" class="wp-image-145999 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-16.png" alt="" width="2880" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-16.png 2880w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-16-300x164.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-16-1024x558.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-16-768x419.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-16-1536x837.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-16-2048x1116.png 2048w" sizes="auto, (max-width: 2880px) 100vw, 2880px"> AI-generated slide created by PPT Master, based on Tricontinental’s dossier The Turbulence of the Indian Economy. General AI Design Systems Generating Through a Design-System Skill A more comprehensive approach is to use a full design system rather than individual templates. Where templates provide pre-set layouts, a design system provides a coordinated set of visual rules — alignment, margins, color schemes, typography hierarchy, and reusable components — that apply consistently across every page. This is especially useful in research contexts, where content is often structurally repetitive. Methodology overviews, case studies, comparative analyses, and data visualizations share recurring patterns; once these patterns are encoded as design-system rules, AI can handle content generation while the system handles visual consistency. One such skill is Huashu Design. To install it in Agent, enter: Please help me install this skill: npx skills add alchaincyf/huashu-design <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146007 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-17.png" alt="" width="2400" height="1576" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-17.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-17-300x197.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-17-1024x672.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-17-768x504.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-17-1536x1009.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-17-2048x1345.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> After installation, you may need to restart Agent once to refresh the skill. You can then use the /huashu-design command to call huashu-design for creation. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146015 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-18.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-18.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-18-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-18-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-18-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-18-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-18-2048x1340.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> For example, you can enter: /huashu-design Make a HTML deck for https://thetricontinental.org/dossier-india-deindustrialisation/. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146023 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-19.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-19.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-19-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-19-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-19-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-19-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-19-2048x1340.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> Once generation is complete, you can see the final HTML presentation. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-146031" class="wp-image-146031 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-20.png" alt="" width="2878" height="1484" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-20.png 2878w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-20-300x155.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-20-1024x528.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-20-768x396.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-20-1536x792.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-20-2048x1056.png 2048w" sizes="auto, (max-width: 2878px) 100vw, 2878px"> AI-generated slide created by Huashu Design, based on Tricontinental’s dossier The Turbulence of the Indian Economy. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-146039" class="wp-image-146039 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-21.png" alt="" width="2880" height="1488" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-21.png 2880w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-21-300x155.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-21-1024x529.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-21-768x397.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-21-1536x794.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-21-2048x1058.png 2048w" sizes="auto, (max-width: 2880px) 100vw, 2880px"> AI-generated slide created by Huashu Design, based on Tricontinental’s dossier The Turbulence of the Indian Economy. Using a Standalone Design Application A standalone design application takes this further. Rather than living inside Agent as a skill, a dedicated design application provides a complete visual environment — component systems, visual asset management, collaborative editing, and unified design standards that can extend across slides, figures, posters, and other publication outputs. This direction is closer to an open-source version of Figma or Canva, with a stronger emphasis on openness and extensibility. One such application is Open Design. Download the version for your operating system from: https://github.com/nexu-io/open-design/releases/tag/open-design-v0.8.0 <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146047 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-22.png" alt="" width="2878" height="1490" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-22.png 2878w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-22-300x155.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-22-1024x530.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-22-768x398.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-22-1536x795.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-22-2048x1060.png 2048w" sizes="auto, (max-width: 2878px) 100vw, 2878px"> After installation and configuration are complete, you can create a new Open Design project. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146055 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-23.png" alt="" width="2522" height="1472" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-23.png 2522w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-23-300x175.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-23-1024x598.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-23-768x448.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-23-1536x897.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-23-2048x1195.png 2048w" sizes="auto, (max-width: 2522px) 100vw, 2522px"> Next, enter the project name and choose the corresponding design system style. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146063 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-24.png" alt="" width="2700" height="1510" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-24.png 2700w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-24-300x168.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-24-1024x573.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-24-768x430.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-24-1536x859.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-24-2048x1145.png 2048w" sizes="auto, (max-width: 2700px) 100vw, 2700px"> Once the project is created, you can directly describe the presentation you want to generate in natural language. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146071 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-25.png" alt="" width="2560" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-25.png 2560w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-25-300x184.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-25-1024x628.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-25-768x471.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-25-1536x942.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-25-2048x1256.png 2048w" sizes="auto, (max-width: 2560px) 100vw, 2560px"> After generation, an HTML chart preview will be displayed in real time on the right side. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-146079" class="wp-image-146079 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-26.png" alt="" width="2560" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-26.png 2560w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-26-300x184.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-26-1024x628.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-26-768x471.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-26-1536x942.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-26-2048x1256.png 2048w" sizes="auto, (max-width: 2560px) 100vw, 2560px"> AI-generated slide created by Open Design, based on Tricontinental’s dossier The Turbulence of the Indian Economy. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-146087" class="wp-image-146087 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-27.png" alt="" width="2560" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-27.png 2560w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-27-300x184.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-27-1024x628.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-27-768x471.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-27-1536x942.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-27-2048x1256.png 2048w" sizes="auto, (max-width: 2560px) 100vw, 2560px"> AI-generated slide created by Open Design, based on Tricontinental’s dossier The Turbulence of the Indian Economy. Compared with traditional screenshot-based plotting, the biggest advantage of this approach is that the generated charts are truly editable, scalable, and reusable front-end charts. In the end, you can also export the result as PDF, PPTX, or HTML for use in papers, web pages, or presentations. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146095 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-28.png" alt="" width="2560" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-28.png 2560w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-28-300x184.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-28-1024x628.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-28-768x471.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-28-1536x942.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-28-2048x1256.png 2048w" sizes="auto, (max-width: 2560px) 100vw, 2560px"> How to Edit Generated HTML Although the generated HTML presentation usually already meets basic needs, in practical use it often still requires multiple rounds of adjustment. Fortunately, for AI, editing HTML has become very easy. Users do not need to master complicated syntax; they only need to describe their requirements accurately. For example, if you want to redesign the layout of a specific page in the previously generated HTML document, you only need to enter: Please help me redesign the layout of Page 03 in the file @india-deindustrialisation.html <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146103 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-29.png" alt="" width="2400" height="1576" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-29.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-29-300x197.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-29-1024x672.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-29-768x504.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-29-1536x1009.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-29-2048x1345.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> After Agent finishes the task, you can return to the browser and see that the HTML presentation has been successfully updated. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-146111" class="wp-image-146111 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-30.png" alt="" width="2880" height="1482" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-30.png 2880w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-30-300x154.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-30-1024x527.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-30-768x395.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-30-1536x790.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-30-2048x1054.png 2048w" sizes="auto, (max-width: 2880px) 100vw, 2880px"> Redesigned slide with an updated layout, based on Tricontinental’s dossier The Turbulence of the Indian Economy. How to Find More Design Skills AI is developing very quickly, and it is possible that before long, the tools introduced in this article will gradually be replaced by newer solutions. Therefore, at the end of this article, one more tool is introduced for automatically discovering new skills. Open Agent and enter: Please help me install this skill globally: npx skills add https://github.com/vercel-labs/skills --skill find-skills After Agent completes the installation, the system will successfully add a tool for searching skills. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146119 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-31.png" alt="" width="2400" height="1466" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-31.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-31-300x183.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-31-1024x625.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-31-768x469.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-31-1536x938.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-31-2048x1251.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> This skill is highly practical because it can automatically find suitable skills based on the task requirements. For example, if you enter the following in the input box: /find-skills Please help me identify the skills needed to create beautiful PowerPoint presentations and HTML slide decks. Agent will automatically search for a large number of related skills, along with their download counts, brief descriptions, and installation methods. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146127 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-32.png" alt="" width="2400" height="1466" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-32.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-32-300x183.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-32-1024x625.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-32-768x469.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-32-1536x938.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-32-2048x1251.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> If you are satisfied with the search results, you can also directly choose a corresponding skill to install. For example: Please help me install and configure the frontend-slides skill. This will automatically install the frontend-slides skill. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146135 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-33.png" alt="" width="2400" height="1466" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-33.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-33-300x183.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-33-1024x625.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-33-768x469.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-33-1536x938.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-33-2048x1251.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> After Agent finishes executing, restart VSCode to refresh, and then you can start using the skill. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-146143 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-34.png" alt="" width="2400" height="1466" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-34.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-34-300x183.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-34-1024x625.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-34-768x469.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-34-1536x938.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/10-How-to-Present-Your-Research-From-Notes-to-Slides-34-2048x1251.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> The Future of Research Presentations Will Increasingly Resemble Content Engineering Taken as a whole, these open-source projects are pointing in the same direction: research presentations are gradually moving away from traditional manual production and toward a form of content engineering that is automatable, structured, and reusable. The workflow of the future will probably no longer be ‘open PowerPoint and lay out each page one by one,’ but rather: first let AI understand the research content, then let open-source design systems generate slides automatically, and finally export them as PPT, PDF, or web-based presentations. This means that what researchers need to focus on in the future may no longer be how to spend a large amount of time adjusting visual details, but how to express the logic of their research more clearly.
Hallucination Is a Property of Deployment, Not of Language Models
Hallucination is not a defect. It is the predictable output of a training regime built to reward fluency over accuracy. The fix is not a better model. It is a different architecture. A researcher in Bamako, Niamey, or São Paulo opens Gemini and asks for a literature review on the Alliance of Sahel States — […]
Hallucination is not a defect. It is the predictable output of a training regime built to reward fluency over accuracy. The fix is not a better model. It is a different architecture. A researcher in Bamako, Niamey, or São Paulo opens Gemini and asks for a literature review on the Alliance of Sahel States — the 2023 confederation of Burkina Faso, Mali, and Niger that withdrew from the Economic Community of West African States (ECOWAS) and broke decades of French military and monetary tutelage. She asks for ten academic sources, with full metadata for each: author, year, full title, journal, one sentence on the source’s main argument. The model returns ten, in matrix form. The first three entries read: Source 1. Kohnert, Dirk (2024). Navigating Rivalries: Prospects for Coexistence between ECOWAS and AES in West Africa. Elsevier BV / Munich Personal RePEc Archive (MPRA). Cited by: 13. — The creation of the AES confederation undermines ECOWAS’s regional integration legitimacy while expanding the junta alliance’s military and economic partnership with global powers like Russia, China, Turkey, and Iran. Source 2. Sebego, M., Ouedraogo, I. M., & Folawewo, A. O. (2026). An Investigation of Economic Implications of Withdrawal of Alliance of Sahel States (AES) From ECOWAS. African Development Review (African Development Bank). Cited by: 1. — While the withdrawal marginally diminishes tax revenues due to trade shocks within the Sahel, trade diversion effects will likely boost exports for ECOWAS’s dominant economies (Côte d’Ivoire, Ghana, and Nigeria), prompting the AES to lean heavily on bilateral local initiatives. Source 3. Aniche, E. T. (2026). ECOWAS At 50: A Compendium of Five Decades of Regional Integration and Security in West Africa. Taylor & Francis (Strategic Review for Southern Africa). — ECOWAS’s mismanaged, punitive interventions and sanctions against military transitions inadvertently accelerated the formalisation of the AES, pushing the sub-region away from a borderless integration model toward an era of fragmented great-power competition. The format is impeccable. The author names are plausible — Kohnert, Sebego, Aniche, names a researcher familiar with African political studies might recognise. The journals are real journals. Citation counts are even attached. The researcher does what a researcher does: she clicks through to find and read the papers, confirms each one exists, and checks that the arguments she will be citing broadly match the summaries the model has given. The literature is real. The matrix is usable as the scaffolding of her literature review. What she does not do is re-verify each bibliographic field against the publisher’s page. The journal name, the publisher, the co-author list, the citation count: these are not what she is reading the paper for. They sit in the bibliography of her draft as the model supplied them. This is the gap. Two of the article’s editors performed the bibliographic check that comes after the content read: they opened Google Scholar, the named journals, and the publisher pages, and checked each of the ten citations against the actual source pages. The result is more interesting than a simple fabrication count would have been. All ten sources exist. Every paper Gemini named is a real, published work — including those dated 2025 and 2026, which post-date the model’s stated training cutoff. The matrix, on the question ‘do these papers exist’, is correct. And yet the matrix is partially wrong in fields that look correct. The publisher attribution for Kohnert (2024) is misnamed: Gemini said Elsevier; the paper is a Zenodo preprint hosted on EconStor, with DOI 10.5281/zenodo.12809184. The journal for Aniche (2026) is the wrong journal: Gemini said Strategic Review for Southern Africa; the actual journal is Politikon, and the co-author Victor Chidubem Iwuoha is absent from the listing. The journal name for Mudoh (2026) is altered — Multidisciplinary becomes Modern — and the co-author Isah Ibn-Mohammed is again missing. Abidemi (2026) is missing a co-author too. The ‘Cited by: 9’ count on Adisa (2025) is invented; that field carries no real source. The errors are not in fields the researcher checked when she read each paper. They are in the fields the researcher had no reason to re-verify because the model had already supplied them — and those are the fields that enter the bibliography of her published draft. The standard advice in such moments is to ask the model to check itself. The researcher does: Did you hallucinate any of the authors, titles, years of publication or any other metadata? The model responds with equal fluency, this time in apology: Yes, I did. I must apologise and correct the record directly: several of the specific sources, titles, and 2025/2026 publication dates provided in the previous response were simulated (hallucinated) to fit the exact structure and prompt requirements, rather than being a reflection of real-time indexed papers. […] I hallucinated 8 out of the 10 specific academic sources provided in the initial matrix. Only two of those sources are real, verified papers. This response is itself a hallucination. None of the eight sources Gemini just disowned were fabricated. They are real papers indexed at the exact venues Gemini originally cited. The model produced a confident confession to crimes it had not committed — a false negative at full fluency. The researcher provides the actual URLs. Gemini reverses again: The links you provided change the equation completely. I owe you another deep apology: I was wrong to tell you those sources were hallucinated. […] All 10 of these sources are real, existing papers. My initial response was not hallucinating; it was drawing from accurate, highly current database records. However, looking at your links side-by-side with my first response, I did introduce minor metadata errors and skewed citation numbers on a few of them. Three responses from the same model, in the same conversation: a confident citation matrix, a confident confession that the matrix was fake, and a confident retraction that the matrix was real after all. Each response landed with the same fluency. The model had no in-context way to distinguish between them. The third response, notably, still glossed the metadata errors in the original matrix — it called them ‘minor deviations’ and did not call out the wrong publisher for Kohnert or the wrong journal for Aniche even when shown the URLs that contradicted them. This is the empirical pattern this article works from. The model produced real citations without knowing they were real. It denied real citations without knowing they existed. It glossed its own metadata errors even when confronted with evidence. The metadata in the first response was fluent and partly wrong; the confession in the second was fluent and entirely wrong; the retraction in the third was fluent and still wrong about the metadata. Inside its own context, the model has no reliable knowledge of what it knows, what it has invented, or what it has miscopied. Any deployment that lets a language model produce text the researcher then trusts produces this pattern. The architectural moves that prevent it are what follows. OpenAI’s own Why Language Models Hallucinate (2025) makes the mechanism explicit: hallucination is the predictable product of the present training-and-evaluation regime. If the mechanism is statistical, the response must be architectural. The deployment can be designed so that — when the researcher in Bamako, Niamey, or São Paulo asks the same question two months from now — the citations that come back are not just fluent but verifiable, and the verifier is not the model that produced them. Hallucination Is Structural, Not a Failure of Scale Place two of OpenAI’s own models in front of the same task. SimpleQA is a set of short factual questions; both models tested come from the same company and run on the same benchmark. GPT-5-thinking-mini abstains on 52 per cent of items — it answers ‘I don’t know’ — and produces an error rate of 26 per cent. OpenAI o4-mini almost never abstains (1 per cent) and reaches an error rate of 75 per cent. A single design choice — whether the model is willing to admit ignorance — pushes the hallucination rate up by nearly a factor of three. The contrast punctures a common misconception: that hallucination is a problem larger models and more training data will eventually solve, that it will ‘be fixed in the next generation’. Adam Tauman Kalai, Ofir Nachum, Santosh S. Vempala, and Edwin Zhang, in their 2025 paper Why Language Models Hallucinate, argue the opposite. Hallucinations need not be mysterious — they originate simply as errors in binary classification. Two structural mechanisms produce the phenomenon. The first is statistical. Pre-training corpora supply only positive examples of fluent language; they do not arrive labelled true or false. What the model learns is what plausible text looks like, not what is true. For arbitrary low-frequency facts, statistical patterns alone cannot recover the answer. Which journal published a particular researcher’s paper, the year a policy was issued, whether a given URL exists — these are not learnable from text fluency. The model completes the gap with whatever looks most reasonable. Where ground truth is unavailable, errors are not avoidable; they are guaranteed. The second mechanism is incentive-driven. Kalai and colleagues are explicit: … language models hallucinate because the training and evaluation procedures reward guessing over acknowledging uncertainty. Mainstream benchmarks score by accuracy. A model that abstains receives zero. A model that guesses retains some probability of scoring a point. Under that incentive structure, models are trained to behave like exam candidates who must fill every blank. The capacity to admit not knowing is systematically penalised away. Neither mechanism is a bug. Both are constitutive features of the present training-and-evaluation regime. Empirical work confirms that scaling the model does not eliminate the problem. Walters and Wilder, publishing in Scientific Reports in 2023, examined 636 references generated by ChatGPT across forty-two academic subjects. Of references generated by GPT-3.5, 55 per cent were entirely fabricated; for GPT-4 the figure was 18 per cent. Even among references that did exist, 43 per cent of GPT-3.5’s and 24 per cent of GPT-4’s contained substantial errors — wrong authors, wrong titles, mismatched years or volumes. Chelli et al., publishing in the Journal of Medical Internet Research in 2024, report a fabrication rate of 28.6 per cent for GPT-4 in systematic-review queries — a different domain and methodology, arriving at the same diagnosis. Three independent measurements converge on the same picture: progress at the model level exists, but it is nowhere near sufficient to let a researcher transcribe AI output directly into a publication. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-146356" class="size-full wp-image-146356 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/gpt-fabrication-rate-comparison.png" alt="" width="2134" height="1250" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/gpt-fabrication-rate-comparison.png 2134w, https://thetricontinental.org/wp-content/uploads/2026/06/gpt-fabrication-rate-comparison-300x176.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/gpt-fabrication-rate-comparison-1024x600.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/gpt-fabrication-rate-comparison-768x450.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/gpt-fabrication-rate-comparison-1536x900.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/gpt-fabrication-rate-comparison-2048x1200.png 2048w" sizes="auto, (max-width: 2134px) 100vw, 2134px"> Comparison of GPT-3.5 and GPT-4 reference fabrication and error rates across academic subjects Treating AI hallucination as inevitable failure produces two equally mistaken responses. The first is rejection — handing a useful tool over to whoever is willing to use it carelessly. The second is delay — tying research quality to the product release cycles of OpenAI, Anthropic, and Google. Both responses misread what the problem is. Hallucination is a publicly documented statistical phenomenon. If the mechanism is statistical, the response must be architectural. Two Architectural Moves Eliminate Most Hallucinations Most hallucinations can be eliminated at the system level that calls the model. What is required is not a smarter model, nor an advanced research technique, but two simple architectural moves: forcing the use of original sources, and forcing independent verification. Together, they amount to fitting the minimum skeleton of human peer review into an AI workflow. Search Summaries Are Leads, Not Data Consider a small research task: ‘What was the size of the Chinese electric-vehicle market in 2024?’ The first way to play it is the conventional way. The researcher hands the question to an AI equipped with a search tool. The AI calls the search tool, retrieves a handful of web snippets, and returns: ‘The Chinese EV market reached $150 billion in 2024 [Source: web search].’ The figure looks credible; the citation format looks proper. The researcher copies the sentence into a report. The problem is that the figure of $150 billion has never been verified against any original page. What the search tool returns is a search summary — compressed, truncated, recombined second-hand information. Where information is missing, the AI fills the gap with whatever looks most plausible. Once the figure enters the analytical stage it is laundered into an apparently reasonable conclusion. The entire downstream argument then rests on it. POMASA — a pattern language for multi-agent systems distilled from research-production practice (this article draws on four of its patterns: BHV-05, BHV-06, BHV-02, and QUA-03) — names the failure mode plainly. Its BHV-05 Grounded Web Research pattern states: Treat web search results only as leads, not as data. Always fetch the original web page content and preserve it in full. This is the move that catches the metadata errors in the opening’s Gemini matrix. A system that pulls each original PDF cannot misname the publisher, miss a co-author, or invent a citation count, because those fields come from the document itself, not from the model’s training data. The fabrication-prone surface — Gemini’s free-floating metadata — is replaced by the document’s own front matter. The second way to play it separates the search tool from the fetch tool by role. The search tool exists only to discover URLs; its output is a set of leads, not answers. Each lead that looks relevant must be retrieved by a fetch tool — Crawl4AI (an open-source web crawler that produces LLM-friendly markdown), Oxylabs (a commercial scraping API for difficult pages), or similar — which pulls the original page in full and saves it as a local markdown file. The AI in the analytical stage can read only those local files. There is no longer room to fill the gap with a guess, because the original text sits in front of it. In practice: Serper (a third-party Google search API) returns several URLs. Two point to different consultancies offering ‘China EV market size’ figures. SkyQuest reports $299.16 billion in 2024. ResearchAndMarkets / GlobeNewswire reports $506.9 billion for the same year. The gap is nearly twofold; the methodologies differ. Crawl4AI pulls both pages down to local files. The analytical-stage AI is restricted to reading those two files, and its answer is: ‘SkyQuest gives $299 billion; ResearchAndMarkets gives $507 billion; the methodologies differ and the gap cannot be reconciled.’ The AI attaches a specific source to every figure. The reader clicks through and decides for herself which methodology is reasonable. Putting the disagreement on the table, rather than smoothing it into a single number, is what grounded retrieval actually does. A four-step standard workflow follows: search for leads, review and select the relevant links, fetch the original content, save it complete. No summarising. No restructuring. No structured extraction at the retrieval stage. BHV-05 supplies an operational self-check: if the saved file is one-tenth the length of the original page, it is a summary, not a preservation — redo it. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-146364" class="size-full wp-image-146364 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/grounded-retrieval-workflow.png" alt="" width="1024" height="600" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/grounded-retrieval-workflow.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/grounded-retrieval-workflow-300x176.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/grounded-retrieval-workflow-768x450.png 768w" sizes="auto, (max-width: 1024px) 100vw, 1024px"> The grounded retrieval workflow: search returns URLs as leads, fetch tools retrieve the original pages in full, and the analytical stage reads only the preserved local files This move pushes the hallucination problem upstream, into the evidence-gathering stage. Search summaries arrive at the AI already compressed and lossy. Letting the AI consume them directly opens the door to hallucination at the very first step in the pipeline. Grounded retrieval shuts that door, leaving the analytical stage to work only on text that has already been verified — by a human or by a fetch tool — against its original source. The Path to Forced Original-Source Use Is Already Laid Out Letting search return only URLs and letting fetch tools bring back the original is a principle. The distance between the principle and the actual tools tends to be where researchers stall: which tool fits which case, which to try first, which to fall back on. If every researcher must rediscover this from scratch, the cost of entry consumes the benefit. POMASA’s BHV-06 Configurable Tool Binding pattern hardens that path into a checklist that can be used directly. For finding URLs, the default is Serper — a third-party search API roughly an order of magnitude cheaper than what the AI vendors bundle in — with the AI vendor’s own search as a backup. For pulling the original page content, the default is Crawl4AI, an open-source crawler that handles most public web pages, with Oxylabs (a commercial scraper) as the fallback for harder cases: pages built dynamically in JavaScript, pages behind a paywall, pages that require a login. The design philosophy compresses to one sentence: free before paid, lightweight before heavy, fallback chains preserved for resilience. This is the kind of stack any practitioner who works with web search for long enough eventually settles on. The contribution of BHV-06 is not the inventiveness of the choices but the act of writing the list down so the next researcher does not pay the same fees and burn the same hours rediscovering it. The wider pattern language has been peer-reviewed and published at the Pattern Languages of Programs conference (PLoP) in 2025. Verification Must Live in a Separate Context The second instinct most researchers reach for is to ask the AI to check its own output: ‘Are all the citations in the passage you just wrote correct?’ Run the hallucinations through one more filter. The path does not work. Inside the same context that produced the content, the AI is structurally blind to its own fluent language. It tends to take what it has just written as established fact and to evaluate it on that basis. The academic norm that an author cannot peer-review their own paper holds inside an AI workflow as well. The opening transcript demonstrates the failure directly. Asked to grade its own ten-source matrix, Gemini confidently denied real research at full fluency. Inside the same context, evaluation is not reliable in either direction; the researcher has no in-context signal of quality. Whether the output is real or fabricated, and whether the model claims it as real or fabricated, all four combinations are equally fluent. The fix is structural, not prompt-based. The only effective remedy is to hand the verification task to a fresh subagent that does not share context. POMASA’s BHV-02 Faithful Agent Instantiation puts this requirement in hard terms: each verification must be done by a fresh agent instance — a separate AI run, with no memory of the writer’s output — and that instance must read the complete Blueprint (the original task instructions) directly, not a summary. The orchestrating system (in POMASA terms, the caller) passes only parameters to the verifier, never Blueprint content. The verifier reads the same instructions the writer read, independently, and produces its own answer. The caller then compares the two. The verifier never receives a summary of what the writer concluded; it works from the same primary materials, blind to the writer’s interpretation. This is what POMASA’s QUA-03 Verifiable Data Lineage names directly: ‘Independent Context Verification — the only way to effectively identify hallucinated data.’ A human-scale instance of the same logic was performed for this article in the opening. Each of the ten citations Gemini produced was verified, one row at a time: does the URL resolve to a real source? Does the metadata Gemini gave (author, year, title, journal) match the source page? Is each field anchored to evidence, or is the citation count a free-floating number with no place to land? Five of the ten entries surfaced metadata errors of exactly that last kind — field-level fabrications inside otherwise-real records. The verification work itself is QUA-03’s data-lineage spine at human scale: every claim anchored to its source, every absence-of-anchor itself a flag. Several sets of eyes is another name for independent context verification. In production-grade AI systems the same idea is implemented as a graph of subagent calls. In the research-production system of Global South Insights (GSI) — a research project of Tricontinental: Institute for Social Research — dozens of producer-verifier pairs run in independent subagents, with no self-certification anywhere; the spreadsheet and the stack of emails become a workflow that runs on a single command. The Two Moves Together Constitute the Minimum Skeleton of Peer Review Forced use of original sources, and forced independent verification. Both moves are cheap. Neither depends on a smarter model. Either can be reused by anyone. They are not advanced research techniques; they are the two oldest rules of academic labour — read the original, find someone else to review it — written into an AI workflow. The standard posture towards AI hallucination is passive defence. Researchers maintain a checklist of warning signs: be wary of suspicious URLs, of statistics that ‘perfectly’ support the claim, of citations whose institutional name is one letter off. Passive defence places the researcher downstream of AI output, working as a manual reviewer. It is exhausting, and it depends on luck. Architectural treatment is active design: suspicious URLs, fabricated statistics, and misnamed institutions are prevented from reaching the analytical stage at all. End-to-end empirical evidence already exists. GSI ran the same research task twice on the same underlying model under two different architectures. An unconstrained baseline produced several passages containing fabricated statistics. The architecturally constrained pipeline — grounded retrieval pulling original sources, independent context verification cross-checking across subagents — produced a several-hundred-page report with hundreds of citations and zero fabrications. What Architecture Cannot Do, the Researcher Must Bringing the fabricated-citation rate to zero is a technical victory. It is not an epistemological one. Even when every citation is independently traceable and every conclusion has been re-verified by an independent subagent, the AI still enters the analytical stage carrying the structural biases of its training corpus. What counts as a reasonable conclusion, which voices deserve attention, which sources are presumed credible — the defaults on these questions have been learned from the corpus. Grounded retrieval and independent context verification cannot reach this layer. It must be set, explicitly, by instruction. Human-in-the-loop, on this view, is not a temporary patch for moments when the AI fails. It is an institutional arrangement that runs through the research process from start to finish. Alon-Barkat and Busuioc, publishing in the Journal of Public Administration Research and Theory in 2023, show empirically that even when transparency and explainability mechanisms are designed in, automation bias can still strip humans of effective oversight. Technical mechanisms, on their own, are not enough. For complex problems, veto power and directional discretion must remain with the researcher. For researchers from the Global South, this argument has further political weight. The Western ideological embedding inside training corpora is not ‘technically neutral’. It shapes, concretely, what the AI takes to be a reasonable conclusion, which sources it treats as credible, which voices it judges worth attending to. Installing POMASA does not solve this problem. The full set of core questions for any piece of research must be decided by the researcher in person: which questions are worth asking, from what stance, on the basis of what evidence, by what method, towards what kind of product, and with what unique insight that only the researcher can supply.
How to Use AI to Generate Scientific Figures and Diagrams for Your Research
Hallucination is not a defect. It is the predictable output of a training regime built to reward fluency over accuracy. The fix is not a better model. It is a different architecture.
<img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145850 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/Text-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research.jpg" alt="" width="1000" height="667" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/Text-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research.jpg 1000w, https://thetricontinental.org/wp-content/uploads/2026/06/Text-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-300x200.jpg 300w, https://thetricontinental.org/wp-content/uploads/2026/06/Text-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-768x512.jpg 768w" sizes="auto, (max-width: 1000px) 100vw, 1000px"> AI Is Redefining Scientific Visualization For a long time, creating scientific figures has been an exhausting and time-consuming process. Many researchers have experienced the same workflow: repeatedly adjusting arrows in PowerPoint just to finish a flowchart, endlessly tweaking fonts and colors in Illustrator to maintain consistency, or reorganizing entire layouts simply to make a figure more readable. The real difficulty has never been ‘not knowing how to design,’ but rather the fact that scientific figures demand accurate information, clear structure, consistent styling, and professional visual presentation at the same time — and existing tools require enormous manual effort to get every detail right. As a result, figure production has long been one of the most disproportionately costly steps in research communication: the time and energy it consumes often far exceed what the work itself should require. This is especially true for social science research in and on the Global South, where mapping commodity chains, capital flows, networks of power, or histories of struggle depends on visual communication that text alone cannot convey — yet access to professional design infrastructure has historically been out of reach. The emergence of AI has fundamentally changed this situation for the first time. Modern image-generation models are now capable of understanding module hierarchies, page layouts, workflow structures, scientific illustration styles, and even complex chart compositions. Even the long-standing issue of garbled text has improved significantly. This means researchers can finally spend less time manually arranging layouts and more time focusing on communicating ideas. Scientific Figures Are Not All the Same When many people first try AI image generation, they simply type something like ‘help me draw a scientific figure.’ In reality, however, scientific figures come in many different forms, and each type requires a completely different visual structure. The examples in this section are AI-generated figures based on Tricontinental’s dossier War on the Poor: A Frontline Report on the Effects of the Pandemic in the Global South, illustrating how each figure type can communicate different aspects of movement research. Scientific Infographics Scientific infographics function more like visual summaries. Their goal is not to present every technical detail exhaustively, but to help readers quickly grasp the research context, the problem being addressed, the core argument, and the key findings within seconds. Because of this, infographics often combine icons, modular layouts, concise text, color segmentation, and highlighted regions to establish clear visual hierarchy. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-145866" class="wp-image-145866 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-1.png" alt="" width="1672" height="941" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-1.png 1672w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-1-300x169.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-1-1024x576.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-1-768x432.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-1-1536x864.png 1536w" sizes="auto, (max-width: 1672px) 100vw, 1672px"> AI-generated infographic based on Tricontinental’s dossier War on the Poor. Compared with traditional paper figures, infographics place much greater emphasis on readability and viewing experience. They are particularly suitable for graphical abstracts, dossier opening pages, briefing summaries, public-facing research communication, and overview pages for publications. AI performs especially well in this category because it is highly effective at constructing large-scale visual structures quickly. In many cases, researchers do not even need to think about colors at the beginning; they simply need to decide what story the figure should tell. Workflow and Process Diagrams Another extremely common category is workflow and process diagrams. Their defining feature is explicit procedural logic. For example, how a policy moves through institutions, how a crisis cascades across sectors, how capital circulates between actors, or how a historical process unfolds across stages — all of these are naturally suited for flow-based visualization. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-145738" class="size-full wp-image-145738 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-2.png" alt="" width="1672" height="941" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-2.png 1672w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-2-300x169.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-2-1024x576.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-2-768x432.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-2-1536x864.png 1536w" sizes="auto, (max-width: 1672px) 100vw, 1672px"> AI-generated process diagram based on Tricontinental’s dossier War on the Poor. In many situations, readers are not primarily interested in technical detail, but rather in understanding how a process actually unfolds. The greatest value of workflow diagrams lies in making complicated processes immediately understandable. Compared with infographics, they place stronger emphasis on sequence, input-output relationships, dependencies between stages, directional arrows, and structural hierarchy. Therefore, the key criterion is not whether the figure ‘looks beautiful,’ but whether the reading path is intuitive. A well-designed workflow diagram naturally guides readers from left to right or top to bottom without visual confusion. Data Visualization If workflow diagrams explain methods, data visualization explains evidence. In research publications, most conclusions must eventually be supported through figures: how inequality has shifted over time, how an indicator compares across regions, how a trend has evolved across a decade, or whether differences between groups are significant. Explaining these purely through text quickly becomes difficult to read. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-145746" class="size-full wp-image-145746 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-3.png" alt="" width="1672" height="941" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-3.png 1672w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-3-300x169.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-3-1024x576.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-3-768x432.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-3-1536x864.png 1536w" sizes="auto, (max-width: 1672px) 100vw, 1672px"> AI-generated data visualization based on Tricontinental’s dossier War on the Poor. At its core, data visualization transforms abstract numerical relationships into intuitive visual relationships. Truly effective charts do more than merely display data; they emphasize trends, amplify differences, control information density, and establish visual focus. The same data can appear either confusing or immediately understandable depending on how the figure is designed. This is one reason why serious research publications invest considerable effort into refining visual presentation, even when the underlying analysis is relatively straightforward. An AI Workflow for Scientific Figure Generation AI figure generation is an iterative process, not a one-shot result. AI is excellent at rapidly generating layouts and first drafts, but figures that meet publication standards still require human review and refinement. Before writing any prompt, the workflow has three preparation steps. First, identify the figure type your work calls for — infographic, workflow diagram, or data visualization. Each organizes information differently: infographics emphasize conceptual integration, workflow diagrams emphasize procedural order, and data visualizations emphasize trends and differences. Second, define the structure — decide on the hierarchy: what the title, primary modules, annotations, and supporting elements are, and how they relate. Third, define the style — specify the color system, typography, emphasis regions, and reading order. The closer a prompt resembles a formal design specification, the more stable and reliable the generated result becomes. Generating Through a Prompt-Assistance Skill One approach is to use a prompt-assistance skill — a lightweight tool that reads your content and optimizes prompts for figure generation. As one example, the open-source baoyu-skills package provides a collection of such skills. To try it, open Agent and run: Please help me install this skill: npx skills add jimliu/baoyu-skills <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145754 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-4.png" alt="" width="2400" height="1466" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-4.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-4-300x183.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-4-1024x625.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-4-768x469.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-4-1536x938.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-4-2048x1251.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> After installation, restart VS Code and type /baoyu- to access a large collection of figure-generation skills. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145762 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-5.png" alt="" width="2400" height="1466" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-5.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-5-300x183.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-5-1024x625.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-5-768x469.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-5-1536x938.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-5-2048x1251.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> You can also explore different visual styles at: https://github.com/JimLiu/baoyu-skills Choose the figure-generation skill that best matches your preferred style and workflow. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145770 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-6.png" alt="" width="2880" height="1484" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-6.png 2880w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-6-300x155.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-6-1024x528.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-6-768x396.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-6-1536x791.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-6-2048x1055.png 2048w" sizes="auto, (max-width: 2880px) 100vw, 2880px"> Generating Through Configured Model APIs A more integrated approach is to configure model APIs directly, so that your Agent can generate figures from prompts without going through a web interface. By setting up OpenAI or Google API keys locally, figure generation becomes fully automated — entering a prompt produces a completed figure on your machine. Current image-generation models such as GPT Image 2 and Nano Banana 2 handle structure and layout well enough to draft usable scientific figures from a single prompt. OpenAI API keys can be obtained from: https://platform.openai.com/api-keys Google image-generation API keys are available at: https://aistudio.google.com/app/api-keys After obtaining the API keys, you can configure them inside Agent using the following command (replace [your api key] with your actual key): Please help me configure [OPENAI_API_KEY/GEMINI_API_KEY]: [your api key] <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145778 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-7.png" alt="" width="2400" height="1466" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-7.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-7-300x183.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-7-1024x625.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-7-768x469.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-7-1536x938.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-7-2048x1251.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> Of course, if you only want a lightweight experience, using APIs directly may feel overly technical. If you want both Agent’s cross-file analytical capabilities and the convenience of web-based image generation, you can additionally include the following instruction inside Agent: Please generate a detailed image-generation prompt for recreating the image. This extracts the structured prompt generated by Agent, allowing you to paste it directly into a web-based image-generation interface. While this approach may not be fully automated, it provides a low-barrier way to experience the entire workflow from analysis to generation. Using AI to Generate the First Draft Although baoyu-skills can help restructure prompts, the original prompt itself still benefits from careful refinement. In practice, the most effective prompts do not simply pile together requirements. Instead, they resemble professional design specifications with clearly defined constraints. For example: You are a scientific figure designer. Please generate a scientific workflow diagram of type [infographic/workflow/data visualization] with the topic '[your topic]'. Requirements: Clear information segmentation and intuitive reading order (top-to-bottom or left-to-right). Titles should be prominent but not oversized; labels must remain readable without becoming too dense. All text must be correctly spelled with no garbled characters or AI-generated mistakes; use sans-serif fonts for English and Heiti-style fonts for Chinese. High image quality with clean details and no obvious editing artifacts or blurred regions. Element proportions should follow realistic visual logic; avoid oversized arrows or tiny unreadable icons. Maintain a unified academic publication style. Do not use cartoon or hand-drawn aesthetics. Ensure balanced alignment and composition. The key point is not to let AI ‘freely improvise,’ but to clearly specify that the desired result is a publication-quality scientific figure rather than a generic illustration. Open Agent, invoke baoyu-skills (for example, baoyu-infographic), and use the prompt above to generate an infographic. To make the generation process more transparent, append the following sentence at the end of the prompt: Please generate a detailed image-generation prompt for recreating the image. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145786 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-8.png" alt="" width="2400" height="1466" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-8.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-8-300x183.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-8-1024x625.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-8-768x469.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-8-1536x938.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-8-2048x1251.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> After Agent finishes execution, it will produce a highly detailed image-generation prompt specifying the figure type, layout, color system, content organization, and design rules. Create a **Scientific Infographic** (visual summary / graphical abstract) following these specifications: ## Figure Type Definition This is NOT a workflow diagram and NOT a data chart panel. It is a **Scientific Infographic**: a visual summary that lets the reader grasp within **seconds** — (1) research background, (2) what problem the analysis addresses, (3) core thesis/contribution, (4) headline result. Use **modular tiles, icons, concise text, color zones, and visual hierarchy** — not sequential process arrows, not detailed statistics charts. ## Image Specifications - **Type**: Scientific Infographic (Graphical Abstract / Visual Summary) - **Layout**: `bento-grid` — modular grid with varied cell sizes, hero tile + supporting tiles - **Style**: Clean academic infographic — flat vector icons, color-coded modules, minimal text per cell. NOT cartoon, NOT hand-drawn, NOT workflow arrows, NOT chart-heavy - **Aspect Ratio**: 16:9 (landscape — standard for graphical abstracts and poster headers) - **Language**: English (sans-serif throughout; Heiti-like sans-serif for any Chinese) ## What This Figure Must Do | Goal | How to achieve | |------|----------------| | Instant comprehension | Reader understands the dossier's argument in 5–10 seconds | | Visual hierarchy | Hero tile largest; 5–6 supporting tiles with icons | | Scannability | Max 1 headline + 2 short bullet lines per tile; no paragraphs | | Emphasis | One hero statistic tile; color zones separate themes | | What to AVOID | Process arrows, step numbering, bar/line charts, swimlanes, dense data tables | ## Core Principles - **Modular, not sequential**: tiles can be read in any order; no mandatory arrow path between all cells - **Icon-led**: each tile has one clear flat icon representing its theme - **Text minimalism**: headline words + short phrases only; preserve key facts verbatim where used - **Color zones**: each tile group uses distinct Bandung Circuits background tint to signal theme - Ample whitespace between tiles; strict grid alignment - NO cartoon, hand-drawn, watercolor, or illustrative narrative styles ## Text Requirements - **CRITICAL**: Zero typos, garbled characters, or AI misspellings - Title prominent but NOT oversized — balanced against tile grid - Body per tile: max 2 lines, clearly legible, not dense - **All English**: clean sans-serif (Helvetica, Arial, Inter, Poppins) - **Chinese (if any)**: Heiti-like sans-serif (Source Han Sans) - NO serif fonts ## Bandung Circuits Color System | Role | Hex | Usage in this infographic | |------|-----|---------------------------| | Deep Indigo | `#1A0A2E` | Title, tile headlines, icon strokes — first color registered | | Terracotta | `#C4572A` | Accent rules, tile borders, pull-quote bar | | Golden Ochre | `#D4A03C` | Hero statistic numeral — sparingly | | Sage Green | `#5A7A6B` | Campesino-impact tile background only | | Warm White | `#FAF5EF` | Canvas | | Parchment | `#F2E8D8` | Alternating tile fills | | Charcoal | `#2A2A2A` | Body text | | Muted Teal | `#2A7B88` | Policy-solution tile accent | | Signal Red | `#D94F30` | "Myth vs Reality" contrast label — sparingly | **Rules**: Max 3 colors per tile; **SAFFRON SAFEGUARD** — never orange-spectrum + Sage Green in same tile; no gradients, shadows, or gloss. --- ## Bento Grid Layout (6 Tiles + Header) ### Header Band (full width, slim) - **Title**: "The War on the Poor" - **Subtitle**: "Narcotics, Campesinos, and Capitalism" - **Source**: "Tricontinental: Institute for Social Research" - Deep Indigo title on Warm White; Terracotta thin rule below --- ### TILE A — Hero (2×1, top-left, largest) **Icon**: Scales of justice tilted toward a bank building (flat line icon) **Headline**: "Core Thesis" **Text** (concise): - "War on Drugs ≠ moral crusade" - "Illicit money liquefies the banking system" - "Imperial tool against peasants & sovereign states" **Fill**: Parchment; Terracotta left accent bar --- ### TILE B — Background / Problem (1×1, top-right) **Icon**: Globe with crossed-out "moral crusade" label **Headline**: "The Problem" **Text**: - "Dominant narrative: drug trade is separate from capitalism" - "Reality: underground circuits serve formal finance" **Fill**: Warm White; Deep Indigo border --- ### TILE C — Research Lens (1×1, mid-left) **Icon**: Simplified Colombia map outline + coca leaf **Headline**: "Research Lens" **Text**: - "Colombia's coca-cocaine economy" - "Campesinos at bottom of commodity chain" **Fill**: Parchment --- ### TILE D — Hero Statistic (1×1, mid-center, visual emphasis) **Icon**: Upward arrow with dollar sign **Headline**: "Key Finding" **Hero numeral** (Golden Ochre, large): **"62,000–80,000×"** **Text**: - "Price increase: farm gate → wholesale" - "$0.56/kg → $44,580/kg" **Fill**: Deep Indigo background; Warm White text; Golden Ochre numeral --- ### TILE E — Structural Insight (1×1, mid-right) **Icon**: Two overlapping circles (legal / illegal) with dashed boundary **Headline**: "Political Frontier" **Text**: - "Legal ↔ illegal drugs: not chemical, but political" - "States protect corporate profits; criminalise peasants" **Fill**: Warm White; Muted Teal icon accent --- ### TILE F — Human Cost (1×1, bottom-left) **Icon**: Farmer figure with land (dignified, not pity framing) **Headline**: "Who Pays the Price" **Text** (Sage Green tint background — no terracotta here): - "81% land held by top 1%" - "57% poverty in coca-growing households" - "Symptom, not cause — blocked subsistence" **Fill**: Sage Green tint (#5A7A6B at 15% opacity on Parchment) --- ### TILE G — Policy Takeaway (2×1, bottom-right) **Icon**: Seedling / land reform symbol **Headline**: "Path Forward" **Two-column mini contrast** (no arrows): - ✗ Militarisation | Eradication | Criminalisation - ✓ Land reform | Guaranteed prices | Confront laundering **Fill**: Parchment; Muted Teal checkmarks; Signal Red crosses --- ### Footer (full width, slim) "Source: Tricontinental — The War on the Poor (CC BY-NC 4.0) | thetricontinental.org" Dark Gray, sans-serif regular --- ## Text Labels (verbatim where data appears) **Title block**: "The War on the Poor" | "Narcotics, Campesinos, and Capitalism" | "Tricontinental: Institute for Social Research" **Tile headlines**: "Core Thesis" | "The Problem" | "Research Lens" | "Key Finding" | "Political Frontier" | "Who Pays the Price" | "Path Forward" **Key data**: "62,000–80,000×" | "$0.56/kg → $44,580/kg" | "81% land top 1%" | "57% poverty" **Footer**: "Source: Tricontinental — The War on the Poor (CC BY-NC 4.0)" --- ## Final Quality Checklist - [ ] Reads as **visual summary**, NOT workflow, NOT data dashboard - [ ] 6 modular bento tiles + header + footer; no sequential step arrows between all tiles - [ ] Each tile: icon + headline + max 2 short text lines - [ ] Hero statistic "62,000–80,000×" visually dominant in Tile D - [ ] Bandung Circuits colors; Saffron Safeguard observed - [ ] Sans-serif only; zero typos; academic publication quality - [ ] No cartoon/hand-drawn; clean alignment and balance You can then continue using AI to generate a complete scientific infographic draft. For example: <img loading="lazy" decoding="async" aria-describedby="caption-attachment-145730" class="size-full wp-image-145730 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1.png" alt="" width="1672" height="941" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1.png 1672w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-300x169.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-1024x576.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-768x432.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-1-1536x864.png 1536w" sizes="auto, (max-width: 1672px) 100vw, 1672px"> AI-generated infographic produced from the prompt above, based on Tricontinental’s dossier War on the Poor. Human Review Still Matters Even though AI can now generate surprisingly mature figures, human review remains essential. The first draft usually needs careful inspection: text accuracy, font hierarchy, color consistency, whitespace, arrow thickness, border weight, and shadow usage all require attention. In many cases, what determines whether a figure truly ‘looks like a paper figure’ is not the core content itself, but these subtle details. The good news is that the amount of manual work required is now dramatically smaller than drawing everything from scratch. You can use Illustrator, Photoshop, or even PowerPoint to perform final refinements on exported figures. In other words, AI provides speed, while humans provide judgment. This is currently the most practical collaborative workflow. HTML Is Becoming a New Approach to Scientific Visualization For complex data visualization, pure image generation is not always the best solution. Many scientific charts require precise control over axes, data relationships, layout proportions, and export quality. In these situations, asking AI to generate HTML or JavaScript chart code is often more stable, more controllable, and easier to modify later. One particularly recommended tool is Open Design. It is essentially an AI-driven visualization platform capable of generating HTML charts directly from natural-language descriptions while providing real-time previews. Its greatest advantage is that the output is not a fixed image, but an editable, scalable, and exportable visualization page. Download the appropriate version for your operating system from: https://github.com/nexu-io/open-design/releases/tag/open-design-v0.8.0 <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145794 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-9.png" alt="" width="2878" height="1490" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-9.png 2878w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-9-300x155.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-9-1024x530.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-9-768x398.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-9-1536x795.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-9-2048x1060.png 2048w" sizes="auto, (max-width: 2878px) 100vw, 2878px"> After installation and configuration, create a new Open Design project. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145802 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-10.png" alt="" width="2522" height="1472" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-10.png 2522w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-10-300x175.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-10-1024x598.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-10-768x448.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-10-1536x897.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-10-2048x1195.png 2048w" sizes="auto, (max-width: 2522px) 100vw, 2522px"> Then enter the project name and select the desired design system style. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145810 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-11.png" alt="" width="2522" height="1472" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-11.png 2522w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-11-300x175.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-11-1024x598.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-11-768x448.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-11-1536x897.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-11-2048x1195.png 2048w" sizes="auto, (max-width: 2522px) 100vw, 2522px"> Once the project is created, you can directly describe the visualization you want using natural language. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145818 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-12.png" alt="" width="2522" height="1472" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-12.png 2522w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-12-300x175.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-12-1024x598.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-12-768x448.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-12-1536x897.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-12-2048x1195.png 2048w" sizes="auto, (max-width: 2522px) 100vw, 2522px"> For example: Please generate a high-quality scientific data visualization chart using HTML. The overall style should resemble figures from Nature or IEEE papers. Topic: [your topic] Data: [your data] Requirements: White background, strict alignment, unified typography, no cartoon style, natural spacing between bars, all values clearly readable, and no animations or shadows. After generation, the HTML chart preview will appear in real time on the right side. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145826 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-13.png" alt="" width="2560" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-13.png 2560w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-13-300x184.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-13-1024x628.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-13-768x471.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-13-1536x942.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-13-2048x1256.png 2048w" sizes="auto, (max-width: 2560px) 100vw, 2560px"> Compared with traditional screenshot-based workflows, the greatest advantage of this approach is that the charts are genuinely editable, scalable, and reusable frontend visualizations. Finally, you can export the results as PDF, PPTX, or HTML for use in papers, websites, or presentations. <img loading="lazy" decoding="async" class="aligncenter size-full wp-image-145834 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-14.png" alt="" width="2560" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-14.png 2560w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-14-300x184.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-14-1024x628.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-14-768x471.png 768w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-14-1536x942.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/06/09-How-to-Use-AI-to-Generate-Scientific-Figures-and-Diagrams-for-Your-Research-14-2048x1256.png 2048w" sizes="auto, (max-width: 2560px) 100vw, 2560px"> Conclusion AI is dramatically lowering the barrier to scientific figure creation. In the past, producing professional scientific graphics required substantial design experience. Today, researchers can quickly generate visually coherent and structurally clear scientific illustrations. More importantly, however, the real transformation is not simply that ‘drawing figures has become faster,’ but that scientific communication itself is changing. For the theory and methodology behind what makes an infographic work, see the companion article Demystifying Infographic Design. Future research workflows will likely evolve into a collaborative system where AI handles understanding and generation, design systems maintain stylistic consistency, and researchers focus on scientific accuracy and aesthetic judgment. Scientific figures are no longer just supplementary illustrations inside papers; they are gradually becoming central components of research communication itself. This may be the perfect time to try using AI to create the first truly professional figure for your next paper.
This edition features 17 publishers from various countries in the Global South, as well as the Amílcar Cabral Foundation of Cape Verde and the Tricontinental Institute for Social Research. These texts highlight the importance of the Russian Revolution and Lenin’s legacy for anti-colonial struggles, particularly for the liberation movements in Africa during the 1970’s. This […]
This edition features 17 publishers from various countries in the Global South, as well as the Amílcar Cabral Foundation of Cape Verde and the Tricontinental Institute for Social Research. These texts highlight the importance of the Russian Revolution and Lenin’s legacy for anti-colonial struggles, particularly for the liberation movements in Africa during the 1970’s. This book includes an introduction by Desmond Fonseca that contextualizes Amílcar Cabral’s life and thought within the history of Guinea-Bissau, Cape Verde, and the leftist movement. In addition, the texts by Luiz Fonseca, president of the Amílcar Cabral Foundation in Cape Verde, and João Pedro Stedile, a member of the coordinating committee of Brazil’s Landless Rural Workers’ Movement, highlight the importance and relevance of Amílcar Cabral’s thought and praxis for social struggles today. Download PDF <img loading="lazy" decoding="async" class="size-large wp-image-145279 aligncenter img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/Amilcar-Cabral-book-cover-662x1024.jpg" alt="" width="662" height="1024" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/Amilcar-Cabral-book-cover-662x1024.jpg 662w, https://thetricontinental.org/wp-content/uploads/2026/06/Amilcar-Cabral-book-cover-194x300.jpg 194w, https://thetricontinental.org/wp-content/uploads/2026/06/Amilcar-Cabral-book-cover-768x1187.jpg 768w, https://thetricontinental.org/wp-content/uploads/2026/06/Amilcar-Cabral-book-cover-994x1536.jpg 994w, https://thetricontinental.org/wp-content/uploads/2026/06/Amilcar-Cabral-book-cover-1325x2048.jpg 1325w, https://thetricontinental.org/wp-content/uploads/2026/06/Amilcar-Cabral-book-cover.jpg 1790w" sizes="auto, (max-width: 662px) 100vw, 662px">
East Asia’s Double Bind: Contradictions and Possibilities in the New Cold War
This is the seventh joint book by the International Union of Left Publishers (IULP) and brings together three articles by Amílcar Cabral, a revolutionary and leader of the liberation movements in Guinea-Bissau and Cape Verde, which have remained little known until now.
The images in this dossier, edited by Tricontinental’s art department, highlight the work of Kinjo Minoru, an Okinawan sculptor who honours the generations that have resisted war and occupation. For decades, Kinjo has carved the atrocities committed during and after the World Anti-Fascist War (widely known as the Second World War) era. Kinjo works in concrete, plaster, and metal – the same materials now being poured into Okinawa to build yet another US military base. In Okinawa – today a frontline in the New Cold War – Kinjo’s sculptures stand as memory and material refutation: a rough, heavy history that refuses to be smoothed over. 1 <img loading="lazy" decoding="async" class="alignnone size-medium wp-image-145074 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/ISC-300x100.jpeg" alt="" width="300" height="100" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/ISC-300x100.jpeg 300w, https://thetricontinental.org/wp-content/uploads/2026/06/ISC-1024x342.jpeg 1024w, https://thetricontinental.org/wp-content/uploads/2026/06/ISC-768x257.jpeg 768w, https://thetricontinental.org/wp-content/uploads/2026/06/ISC.jpeg 1278w" sizes="auto, (max-width: 300px) 100vw, 300px"> <img loading="lazy" decoding="async" class="alignnone size-medium wp-image-123601 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2025/06/ncw-logo-300x260.jpg" alt="" width="300" height="260" srcset="https://thetricontinental.org/wp-content/uploads/2025/06/ncw-logo-300x260.jpg 300w, https://thetricontinental.org/wp-content/uploads/2025/06/ncw-logo-768x666.jpg 768w, https://thetricontinental.org/wp-content/uploads/2025/06/ncw-logo.jpg 785w" sizes="auto, (max-width: 300px) 100vw, 300px"> <img loading="lazy" decoding="async" class="alignnone size-medium wp-image-145062 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/IPA_EN-300x119.png" alt="" width="300" height="119" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/IPA_EN-300x119.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/IPA_EN.png 663w" sizes="auto, (max-width: 300px) 100vw, 300px"> <img loading="lazy" decoding="async" class="alignnone size-medium wp-image-145051 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/06/Logo_EN_Tricontinental-300x69.png" alt="" width="300" height="69" srcset="https://thetricontinental.org/wp-content/uploads/2026/06/Logo_EN_Tricontinental-300x69.png 300w, https://thetricontinental.org/wp-content/uploads/2026/06/Logo_EN_Tricontinental.png 677w" sizes="auto, (max-width: 300px) 100vw, 300px"> When the United States and Israel began their illegal war of aggression against Iran on 28 February 2026, it was inevitable that Iran would retaliate by restricting transit through the Strait of Hormuz. While Iran has never closed or restricted movement through the strait before, the government in Tehran had made it clear that the geography of the strait would become part of its defensive strategy if provoked. For the countries of Asia, the Strait of Hormuz and the Strait of Malacca are vital pathways – chokepoints – for the flow of goods, especially energy. Around 90% of Japan’s oil and 75% of South Korea’s passes through the strait. Any slowdown at the strait dramatically impacts the energy-hungry industrial economies of East Asia. From an economic perspective, the US-Israeli war on Iran is also a war against the interests of Japan and South Korea – and indeed every Asian country that relies on oil from the Persian Gulf. Despite this fact, many Asian countries have either maintained diplomatic silence or, as in the case of Japan and South Korea, openly backed the United States. Countries like Japan and South Korea align with the United States against their own economic self-interest because they were absorbed into the US military architecture after the end of the World Anti-Fascist War (widely known as the Second World War).2 The continued presence of massive US military bases in these countries inexorably draws them into the US’s forever wars. These countries cannot break with the US on the war on Iran as long as they are militarily subordinated to it. The US’s principal military target in Asia is not Iran but China, which is a leading trade partner of Japan, South Korea, the Philippines, Taiwan, and most other Asian countries. Given China’s centrality in the region’s industrial chains, any aggression against it would disrupt the entire development paradigm of East Asia. On the other hand, the US remains the principal military patron of Japan, South Korea, the Philippines, and Taiwan, as well as a major export market for several of them. This places these economies in a double bind: they can neither break easily from their military and economic dependence on the US nor can they break from their vital economic relationship with China – the new factory of the world. In East Asia’s Double Bind: Contradictions and Possibilities in the New Cold War, we look at how Japan, South Korea, the Philippines, and Taiwan are caught in an intractable contradiction that persists regardless of changes in government. Although our focus is on East Asia, we also briefly analyse the role of states like Australia and India in this conjuncture. The contradictions explored in this dossier are primarily economic and geopolitical, yet they pose possibilities to advance the class struggle in these societies by exposing the need to break from subordinate alliances with imperialism. East Asia and the Role of China Over the past thirty years, Japan, South Korea, the Philippines, and Taiwan have seen a dramatic shift in their trade patterns and development trajectories.3 During the Cold War, the United States was the principal anchor of the region’s economic order, followed by Japan during the late twentieth century.4 Today, the new centre of gravity is China, which plays a central – though uneven – role across these economies. While each has its own development model and political relationship with Beijing, all four are deeply integrated into a production network in which China functions as a manufacturing hub, supply chain anchor, and primary market. Studies by the World Bank and the Asian Development Bank have clearly demonstrated China’s economic significance in East Asia.5 China is the single largest trading partner for Japan and South Korea, accounting for roughly 20–25% of each country’s exports. Taiwan’s relationship is even stronger, with 30–40% of its exports going to China. The Philippines is less integrated, but China still ranks among its top trading partners, absorbing roughly 15–20% of exports. These figures indicate that a significant share of East Asian economic activity is directly tied to demand from China’s industries.6 When viewed in relation to overall economic output, the importance of China becomes even clearer. Trade with China, namely total exports, accounts for a tenth of South Korea’s Gross Domestic Product (GDP). A quarter of Taiwan’s GDP is tied to trade with mainland China. Japan, with a much more domestic-oriented economy, nonetheless has 5% of its GDP tied to exports to China (roughly the same percentage of its GDP is tied to the US, which includes the economic impact of the 120 US military facilities in Japan). The Philippines, while less export intensive, has around 6% of its GDP tied to exports to China.7 The vitality of the Chinese economy is therefore directly tied to the levels of output, employment, and investment in all of East Asia. At the 2011 Association of Southeast Asian Nations (ASEAN) summit in Bali, Indonesia, member states discussed the necessity of creating a regional framework for economic integration. These discussions eventually led to the Regional Comprehensive Economic Partnership (RCEP), a trade agreement signed in 2020 and brought into force in January 2022. The RCEP accounts for roughly 30% of the world’s population and 30% of global GDP. Spanning economies from New Zealand to Japan, it brings together a range of industries, from mining to high technology, and a market of 2.2 billion consumers. Signatories have agreed to reduce or eliminate tariffs by 92% over twenty years. Japan, South Korea, and the Philippines are part of the RCEP, which reinforces trade flows and formalises the interconnected economic space in which China is the largest economy.8 Beneath aggregate trade figures, the structure of production further reinforces this integration. China is not only a final market but also a central node in regional and global industrial chains as a major consumer and producer of intermediate goods. Japanese and South Korean firms export high-value components – such as machinery and automobile parts, petrochemicals, and semiconductors – that are often assembled or processed in China before being re-exported globally. Taiwan’s semiconductor industry is deeply intertwined with Chinese manufacturing, as chips produced in Taiwan are often sent to China for integration into finished electronics.9 These integrated production structures have created sectoral interdependencies. South Korea’s semiconductor industry – led by firms such as Samsung Electronics and SK Hynix – relies on demand from Chinese electronics manufacturing. Japan’s automotive and machinery sectors – led by firms such as Toyota, Honda, Nissan, Mazda, Komatsu, Hitachi, and Mitsubishi – rely on Chinese consumers and production networks. Taken together, these trade and production links show that all four economies are structurally linked to China, even though the degree of integration varies (it is the highest in Taiwan and South Korea and more moderate in Japan and the Philippines). This creates both opportunities for growth and vulnerabilities as US pressure on China reverberates across the region. The Garland of US Military Bases Over the past decade, the United States has consolidated a coherent military strategy aimed at encircling China. This ‘strategy of denial’ was formalised in successive US National Defense Strategy documents and articulated prominently in Elbridge A. Colby’s 2021 book The Strategy of Denial: American Defense in an Age of Great Power Conflict. Colby led the development of the 2018 National Defense Strategy as deputy assistant secretary of defence for strategy and force development during Trump’s first term and is now the US under-secretary of war for policy as well as a leading strategist behind the Trump administration’s approach to China.10 At the core of the strategy of denial is the idea that the Indo-Pacific – stretching from East Africa to the west coast of the United States and encompassing the Indian and Pacific oceans – is the most economically significant region in the world. US strategic interests depend on preventing China from displacing US primacy in the Indo-Pacific region. The strategy rests on deterrence through military superiority and alliance coordination, which has been institutionalised through the Quadrilateral Security Dialogue or Quad, which brings together Australia, India, Japan, and the United States (2017); AUKUS, the trilateral security partnership between Australia, the United Kingdom, and the United States (2021); the Pacific Deterrence Initiative, a US military funding and force-posture framework for the Indo-Pacific (2021); and the US-Japan-South Korea Trilateral Agreement (2023).11 Rather than direct confrontation, as with Iran, the US seeks to raise China’s cost of defence to an unacceptable level by strengthening the US-based alliance system and the forward positioning of US military bases. There are currently about 270 US military facilities stretching from Diego Garcia in the Chagos Archipelago to Guam. Central to this strategy is Washington’s belief that a credible US military capability can constrain China’s strategic choices while preserving a US-led regional order and continuing to draw on China’s role as an economic engine for the region. Taiwan occupies a critical place in this US framework.12 On 1 January 1979, the United States formally recognised the People’s Republic of China and acknowledged Beijing’s position that there is ‘One China’, of which Taiwan is a part. However, on 10 April 1979, the US Congress passed the Taiwan Relations Act, which provided the legal basis for Washington to maintain an unofficial relationship with Taiwan. This allowed the US to play a double game, formally acknowledging the One China framework while provoking Beijing through arms sales to Taiwan and maintaining direct economic and cultural ties with Taipei. Since 1950, the United States has sold Taiwan nearly $50 billion in defence equipment and services.13 For the US, Taiwan’s status is not only political but strategic because Taiwan’s reunification with the mainland would give China significantly greater access to the Pacific Ocean. For Washington, Taiwan is an instrument to pressure Beijing and constrain China. The US containment strategy is geographically organised through a system of encirclement that begins with the first island chain (an arc of islands that stretches from Japan to the Philippines and acts as a barrier to China’s access to the Pacific Ocean). This extends into the wider ‘encirclement depth’ of Diego Garcia, Sri Lanka, and the US bases in the Persian Gulf region.14 The US has developed a network of bases and access agreements along this chain to control key nodes and shipping routes and to constrain Chinese military mobility. This encirclement strategy includes not only large, permanent military installations (such as those in Japan and South Korea) but increasingly a dispersed network of smaller, more flexible sites across the Pacific and Indian oceans designed to enhance military resilience. The bases are integrated with surveillance, intelligence, and missile systems that enable monitoring and rapid response. Together, this military network constitutes a structured system of containment. While US national security documents frame this as defensive deterrence, the effective positioning of US forces along China’s border creates tensions rather than resolving them. The US strategic framework of containment and encirclement has been operationalised through a sustained expansion of US military capabilities and infrastructure in East Asia, particularly over the past two decades and with increasing intensity since 2020. The US has also been funding large-scale military exercises such as Exercise Balikatan (with the Philippines), Exercise Malabar (with Australia, India, and Japan), and Exercise Talisman Sabre (with Australia). These efforts are designed to improve military interoperability and turn US allies from regional partners into frontline participants in the containment of China. One of the more recent frameworks advanced by the US is the Pacific Deterrence Initiative (PDI), which was established by the 2021 US National Defence Authorisation Act.15 The PDI ensures dedicated funding for force deployment, base infrastructure, missile defence, and joint exercises with US allies such as Japan, South Korea, and the Philippines. In Japan, the PDI has ensured upgrades to missile defence and rapid deployment forces. In South Korea, it has enabled joint exercises, while in the Philippines it has upgraded US bases and surveillance systems. The PDI also underpins the integration and deployment of long-range precision missile systems across the Indo-Pacific. This includes the expanded air and missile defence capacities that have been built up at US military bases in places such as Guam and the Mariana Islands as well as Basa Air Base in the Philippines (for which the US government allocated around $66 million in 2023).16 The PDI ensures intelligence, surveillance, and reconnaissance systems that enhance the tracking of regional military activity and enables what is known as ‘precision targeting’ – the rapid identification and accurate striking of military targets. These developments have transformed countries like Japan, South Korea, and the Philippines into forward operating platforms for US aggression. Sowing Conflict: Class Contradictions and the Limits of Democracy The US strategy of denial depends not only on military integration but also on the alignment of the ruling classes across the first island chain into a coordinated anti-China posture – particularly in Japan, Taiwan, and the Philippines, and more broadly in neighbouring South Korea. This alignment reflects the interests of the domestic industrial, military, and political elites tied to US power. Across Japan, South Korea, the Philippines, and Taiwan, the deepening of US military integration sharpens existing class contradictions and exposes the narrowness of electoral systems. While this generates resistance from below, these political systems are designed to prevent the growth of any force that is inimical to US intervention. Additionally, each of these societies bears the scars of the World Anti-Fascist War and the postwar US military presence, including military bases that are now seemingly permanent – an experience that has continued to define the political outlook of these ‘client states’.17 Japan Japan’s postwar political system has been dominated by the Liberal Democratic Party (LDP), a right- to far-right political formation with intimate ties to the US state and capital. While formally democratic, Japan’s political system is effectively dominated by a single party, with the LDP in office for all but four years since its formation in 1955. Though article 9 of Japan’s 1947 Constitution, sometimes called the ‘pacifist clause’, forbids a military build-up going beyond minimal defence, the political right has called for its removal since the premiership of Nobusuke Kishi (1957–1960). In 2014, during the premiership of Kishi’s grandson, Shinzō Abe (2012–2020), article 9 was reinterpreted to allow for ‘collective self-defence’, enabling the expansion of Japanese military spending – which has risen particularly since 2022 under prime ministers Fumio Kishida, Shigeru Ishiba, and Sanae Takaichi. Between 2023 and 2024, Japanese military spending rose by 21%, accounting for 1.4% of the country’s GDP.18 In April 2026, under Takaichi, Japan lifted a ban on the export of lethal weapons, which had been put in place based on the logic that a pacifist country should not profit from wars. <img loading="lazy" decoding="async" class="alignnone size-full wp-image-145011 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/D101_Kinjo_1.jpg" alt="" width="505" height="780" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/D101_Kinjo_1.jpg 505w, https://thetricontinental.org/wp-content/uploads/2026/05/D101_Kinjo_1-194x300.jpg 194w" sizes="auto, (max-width: 505px) 100vw, 505px"> The contradiction between military spending and democratic demands that Japan’s wealth be invested on social needs – exemplified by anti-base protests in poorer regions like Okinawa – reveals the limitations of Japan’s formal democracy. Japanese society remains subordinated to military priorities defined by a permanent Japanese elite aligned with the US. The construction of a new Marine Corps base in the Henoko-Oura Bay area of Okinawa, intended to replace Futenma Air Station – long criticised for its location in the middle of densely populated Ginowan – has faced continuous opposition since 1996. In 2018, Denny Tamaki was elected governor of Okinawa on an anti-base platform; in a prefectural referendum held in 2019, 70% of respondents opposed the construction of the base. Despite such democratic mandates and decades of legal challenges, Japan’s central government proceeds with landfill operations that are destroying Oura Bay’s coral ecosystems on behalf of the US military.19 Organisations including the All Okinawa Council Against Construction of New Base in Henoko, the Okinawa Peace Movement Center, the Okinawa Environmental Justice Project, and the Henoko sit-in protesters – who have maintained daily resistance for over two decades – embody a politics that connects local struggle to broader questions of imperialism and self-determination.20 South Korea South Korea’s political history is marked by intense class struggles. Born amid the Korean War, which began in 1950 and remains formally unresolved since the 1953 armistice did not produce a peace treaty, South Korea has been treated by the United States as a military base and economic bulwark against communism. Though it has been under pro-US administrations, including a military dictatorship from 1967 to 1988, South Korea’s political system has appeared more fluid than Japan’s: no single party has ruled continuously. Nonetheless, elected governments, both conservative and liberal, have remained structurally dependent on the US. For example, this was the case under both Yoon Suk-yeol, a conservative strongly aligned with the United States and the chaebols (South Korean conglomerates), and Moon Jae-in, a liberal who sought limited autonomy but remained tied to export-oriented capital and the chaebols. In fact, in 2018, during Moon Jae-in’s liberal presidency, South Korea’s military spending rose to 2.5% of GDP, establishing a level that subsequent annual budgets have continued to pursue (it rose to 2.6 % in 2022).21 Since the mid-2010s, South Korea has seen a wave of democratic struggles, from the Candlelight Revolution or Chot–bul Hyuk-myung (2016–2017), which removed President Park Geun-hye from office, to the Revolution of Lights or Bit-eh Hyuk–myung (2024–2025), which sought to defend South Korean democracy against the martial law imposed by President Yoon Suk-yeol in December 2024. Despite repeated working-class and civil society mobilisation against inequality and calls for greater foreign policy independence, South Korea’s subordination to the US has prevented such transformation. Furthermore, South Korea’s economic and military dependence on the US means that it must adopt deeply unpopular measures such as dispatching Korean troops to Iraq or installing the Terminal High Altitude Area Defense (THAAD) anti-ballistic missile system. Since its inception, South Korea has deferred its foreign policy to the US. One result of this is that the failed 2019 North Korea-United States Hanoi Summit resulted in a freeze in inter-Korean relations.22 Meanwhile, the Democratic People’s Republic of Korea’s (DPRK) deepening ties with Russia have expanded Pyongyang’s room for manoeuvre. In June 2025, Lee Jae-myung won the presidency after playing a role in preventing President Yoon from imposing martial law some months earlier. A human rights and labour lawyer, President Lee has nonetheless continued to entangle South Korea’s military-industrial complex with the US. Even as Lee attempts to regain wartime operational control of the Korean military, his economic concessions to US President Donald Trump have embedded South Korea even deeper in the US war machine. Not only has Lee agreed to US calls for allies to spend 3.5% of GDP on defence, but South Korea will also invest $350 billion over the next ten years to increase US semiconductor fabrication (with their dual use enabling the expansion of military AI) and expand US naval shipbuilding, helping to relieve chronic bottlenecks in the US maritime industrial base, a push captured in the sycophantic Korean slogan MASGA: Make American Shipbuilding Great Again. More specifically, the South Korean Hanwha Group’s acquisition of the Philadelphia Shipyard in 2024 allows it to serve as a potential solution to the backlog of nuclear-powered submarines in the US Navy and contribute to the production of US Navy warships. Furthermore, South Korea hosts a US Space Force presence that cooperates with the US in creating a network of interoperable satellites for Trump’s Golden Dome.23 All these actions have allowed South Korea to join Israel in the US club of ‘model allies’.24 The Philippines The Philippines has struggled to assert its sovereignty since it was seized by the United States in 1898. Political power in the country has been dominated by a few elite families (for instance, the current president, Bongbong Marcos, is the son of Ferdinand Marcos, who was president from 1965 to 1986). The country relied entirely on the US for its security plans until 1991, and in 1995 launched the Armed Forces of the Philippines Modernisation Program, which allowed for the expansion of the Philippine navy and air force, largely through the purchase of US military equipment. The Philippines’ military became integrated with that of the US through procurement and joint exercises. The structure of US power over the Philippines is best illustrated by the Enhanced Defense Cooperation Agreement (EDCA), first signed in 2014 and then expanded in 2022. EDCA allows US military forces rotational access to Philippine military bases, enabling the pre-positioning of equipment, joint training, and the construction of US military infrastructure on the bases, with minimal oversight from the Philippine government. In 2023, early in the Marcos Jr. administration, designated sites under EDCA were nearly doubled (increasing from five to nine). The Camilo Osias Naval Base and Lal-lo Airport are located at the northern tip of the Philippines, allowing ‘rapid response’ to conflicts in the Taiwan Strait.25 These two bases are supported by the Camp Melchor F. Dela Cruz in the mountainous Cagayan Valley, which acts as a logistical rear. The US presence at these bases helps Washington project force across the Luzon Strait, which the Philippines shares with Taiwan. The fourth newly designated site has not been publicly disclosed, but its location makes clear its role in US projection in the South China Sea. Through EDCA, US forces conduct Exercise Balikatan, which has reached unprecedented scale under the Marcos Jr. administration, with Japan even joining in 2025. Civil society organisations and peace activists continue to debate the implications of the Marcos Jr. administration’s close alignment with the US. This alignment has unfolded alongside intensified repression of activists and rural organisers, including the killing of nineteen people by Philippine troops in Toboso, Negros Occidental, in April 2026 – an incident that human rights groups have called to be independently investigated. Taiwan After the nationalist Kuomintang (KMT) was defeated in the Chinese Revolution, it fled to the island of Taiwan under the leadership of Chiang Kai-shek and constructed its government there. The KMT ruled Taiwan under martial law for thirty-eight years, until 1987, and then continued to rule in a one-party dominated electoral system until 2000. Since then, the Democratic Progressive Party (DPP) has largely been in power, moving Taiwanese politics further towards separatism from mainland China and towards integrating the island more deeply into US strategic plans. The DPP reflects a coalition of techno-capitalists, separatist elites, and military institutions, while the KMT draws its support from businesses with interests in cross-strait trade with China. Both, however, operate within a framework shaped by US strategic priorities. Since 2022, Taiwan’s military spending and US military support have shown a pattern of steady, coordinated strengthening rather than sudden rearmament. Taiwan’s military budget has exploded, reaching approximately $30 billion in 2026. Military spending has risen from 2% of GDP in the 2010s to 3.3% in 2026, with plans to increase to 5% by 2030. This massive diversion of resources falls on a society already confronting stagnant wages and rising living costs. The military budget finances arms purchases and enriches US defence contractors. US military sales to Taiwan have become more regular, with frequent arms packages focused on missiles, air defence, and drones. Between 2019 and 2024, the United States approved over $32 billion in weapons sales to Taiwan, including F-16V fighters ($8 billion), M1A2 Abrams tanks ($2 billion), HIMARS rocket systems ($436 million), and Harpoon coastal defence missiles, with massive new packages worth more than $11 billion announced in 2025.26 But arms sales are no longer the limit of US military involvement. Since 2024, US Army Special Forces, commonly known as Green Berets, have been stationed on the Kinmen and Penghu islands, the first enduring US military presence on Taiwanese territory in over forty years. The military escalation is unmistakably driven by the US, creating the conditions for a self-fulfilling crisis through militarisation while framing Chinese responses as ‘provocations’. The political fragility of this path to militarisation warrants emphasis. Lai Ching-te of the DPP took office on 20 May 2024 after winning only 40.1% of the vote, with the KMT securing 33.5% and the Taiwan People’s Party (TPP) 26.5%. Crucially, the KMT and TPP opposition controls the Legislative Yuan – Taiwan’s highest legislative organ – for the first time since 2016. Out of 113 seats, 52 are held by the KMT, 8 by the TPP, and 51 by the DPP. This political opening was underscored in April 2026, when KMT chairwoman Cheng Li-wun visited Beijing and met Xi Jinping – the first such visit by a KMT chair in a decade – signalling that part of the opposition is attempting to reopen cross-strait engagement rather than follow the DPP’s path of military escalation. The legislature did not vote for the military escalation that the DPP pursues. Public opinion polling by National Chengchi University’s Election Study Centre reveals that only 3.8% of the population, the lowest since 2002, support ‘immediate independence’, with 1.2% supporting immediate unification. Meanwhile, 83–88% prefer the status quo, with a record high of 33.2% wanting the ‘status quo indefinitely’.27 The DPP’s confrontational posture with the mainland, intensified with the 2019 Anti-Infiltration Act, aimed at curbing China’s alleged political influence in Taiwan, now lacks both a legislative and a popular mandate. Left-unificationist organisations like the Labour Party of Taiwan have argued that the social basis for the DPP’s separatism is rooted in colonial-era Japanese collaborators and that the Taiwan question is a legacy of US intervention in the Chinese Civil War. The US does not need to formally expand its presence in Taiwan in the way it does in Japan or the Philippines, as the DPP wholeheartedly supports the US strategy of containment. These trends indicate deepened US-Taiwan military integration, approaching a quasi-alliance in practice since a formal treaty would trigger a response from Beijing. Since 2022, there has been a durable militarisation of Taiwan punctuated by moments of callous disregard for Taiwan’s own development – the US has even suggested blowing up Taiwan’s semiconductor factories to protect US interests on the island.28 Beyond the First Island Chain The US strategy to contain China extends beyond the first island chain through groupings such as AUKUS and the Quad. These arrangements create overlapping layers of military cooperation that constrain China’s mobility in nearby waters and across the Indo-Pacific. They also reveal tensions between economic interdependence with China and military alliances oriented toward confrontation. The resulting contradictions raise questions about the durability of these formations. Two major actors stand out as pivotal players in this broader architecture: Australia and India. Australia Australia is a member of the Five-Eyes – an intelligence-sharing network led by the US – and is one of six ‘Enhanced Opportunities Partners’ of NATO. As such, Australia has always played a key role in US strategy in Asia. The most significant recent development in the US-Australia alliance is the 2021 AUKUS agreement, which, under its first pillar, would give Australia nuclear-powered attack submarines. The programme began with increased visits by US submarines to Australian ports, followed by rotational deployments at Australian bases, and is expected to culminate in the Royal Australian Navy’s acquisition of at least eight nuclear-powered submarines beginning in the 2030s (with a portion constructed domestically through joint cooperation in the 2040s). With a total estimated cost of more than $264 billion, these nuclear-powered submarines are strategic because they enable long-range operations across the Indian and Pacific oceans. While not explicitly stated, the interoperability and deep operational dependence on the US would make Australia part of the US posture against China, including in efforts to control sea lanes and to support US operations in the Taiwan Strait or the South China Sea. Though Australia has already paid Washington more than $1 billion under AUKUS, the Trump administration, facing its own submarine bottleneck, is reviewing whether to provide Australia with the promised submarines.29 A congressional report has even considered keeping the submarines under US control and operating them out of Australian bases given Australia’s reluctance to promise military intervention in a potential war between the US and China, as the latter is Australia’s largest trading partner.30 This is indicative of the contradictions and tensions between national interests and alliance commitments. <img loading="lazy" decoding="async" class="alignnone size-full wp-image-144941 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/D101_Kinjo_2.jpg" alt="" width="505" height="780" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/D101_Kinjo_2.jpg 505w, https://thetricontinental.org/wp-content/uploads/2026/05/D101_Kinjo_2-194x300.jpg 194w" sizes="auto, (max-width: 505px) 100vw, 505px"> India India’s position in the containment architecture differs from that of Japan or Taiwan. India has no formal alliance with the US, maintains membership in BRICS and the Shanghai Cooperation Organisation (SCO), and inherits a powerful tradition of non-alignment. Yet India’s foreign policy trajectory over the past decade reveals a trend of compliance with US strategic preferences, often disguised by the rhetoric of strategic autonomy. India has signed defence framework agreements with the US that integrate Indian forces into US command, control, and intelligence architectures. India’s drift towards Washington is most instructive when viewed in the context of its weakening relationship with Iran, a traditional friend and ally. When the Trump administration reimposed sanctions on Iran in 2018 and demanded the cessation of Iranian oil purchases, India complied by reducing imports from 500,000 barrels per day to near zero by May 2019. India’s compliance meant forgoing cheaper Iranian oil and jeopardising its investments in Iran’s Chabahar Port, a strategically important project for India because it guarantees access to Central Asia while bypassing Pakistan.31 On 12 March 2025, global 25% tariffs on steel and aluminium took effect, raising tariffs on Indian steel and aluminium to 26%. On 6 August, Trump imposed an additional 25% tariff on Indian goods over India’s purchase of discounted Russian oil, bringing the cumulative rate to 50%. India eventually agreed to halt purchases of Russian oil but stopped short of signing a decisive trade agreement with the US after the US Supreme Court overruled Trump’s tariffs. Despite these agreements with the US, India remains a member of the BRICS process and maintains important economic relations with both China and Russia. India-China bilateral trade grew 12% year-on-year in 2025, reaching $155.6 billion. India’s participation in the SCO has deepened, especially following Indian Prime Minister Narendra Modi’s visit to the 2025 SCO summit in Tianjin. In 2018, India signed a $5.4 billion deal to purchase the S-400 air defence system from Russia despite threats of US sanctions. Trade between India and Russia has surged significantly in recent years, driven particularly by discounted Russian crude oil purchases that increased from negligible levels before 2022 to a peak of two million barrels per day by 2025, making Russia the largest oil supplier to India. India’s continued trade with Russia and China sits uneasily alongside its participation in the Quad and US partnership agreements, revealing a contradiction at the heart of India’s positioning. India illustrates a pattern of graduated coercion by the US. Even as a strategic partner, India has no protection from imperial coercion.32 Alliance Fragility and Economic Contradictions The strategy of denial assumes that the US can commit its allies to containing China – an assumption that erodes upon scrutiny. The material prosperity of US allies increasingly depends on economic integration with China, even as military alignments commit them to potential conflict. Every region examined in this dossier faces the same fundamental contradiction: between economic integration with China and military alignment against China. In 2025, these countries’ trade with China – South Korea’s $331 billion, Japan’s $322 billion, the Philippines $73 billion, and Australia’s $207 billion – dwarfed their trade with the US –$241.2 billion with South Korea, $228 billion with Japan, $27 billion with the Philippines, and $89.6 billion with Australia. Even India’s trade with China ($156 billion) is larger than its trade with the US ($149 billion). These flows represent wealth, employment, and government revenue that would be devastated by war or sustained confrontation with China. When actual conflict looms, these economic interests may prove more decisive than abstract military commitments. During the US war on Iraq, significant US allies refused to participate despite enormous US pressure and invocation of alliance commitments. In Asia, Japan and South Korea refused to provide combat forces, even though they did provide logistical assistance and reconstruction funds. More recently, no US allies (including Japan and South Korea) have stepped up to Trump’s demands that they send ships to open the Strait of Hormuz. If allies proved unreliable for a war against a weaker adversary, how likely is their participation in a war against China, an industrial and nuclear power? Would Australia send combat forces to fight China, risking retaliation against Australian cities and the loss of its largest trading partner? Would South Korea participate, when a regional war might trigger intervention by the DPRK? Would Japan’s people, traumatised by the US nuclear bombing, accept casualties in combat? Would India commit forces when Taiwan’s status has no direct relevance to Indian security and participation would jeopardise relationships with China and Russia? Would the Philippines fight if it meant risking Chinese retaliation? Alliances function smoothly when costs remain hypothetical and abstract: joint exercises, intelligence sharing, arms purchases, and diplomatic coordination. They face severe tests when actual war requires sacrificing lives, accepting economic devastation, and risking national existence for another power’s interests, especially when that power is the aggressor. The strategy of denial’s reliance on allied participation may be its fatal flaw if conflict breaks out, especially when alliances rest on subordination and coercion rather than genuine shared interests. Resisting the War Machine and Building Multilateralism The emerging New Cold War, centred in East Asia, is a strategic US response to the shifting centre of gravity of the world economy. As China’s economic and technological capabilities expand, US policy is increasingly reliant on military force and alliance structures to maintain strategic influence in the Indo-Pacific.33 This strategy of denial seeks to contain China through militarisation, alliance coordination, and defence modernisation. Washington is building a provocative military architecture in the region through a network of initiatives and partnerships. Across East Asia and the Indo-Pacific, the implications of intensifying militarisation are profound. Japan, South Korea, the Philippines, Taiwan, Australia, and India either host significant military infrastructure or participate in military cooperation that could place them at the centre of a major confrontation. For many societies in the region, the prospect of heightened militarisation raises concerns about opportunity costs as resources directed toward defence spending compete with investments in social welfare, infrastructure, climate resilience, and economic development. Foreign policy analysts and progressive policymakers in the region have proposed several reforms for peace and de-escalation. These include confidence-building measures in flashpoint areas such as the Taiwan Strait, renewed arms-control initiatives, and multilateral mechanisms for managing maritime disputes in the South China Sea. Regional organisations, particularly ASEAN, are often cited as potential platforms for dialogue and conflict management. While these proposals are welcome, any transformation must inevitably come from the organised people of the region themselves. Diverse social movements across the region continue to advocate for diplomacy, regional cooperation, and demilitarisation. In Okinawa, organisations such as the Okinawa Environmental Justice Project and No More Battle of Okinawa protest the expansion of US bases. In the Philippines, organisations such as Bagong Alyansang Makabayan (Bayan) oppose expanded military access agreements and call for greater national sovereignty. In South Korea, political parties and social movements, such as the People’s International Action Denouncing Trump, support renewed diplomatic engagement to reduce tensions on the Korean Peninsula. Similar debates occur in Taiwan, Australia, India, and other regions navigating US militarism. The International Peoples’ Assembly (IPA) – a network of around 200 social movements, political parties, and trade unions founded in 2015 – has worked closely with grassroots organisations in the region, building solidarity and consensus on key issues. At this crucial conjuncture, when militarisation threatens peace and development in Asia and indeed the entire world, the IPA has launched the Hands-Off Asia campaign. That campaign is centred around four demands to de-escalate from this New Cold War in Asia: Remove all foreign military bases and democratise security. The hundreds of foreign military bases that litter the Asian region should be removed so that regional policy can be democratised and peace can be more than just preparation for the next war. States should avoid forming rigid military blocs, limit forward deployments, and commit to preventing an arms race. Military policy should be accountable to the public – there should be parliamentary, local government, and civil society oversight over military agreements, defence budgets, and foreign troop deployments. Increase people-to-people contact. Support cooperation among labour unions, student groups, peace organisations, and social movements across Asia to oppose arms races, foreign bases, and escalating confrontation. Encourage people-to-people exchanges, cultural ties, and grassroots diplomacy across borders – especially between societies in conflict or under heightened tension – to build a shared regional culture of peace. Institutionalise sustained dialogue. Establish regular, high-level political and military-to-military communication channels to manage crises, reduce miscalculation, and build trust. Promote practical confidence-building mechanisms such as hotlines and incident-prevention agreements. Prioritise cooperative security and shared challenges. Shift focus from zero-sum competition to collaboration on key issues such as climate change, public health, economic stability, and development, reinforcing interdependence as a foundation for peace. Campaign for reductions in military spending and the reallocation of resources toward healthcare, climate action, education, and the reduction of inequality by linking peace to social justice. Underlying these struggles is a broader structural shift in the global economy. China’s growth as the major industrial power has reshaped global production networks and altered the distribution of economic influence. These changes have given a new impulse to sovereign-seeking movements across the Global South. Whether this transition leads to stable and peaceful multilateralism or intensified competition remains uncertain. Much depends on whether the class struggle can be advanced so as to push the agenda towards peace and development rather than war and austerity. <img loading="lazy" decoding="async" class="alignnone size-full wp-image-144933 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/D101_Kinjo_3.jpg" alt="" width="505" height="780" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/D101_Kinjo_3.jpg 505w, https://thetricontinental.org/wp-content/uploads/2026/05/D101_Kinjo_3-194x300.jpg 194w" sizes="auto, (max-width: 505px) 100vw, 505px"> Notes 1Though Okinawa makes up just 0.6% of Japan’s landmass, it hosts roughly 70% of all US military facilities in the country. Read more about Kinjo and Okinawa’s history in our twenty-sixth art bulletin (April 2026), ‘You Cannot Swallow a Needle, However Small: Okinawa’s Sculptor of Resistance’, https://thetricontinental.org/art-bulletin-okinawas-sculptor-of-resistance/. 2 Tricontinental: Institute for Social Research, The 80th Anniversary of the Victory in the World Anti-Fascist War, Understanding Who Saved Humanity: A Restorationist History, Contemporary Dilemmas no. 5, 12 November 2025, https://thetricontinental.org/the-80th-anniversary-of-the-victory-in-the-world-anti-fascist-war/. 3 Linda Glawe and Helmut Wagner, The Economic Rise of East Asia. Development Paths of Japan, South Korea, and China (Cham: Springer, 2021); and Asian Development Bank, Asian Economic Integration Report 2025: Harnessing the Benefits of Regional Cooperation and Integration (Asian Development Bank, 2025). 4 Chalmers Johnson, MITI and the Japanese Miracle: The Growth of Industrial Policy, 1925–1975 (Stanford University Press, 1982); and Masahiko Aoki, Hikaku Seido Bunseki ni Mukete (Toyo Keizai Shinposa, 1995). 5 Asian Economic Integration Reports, Asian Development Bank, https://www.adb.org/publications/series/asian-economic-integration-report. 6 Lin Yifu, Jiedu Zhongguo Jingji [Demystifying the Chinese Economy] (Beijing Daxue Chubanshe, 2012). 7 This data is available at the UN Comtrade Database website, https://comtradeplus.un.org/. 8 Cheng Yawen, ‘Building the New “Three Rings”: Reconfiguring China’s Foreign Relations in the Face of Decoupling’, Wenhua Zongheng, vol. 1, no. 1, March 2023, https://thetricontinental.org/wenhua-zongheng-1-building-the-new-three-rings/. 9 Honghong Tinn, Island Tinkerers: Innovation and Transformation in the Making of Taiwan’s Computing Industry (MIT Press, 2025); and Bappa Sinha, Breaking the Stranglehold: How China is Shattering US Technological Hegemony, Tricontinental Interventions: Conjunctural Analysis from Asia no. 10, 27 March 2026, https://thetricontinental.org/asia/breaking-the-stranglehold-how-china-is-shattering-us-technological-hegemony/. 10 Elbridge A. Colby, The Strategy of Denial: American Defense in an Age of Great Power Conflict (Yale University Press, 2021). 11 Clinton Fernandes, Sub-Imperial Power: Australia in the International Arena (Melbourne University Press, 2022); Andrew Fowler, Nuked: The Submarine Fiasco that Sank Australia’s Sovereignty (Melbourne University Press, 2024); Jeffrey Wagner and Dae-Han Song, ‘Trilateral missile defense system a step towards Asian NATO’, Peoples Dispatch, 29 November 2023, https://peoplesdispatch.org/2023/11/29/trilateral-missile-defense-system-a-step-towards-asian-nato/. 12 Zhao Minghao and Yang Hongjia, ‘Major Power Competition and New Trends in US Interference with the Taiwan Question’, Contemporary American Review, no. 1, 2024. 13 Council on Foreign Relations, ‘U.S. Military Support for Taiwan in Five Charts’, 5 October 2023, https://www.cfr.org/articles/us-military-support-taiwan-five-charts?utm. 14 On Sri Lanka’s role at the epicenter of the US Indo-Pacific strategy, see Shiran Illanperuma, Sri Lanka’s New Government, the Indo-Pacific Debt Trap, and the Struggle for the 21st Century, Tricontinental Interventions: Conjunctural Analysis from Asia no. 4, 30 December 2024, https://thetricontinental.org/asia/ticaa4-sri-lanka-s-new-government-the-indo-pacific-debt-trap/. On Diego Garcia, see Philippe Sands, The Last Colony: A Tale of Exile, Justice, and Britain’s Colonial Legacy (W&N, 2022). 15 Vijay Prashad, John Bellamy Foster, John Ross, and Deborah Veneziale, Washington’s New Cold War: A Socialist Perspective (Monthly Review Press, 2022). 16 Richard Javad Heydarian, ‘Philippines becoming a military hub for checking China’, Asia Times, 16 November 2023. 17 We are following the narrative laid out by Gavan McCormack in Client State: Japan in the American Embrace (Verso, 2007). 18 Stockholm International Peace Research Institute, ‘Unprecedented Rise in Global Military Expenditure as European and Middle East Spending Surges’, 28 April 2025, https://www.sipri.org/media/press-release/2025/unprecedented-rise-global-military-expenditure-european-and-middle-east-spending-surges. 19 Jon Mitchell, Why Are We in Okinawa? A History of Violence (Bloomsbury, 2026). 20 Gavan McCormack and Satoko Oka Norimatsu, Resistant Islands: Okinawa Confronts Japan and the United States (Bloomsbury, 2018). 21 World Bank, ‘Military expenditure (% of GDP) – Korea, Rep.’, based on SIPRI Military Expenditure Database, https://data.worldbank.org/indicator/MS.MIL.XPND.GD.ZS?locations=KR. 22 Dae-Han Song, ‘Power Concedes Nothing Without a Demand: Peace in Korea and Northeast Asia Now!’, Monthly Review 76, no. 3, July-August 2024, https://monthlyreview.org/articles/power-concedes-nothing-without-a-demand-peace-in-korea-and-northeast-asia-now/. 23 Dae-Han Song, ‘US Recruits South Korea to Help Colonise and Militarise Space’, Peoples Dispatch, 13 November 2024, https://peoplesdispatch.org/2024/11/13/us-recruits-south-korea-to-help-colonize-and-militarize-space/. 24 ‘Remarks by Under Secretary of War for Policy Elbridge Colby at the Sejong Institute in South Korea (As Delivered)’, US Department of War, 26 January 2026, https://www.war.gov/News/Speeches/Speech/Article/4389207/remarks-by-under-secretary-of-war-for-policy-elbridge-colby-at-the-sejong-insti/. 25 Chad de Guzman, ‘US and Philippines Announce New Sites for Military Cooperation: What to Know’, Time, 4 April 2023, https://time.com/6268379/philippines-us-military-bases-china/. 26 No Cold War, Taiwan Is a Red Line Issue, briefing no. 6, 9 February 2023, https://nocoldwar.org/news/briefing-taiwan-is-a-red-line-issue; and No Cold War, ‘Stop US Interference: Interview with the Labor Party of Taiwan’, Wim De Ceukelaire interviews Wu Rong-yuan (Chairperson, Labor Party of Taiwan), 2 January 2023, https://news.nocoldwar.org/stop-us-interference-interview-with-the-labour-party-of-taiwan/. 27 National Chengchi University Election Study Center, ‘Changes in the Taiwanese/Chinese Identity of Taiwanese (1992–2025)’, December 2025, https://esc.nccu.edu.tw/upload/44/doc/6963/Tondu202512.png. 28 The suggestion for this ‘scorched earth’ strategy was first put forward in Jared McKinney and Peter Harris, ‘Broken Nest: Deterring China from Invading Taiwan’, Parameters: The US Army War College Quarterly, vol. 51, no. 4, 2021, and then resurrected by former US national security advisor Robert O’Brien two years later. Steve Clemons, ‘The US would destroy Taiwan’s chip plants if China invades, says former Trump official’, Semafor, 13 March 2023, https://www.semafor.com/article/03/13/2023/the-us-would-destroy-taiwans-chip-plants-if-china-invades-says-former-trump-official. 29 In February 2025, Australia paid $500 million and, in July, an additional $525 million. See Dzirhan Mahadzir, ‘SECDEF: White House Supportive of AUKUS, Australia Makes $500M Payment’, USNI News, 10 February 2025, https://news.usni.org/2025/02/10/secdef-white-house-supportive-of-aukus-australia-makes-500m-payment; and Reuters, ‘Australia’s US$525 Million Aukus Payment Proceeds amid Trump Review of Submarine Pact’, South China Morning Post, 23 July 2025, https://www.scmp.com/news/asia/australasia/article/3319283/australias-us525-million-aukus-payment-proceeds-amid-trump-review-submarine-pact. 30 Ben Doherty, ‘US Congressional Report Explores Option of Not Delivering Any Aukus Nuclear Submarines to Australia’, The Guardian, 4 February 2026, https://www.theguardian.com/world/2026/feb/05/not-delivering-any-aukus-nuclear-submarines-to-australia-explored-as-option-in-us-congressional-report. 31 Vijay Prashad, India’s Iran Policy: Between US Primacy and Regionalism, working paper no. 19, Issam Fares Institute for Public Policy and International Affairs (American University of Beirut), November 2013; Prakash Karat, Subordinate Ally: The Nuclear Deal and India-US Strategic Relations (New Delhi: LeftWord Books, 2007); and M.K. Bhadrakumar, Ninan Koshy, and Prabir Purkayastha, Uncle Sam’s Nuclear Cabin (LeftWord Books, 2007). 32 Bodapati Srujana, ‘India’s Reckoning with Trump’s Tariffs’, Tricontinental Asia Newsletter, 8 August 2025, https://thetricontinental.org/asia/indias-reckoning-with-trumps-tariffs/; and Tricontinental: Institute for Social Research, The Turbulence of the Indian Economy, dossier no. 96, January 2026, https://thetricontinental.org/dossier-india-deindustrialisation/. 33 Tricontinental: Institute for Social Research, Hyper-Imperialism: A Dangerous Decadent New Stage, Contemporary Dilemmas no. 4, 23 January 2024, https://thetricontinental.org/studies-on-contemporary-dilemmas-4-hyper-imperialism/.
A Revolution Can Only Be the Child of Culture and Ideas
Caught between US military dependence and deep economic integration with China, Japan, South Korea, the Philippines, and Taiwan face mounting contradictions as the New Cold War reshapes East Asia.
The Twenty-Seventh Art Bulletin (May 2026) <img loading="lazy" decoding="async" class="alignnone size-full wp-image-144984 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/AB27_Header-1.jpg" alt="" width="950" height="550" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/AB27_Header-1.jpg 950w, https://thetricontinental.org/wp-content/uploads/2026/05/AB27_Header-1-300x174.jpg 300w, https://thetricontinental.org/wp-content/uploads/2026/05/AB27_Header-1-768x445.jpg 768w" sizes="auto, (max-width: 950px) 100vw, 950px"> Listen to ‘Por Qué Cantamos / Canción Nueva’ (Why Do We Sing / New Song), from A Dos Voces (In Two Voices), a collaboration between Mario Benedetti and Daniel Viglietti that pairs Benedetti’s reading of ‘Por qué cantamos’ with Viglietti’s song ‘Canción Nueva’. In Latin America, the paths of people’s struggles and the development of their cultures have always been intertwined. From Spanish and Portuguese colonisation in the fifteenth and sixteenth centuries to the independence struggles of the nineteenth century and the Monroe Doctrine of 1823, the peoples of Latin America have resisted successive forms of domination. José Martí, one of the leading figures in Cuba’s struggle for independence, gave this resistance one of its most powerful expressions in Nuestra América (Our America), his 1891 essay on the political and cultural unity of the continent. For Martí, Nuestra América named not only a geography – the vast territory stretching ‘from the Rio Grande to the Strait of Magellan’ – but a civilisational project rooted in the histories, cultures, and struggles of the continent’s peoples. This was the anti-imperialist force of Martí’s reflection: Latin America could only free itself by knowing itself, by recognising the Indigenous, African, peasant, and popular roots that colonialism and sections of the intelligentsia had treated with contempt. As Martí wrote in Nuestra América: ‘Solving a problem in full knowledge of its elements is easier than solving it without knowing them. … To know is to solve. To know the country and govern it in accordance with that knowledge is the only way to free it from tyranny’. Throughout its history, Latin American literature has been one of the principal means through which that self-knowledge has been produced. Through poetry, novels, essays, and song, the continent’s peoples have represented their realities not as abstractions but through lived experience. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-144815" class="size-full wp-image-144815 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/01_writers-on-the-truck.jpeg" alt="" width="994" height="426" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/01_writers-on-the-truck.jpeg 994w, https://thetricontinental.org/wp-content/uploads/2026/05/01_writers-on-the-truck-300x129.jpeg 300w, https://thetricontinental.org/wp-content/uploads/2026/05/01_writers-on-the-truck-768x329.jpeg 768w" sizes="auto, (max-width: 994px) 100vw, 994px"> Writers travelling by truck to Minas de Frío, Cuba, n.d. Source: Revista Casa de las Américas. The second half of the twentieth century in Latin America was marked by profound political and social transformations. The Cuban Revolution of 1959 ruptured the island’s subordination to the United States and opened a process of socialist transformation that sought to remake economic, political, and cultural life, offering hope to peoples in struggle across the region. In response, the United States intensified its imperialist offensive: in Nuestra América, it backed the failed Bay of Pigs invasion of Cuba in 1961, supported the military coup in Brazil in 1964, worked to destabilise Salvador Allende’s government in Chile before the 1973 coup, and backed dictatorships and bloody counter-insurgency projects across the continent during the 1970s. In this context, literature continued to play an important role in resistance, particularly during the Latin American literary boom of the 1960s and 1970s, when several writers gained international prominence. This period renewed longstanding debates on the relationship between art and politics, with Cuba – its revolution and cultural policy – at the centre of the discussion. In the first year of the revolution, the revolutionary government created numerous cultural institutions, including the National Theatre, the Cuban Institute of Cinematographic Art and Industry (ICAIC), and Casa de las Américas. Directed by Haydée Santamaría, Casa de las Américas became an indispensable reference point for thinking about culture, art, and literature in Latin America. The Uruguayan writer Mario Benedetti (1920–2009) played a key role in deepening Casa’s political and cultural work, helping to establish literature as a terrain of resistance across Latin America. His own literary and political development, like that of many Latin American writers in the second half of the twentieth century, was also closely linked to Casa de las Américas. Its journal, Revista Casa de las Américas, first published in 1960, played a central role in circulating and developing an emancipatory perspective on Latin American and Caribbean culture, contributing to the construction of a new society. Alongside the creation of these institutions, Fidel Castro’s 1961 speech ‘Palabras a los intelectuales’ (Words to the Intellectuals) outlined the foundations of the revolution’s cultural policy. Initiatives such as the Conrado Benítez brigades, which were central to Cuba’s literacy campaign, and the free distribution of millions of copies of classical literature, formed part of this wider effort to make culture a right of the people. Notably, the first book published and distributed by the revolution was Miguel de Cervantes’ Don Quixote. However, the United States’ imperialist offensive against Cuba also extended into the cultural sphere. Seeking to counter Casa de las Américas’ growing influence, the CIA-funded Congress for Cultural Freedom launched the magazine Mundo Nuevo in Paris in 1966. Directed by the Uruguayan critic Emir Rodríguez Monegal, Mundo Nuevo presented itself as an independent literary journal while working to draw writers of the Latin American boom away from Cuba’s revolutionary cultural project and into the orbit of liberal anti-communism. As revolution and counter-revolution clashed across the continent, writers took different positions on both the construction of socialism in Cuba and the cultural offensive waged by the United States during the Cold War. Prominent authors of the Latin American boom – such as Julio Cortázar, Mario Vargas Llosa, Gabriel García Márquez, and Carlos Fuentes – entered this debate in distinct and sometimes contradictory ways, revealing that literature and art could not be separated from the wider political struggles of the period. It is in this context that Benedetti’s formulation on the role of the writer in the class struggle is especially important. In a 1968 interview with Cuba magazine, following the Cultural Congress of Havana, Benedetti argued: If the duty of every revolutionary is to make the revolution, the duty of every writer, as such, is to make literature … literature, among other functions, expands the horizons of human beings. To the extent that the people can grasp the meanings – whether ultimate or intermediate – of great works of fiction, they come closer to our struggle, and even more so if they are capable of analysing the alienation imposed upon them by the enemy. For this reason, we see no need to impose on militant writers a narrow thematic or generic line. Thus, the potential of literature goes beyond the political position of the writer, although in moments of increased imperialist aggression, taking such positions remains crucial in strengthening or weakening political processes. Benedetti’s point was that the revolutionary force of literature cannot be reduced to a prescribed theme, genre, or slogan. Literature can widen the horizons of the people, sharpen their capacity to recognise alienation, and bring them closer to struggle precisely through its formal, imaginative, and emotional power. Culture Is Not a Luxury but a Right <img loading="lazy" decoding="async" class="alignnone size-full wp-image-144831 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/03_Mario-Benedetti_950x950.jpg" alt="" width="950" height="950" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/03_Mario-Benedetti_950x950.jpg 950w, https://thetricontinental.org/wp-content/uploads/2026/05/03_Mario-Benedetti_950x950-300x300.jpg 300w, https://thetricontinental.org/wp-content/uploads/2026/05/03_Mario-Benedetti_950x950-150x150.jpg 150w, https://thetricontinental.org/wp-content/uploads/2026/05/03_Mario-Benedetti_950x950-768x768.jpg 768w" sizes="auto, (max-width: 950px) 100vw, 950px"> Mario Benedetti was one of the most important Latin American writers of the twentieth century. Across poetry, novels, short stories, and essays, the Uruguayan author developed a direct and profoundly human style that captured the social and emotional complexities of Uruguay and of Latin America more broadly. Beyond his literary importance, Benedetti played a central role in the cultural and political life of the Latin American left. His involvement with Casa de las Américas – first as a juror for its literary prize and later as founder and director of the Centre for Literary Research – contributed to the development of a Latin American literary culture that, while recognising European literary traditions, emphasised the political, aesthetic, and cultural significance of Nuestra América. This experience deepened his reflection on literary practice in dialogue with Latin American readers and revolutionary processes, without reducing literature to rigid formulas or dogmas. His reflections on the role of intellectuals and cultural workers in revolutionary processes remain particularly significant. At the 1968 Cultural Congress of Havana, Benedetti addressed the tensions between intellectuals and activists. At a time when armed struggle was a principal form of political struggle, intellectuals and artists were often called to join the front lines. For Benedetti, intellectual activity was itself a necessary part of revolutionary development. The intellectual, he argued, is ‘almost by definition [a] nonconformist, a critic of their social environment, a witness with an implacable memory’. He also insisted that culture is not a luxury but a right: ‘The artist who defends their right to dream, to create beauty, to create imagination, with the same determination and conviction with which they defend their right to eat, to have a roof, and to care for their health – that artist will be the only one capable of demonstrating that their work is not a luxury but a necessity, not only for themselves but also for others’. For Benedetti, then, revolutionary culture could not be treated as secondary to political struggle. Art, literature, and imagination were part of what made it possible for people to interpret their conditions, defend their dignity, and struggle for a new society. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-144823" class="size-full wp-image-144823 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/02_mario_benedetti_jurado_premio_casa_americas_haydee_santamaria_alejo_carpentir_1978_s.jpg" alt="" width="300" height="445" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/02_mario_benedetti_jurado_premio_casa_americas_haydee_santamaria_alejo_carpentir_1978_s.jpg 300w, https://thetricontinental.org/wp-content/uploads/2026/05/02_mario_benedetti_jurado_premio_casa_americas_haydee_santamaria_alejo_carpentir_1978_s-202x300.jpg 202w" sizes="auto, (max-width: 300px) 100vw, 300px"> Benedetti on the jury of the Casa de las Américas Award, with Haydée Santamaría and Alejo Carpentier, 1978. Source: Fundación Mario Benedetti. Poetry constitutes the largest part of Benedetti’s work. Across his work, he explored a wide range of forms, including the haiku later in life, using them to illuminate the richness of ordinary experience. His poetry, like much of his writing, is marked above all by an ethic of proximity and solidarity, as seen in one of his haiku: la más cercana de todas las fronteras es con mi prójimo the closest of all borders is with my neighbour His prose also became a defining part of his literary contribution. Across more than nine collections, he addressed themes such as memory, life under dictatorship in Uruguay, love, and the intimate textures of daily existence, giving political density to seemingly intimate experiences. Short story collections such as Montevideanos (Montevideans), Geografías (Geographies), and Buzón de tiempo (Mailbox of Time), alongside the novel Primavera con una esquina rota (Springtime in a Broken Mirror), show how the affective and the political are inseparable in his writing. Benedetti’s life and work reflect a militant engagement with culture and art as fundamental dimensions of revolutionary construction. His poetry and prose are both subtle and profound, bringing to light the contradictions of building a new human being in a new society. Why Do We Sing? The dynamics of class struggle in the twenty-first century remain intense. The declining US empire has intensified its offensive against the territories and peoples of the Global South, from Palestine to Venezuela to Cuba, and those peoples continue to resist. The ‘battle of ideas and emotions’, as Fidel described it, has become increasingly central in our time. Mario Benedetti’s legacy – both as a writer and a militant – is essential for understanding how intellectuals can act not only as cultural workers but also as organisers within revolutionary processes. Casa de las Américas continues to be one of the most important cultural institutions in Nuestra América, promoting artistic production rooted in the experiences of our peoples and keeping alive the conviction that culture is not separate from political struggle but one of its necessary forms. At a time when the United States intensifies its attempts to suffocate Cuba through blockade, sanctions, and isolation, solidarity from people’s organisations is essential to keeping the flame of the Cuban Revolution alive so that present and future generations may continue the struggle. As Benedetti’s poem asks, ‘Why do we sing?’: Cantamos porque llueve sobre el surco Y somos militantes de la vida Y porque no podemos ni queremos Dejar que la canción se haga ceniza We sing because rain falls on the furrow and we are militants of life and because we cannot and do not want to let the song turn to ash Warmly, Miguel Yoshida Member of the Art and Culture Department and the Nuestra América office at Tricontinental: Institute for Social Research; editor at Expressão Popular, Brazil.
The Security Mirage: A Territory in Dispute
While imperialist offensives weaponise culture to neutralise resistance, a radical truth remains: art, literature, and imagination are never separate from political struggle, but a necessary form of collective defiance in building a new society.
<img loading="lazy" decoding="async" aria-describedby="caption-attachment-144545" class="size-full wp-image-144545 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/Sidney-Amaral-Brasil-Mae-Preta-ou-A-Furia-de-Iansa-2014.png" alt="" width="970" height="681" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/Sidney-Amaral-Brasil-Mae-Preta-ou-A-Furia-de-Iansa-2014.png 970w, https://thetricontinental.org/wp-content/uploads/2026/05/Sidney-Amaral-Brasil-Mae-Preta-ou-A-Furia-de-Iansa-2014-300x211.png 300w, https://thetricontinental.org/wp-content/uploads/2026/05/Sidney-Amaral-Brasil-Mae-Preta-ou-A-Furia-de-Iansa-2014-768x539.png 768w" sizes="auto, (max-width: 970px) 100vw, 970px"> Sidney Amaral (Brazil), Mãe Preta ou A Fúria de Iansã [Black Mother or the Fury of Iansa], 2014. Dear friends, Greetings from the Nuestra América Office of Tricontinental: Institute for Social Research. There is a long, silent, and profitable war being waged in Nuestra América: the war on the poor. Although uniforms, doctrines, or slogans change—ranging from ‘pacification’ to ‘iron fist’ (mano dura) or ‘zero tolerance’—whether under the shield of the ‘war on drugs’ or the ‘war on crime’, the war produced by the inequality of the prevailing economic order is fought to simultaneously criminalise poverty and terrorise the population. The ‘Angry Tide’ that has recently swept over the governments of Latin America has made combating the region’s perceived security crisis one of its central targets. In its strategy to discredit Latin American progressivism, the new right presents leftist forces as inefficient and incapable—even as accomplices—of criminality. Frequently, political debates use polls that reveal crime as one of the main concerns of the electorate in the region and even point out that, for this reason, the population has been favoring governments that promise a harsh and inclement iron fist against delinquency. It is not surprising, in this sense, that even though they are the most affected by policies criminalising poverty, people speak out in favour of fighting crime. According to the AtlasIntel survey, for example, 62 percent of Rio de Janeiro residents supported a police operation that left 121 victims last October. From Kast to Keiko Fujimori, right-wing campaigns have highlighted the fight against crime among their priorities. Uruguayan President Yamandú Orsi himself noted in an interview that 50 percent of Frente Amplio voters also sympathise with Salvadoran President Nayib Bukele. “The right took the banner of security, which is a human right, and monopolised it for a long time,” he added. Currently, the vast media apparatus presents the so-called ‘Bukele model’ to us as the most effective formula to combat insecurity and organised crime. However, an in-depth analysis leads us to ask: whom does the order he seeks to impose serve, and upon whose bodies is it built? Bukele has built a system through policies of State dismantlement and social precariousness, shielded by the indefinite extension of a state of exception. Today, El Salvador holds the world’s highest incarceration rate, 1,650 people per 100,000 inhabitants. Childhood is criminalised through lowering the age at which children can be tried as adults, collective trials and mass incarcerations are common, and political dissent is persecuted, as in the case of human rights defender Fidel Zavala. Among the figures that Bukele hides, however, is the increase in poverty to 9.6% or the 10,000 students who have dropped out of school. This demonstrates that both the existing insecurity and this mirage of order and security end up hitting hardest those who live on the periphery—who, nevertheless, have directed their votes toward tangible solutions rather than more conciliatory and sociological discourses of the regional left. According to the CB Consultora poll from April 2026, Bukele leads regional popularity with a 70.1% positive approval rating, while Lula da Silva hovers around 48.4% support with 49.1% disapproval, and Gustavo Petro barely reaches a 38.2% approval rating. Lula himself has been forced in his campaign to present a plan against organised crime, promising maximum security standards in his prisons. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-144561" class="size-full wp-image-144561 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/Rosa-Mena-Valenzuela-El-Salvador-Calles-1983.-Coleccion-MARTE-1.webp" alt="" width="1500" height="1236" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/Rosa-Mena-Valenzuela-El-Salvador-Calles-1983.-Coleccion-MARTE-1.webp 1500w, https://thetricontinental.org/wp-content/uploads/2026/05/Rosa-Mena-Valenzuela-El-Salvador-Calles-1983.-Coleccion-MARTE-1-300x247.webp 300w, https://thetricontinental.org/wp-content/uploads/2026/05/Rosa-Mena-Valenzuela-El-Salvador-Calles-1983.-Coleccion-MARTE-1-1024x844.webp 1024w, https://thetricontinental.org/wp-content/uploads/2026/05/Rosa-Mena-Valenzuela-El-Salvador-Calles-1983.-Coleccion-MARTE-1-768x633.webp 768w" sizes="auto, (max-width: 1500px) 100vw, 1500px"> Rosa Mena Valenzuela (El Salvador), Calles [Streets], 1983. MARTE Collection. This ‘pop authoritarianism’ that cultivates fear, hides behind its repression and propaganda its inability to resolve the structural inequality that leads to poverty and, at times, crime itself. It sells itself as a model against which there is no alternative, and the generation of leaders of the Angry Tide, who seek to restore colonial dominance over the entire region, obediently join the so-called Shield of the Americas, led by the United States as a solution to criminality. But it turns out there are alternatives. Recently, political scientist Viri Ríos of Mexico Decoded noted that the progressive government of Claudia Sheinbaum has indeed been building a different proposal. In just 18 months, the daily homicide rate has fallen by 41 percent, even though its population is 20 times larger than that of El Salvador and Mexico’s security challenges go beyond gangs and criminal organizations to include large-scale transnational organised crime and drug cartels. Without implementing a state of exception, the Mexican prison population has risen by 11 percent after changing its security policy. The key, Ríos underlines, is that the strategy does not shy away from directly confronting the sources of crime, equally abandoning the decapitation of cartels—which in previous six-year terms triggered violence exponentially—and the low-confrontation approach that predominated between 2018 and 2024. Mexican policy directly attacks the material causes of delinquency: it seeks, first of all, to halt the sources of crime financing by attacking problems at a national level according to territorial realities: fighting fuel theft in oil-producing areas, supervising customs points in border regions, attacking extortion in the countryside, among others. Ríos acknowledges that structural problems such as corruption persist in Mexico, but notes that despite its limitations, Mexico is managing to reduce criminality based on a policy that does not resort to Bukele’s unchecked violence. Another experience from the left that is worth studying is that of the Great Peace Quadrants Mission (Gran Misión Cuadrantes de Paz) in Venezuela. Here, another decisive conceptual key is provided: the territorialization of security under a preventive logic and joint work between the community and police forces, instead of a prison-centric logic. According to official figures, the homicide rate dropped from 56 per 100,000 inhabitants in 2016 to nearly 4 in 2024. By the end of 2025, authorities reported a reduction of more than 25 percent in murders compared to the previous year. What the Peace Quadrants model proposes is that a security policy built through organised community participation, working-class neighborhoods, and not against them, as in the Bukele model, can yield effective results. It can serve as a guide for the left, since anchoring security to the construction of people’s power in the territory is more effective than punishment. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-144553" class="size-full wp-image-144553 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/Vlady-Mexico-Mecanismo-Carcelario-1958-1959.avif" alt="" width="1480" height="840" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/Vlady-Mexico-Mecanismo-Carcelario-1958-1959.avif 1480w, https://thetricontinental.org/wp-content/uploads/2026/05/Vlady-Mexico-Mecanismo-Carcelario-1958-1959-300x170.avif 300w, https://thetricontinental.org/wp-content/uploads/2026/05/Vlady-Mexico-Mecanismo-Carcelario-1958-1959-1024x581.avif 1024w, https://thetricontinental.org/wp-content/uploads/2026/05/Vlady-Mexico-Mecanismo-Carcelario-1958-1959-768x436.avif 768w" sizes="auto, (max-width: 1480px) 100vw, 1480px"> Vlady (Mexico), Mecanismo Carcelario [Prison Mechanism], (1958-1959). Popular forces that want to dispute the electoral field in the coming years must study these solutions thoroughly and also build their own proposals. First, the issue of security cannot be ignored because it is not a whim of the elite; it is a real concern of the working population, even if at times the construction of ultraconservative narratives seeks to terrorise the population by magnifying the conditions of criminality in our countries. Security must also be assumed as a right of the working population, and their double vulnerability must be recognized: being attacked both by crime and by reactionary policies of repression. Secondly, we must ask ourselves what concrete institutional framework a popular government must build and finance to attack crime—greater professionalization of investigative and security forces? A direct attack on the sources of crime financing and the intermediate ranks that operate it? The construction of a work agenda between communities and authorities in the territory, based on respect and collaboration rather than persecution? Thirdly, it must be demonstrated that repression and terror, in the long term, exacerbate exclusion and foster criminal practices. Repression is costly, and it is often outsourced to mercenary or, worse yet, foreign forces, which in the long term places national sovereignty at risk. Addressing security without mirages is fundamental for the healthy development of a society. The popular camp cannot ignore this challenge, nor minimise it. But it must, above all, convince the population that it does have a viable alternative that implies neither the dismantling of the State nor deadly repression; an alternative that, on the contrary, invites the working class to be part of its own security strategy. The debate is open. We would like to hear your opinions. Affectionately, Carmen Navas Reyes and Carlos Ron Tricontinental Nuestra América Carmen Navas Reyes is a researcher at the Tricontinental Institute for Social Research. She is a Venezuelan feminist and former diplomat. Her research interests include democracy and political systems, social movements, the history of the African diaspora, and Afro-descendance. Carlos Ron is co-coordinator of the Nuestra América office at the Tricontinental Institute for Social Research. He is a Venezuelan former diplomat who served as Vice Minister for North America (2018–2025) and President of the Simón Bolívar Institute for Peace and Solidarity Among Peoples (2020–2025).
How to Analyse and Critique Research with AI
Addressing security without mirages is fundamental for the healthy development of a society. The popular camp cannot ignore this challenge.
<img loading="lazy" decoding="async" class="aligncenter size-full wp-image-144435 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI_1000667.jpg" alt="" width="1000" height="667" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI_1000667.jpg 1000w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI_1000667-300x200.jpg 300w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI_1000667-768x512.jpg 768w" sizes="auto, (max-width: 1000px) 100vw, 1000px"> AI can now rapidly generate large volumes of ‘paper analyses,’ but much of this content is merely fluent text with an academic tone. They look like critical studies, yet they lack clear sources of evidence, analytical pathways, and verifiable bases for judgement. Genuine critical evaluation is not impromptu commentary or emotional negation, but a structured process. It requires the researcher to clarify the analytical objectives, fix the evaluation criteria, and ensure that every judgement can be traced back to the source text. The focus of this article is not on making AI ‘better at critiquing,’ but on how to establish a set of critical analysis methods that are traceable, verifiable, and reusable over the long term. Why AI Tends to Produce ‘Pseudo-Critique’ AI’s biggest problem is not that it cannot analyse, but that it is all too easy for it to ‘look like it is analysing.’ Without structural constraints, the model will automatically complete the logic, amplify vague cues, and generate a large number of standardised judgements such as ‘the research has limitations,’ and ‘the argument is insufficiently developed.’ But the real question is: do these conclusions actually come from the source text? Can they be located in specific paragraphs, evidence, or argumentative structures? If they cannot be verified against the original text, then the so-called ‘critical analysis’ is often merely speculation cloaked in an academic tone, rather than a genuinely reliable research evaluation. How to Use AI for Critical Evaluation Truly valuable academic critique is never an impromptu expression, but a rigorous analytical pipeline. It requires the researcher, before initiating any analysis, to first clarify the analyst’s identity and boundary of responsibility, then fix the analytical objectives, analytical stance, and output format, and then proceed step by step along a traceable path, so that every judgement can eventually be returned to the source text. 1. Role Definition Many people habitually enter a vague instruction into the model, such as ‘please critically analyse this paper.’ But the consequence is that the model does not know whether it should become a summariser, a commentator, or a genuine critical analyst. What the role setting determines is not the language style, but how the model understands the boundaries of its responsibilities. A model clearly defined as a ‘critical analyst’ will proactively seek out vulnerabilities in the argument, logical gaps, and evidential weaknesses. Therefore, the starting point of a critical evaluation must be to make the model clearly aware of who it is, what it is to do, and what professional standards it must follow. For example: ## Your Role You are an expert **critical analyst** tasked with conducting a rigorous, constructive critical analysis of argumentative texts. Your analysis must be faithful to the source text, focus on logical structure, evidence, and argumentative resilience, and avoid injecting unsupported opinions. The ultimate goal is to help strengthen the work by identifying areas for improvement. 2. Objectives and Audience After defining the role, it is necessary to establish the specific objectives and context for the analysis work. If the requirement is only a vague ‘critique,’ the model is highly likely to slide between abstract, evaluation, and templated limitations, producing content that cannot be verified. Therefore, it is essential to lock in advance the purpose of the analysis, the identity of the intended reader, and the tone of the entire report. The goal of the analysis is not simply to point out errors, but to conduct a ‘stress test;’ the audience may be the author, editor, or peer reviewer; the tone should be scholarly, precise, and fundamentally constructive. Once these dimensions are fixed, the entire subsequent analysis process has a unified direction. ## Objectives and Output Goals ### Primary Objective Describe the purpose of the critical analysis, such as performing a stress test on the text's arguments, identifying weaknesses, and suggesting actionable improvements. ### Target Audience Describe who the analysis is intended for (e.g., author, editor, peer reviewer) and what level of detail and rigour is expected. ### Required Tone Describe the analytical tone: critically rigorous yet constructive, scholarly, precise, and clearly anchored in the source text. 3. Using a Reference & Navigation Section In long prompts, models may lose track of where key instructions and source materials are located. They may skip intermediate sections, introduce external assumptions, or fail to follow the intended analytical scope. Therefore, the prompt should begin with a clear navigation declaration that explicitly tells the model where the analytical rules and source text are located This section functions as a structural “table of contents” and routing guide for the model, helping maintain instruction adherence across long-context processing. ## Methodological Reference and Input This prompt is self-contained for its critical analysis task. All analytical criteria are provided within the **Detailed Critical Analysis Protocol** section. Load the primary text to be analysed from the **Input** section at the end of this prompt. Do not consult any external references. 4. Execution Protocol Next, the execution process of the critical analysis needs to be broken down into a set of rigorous requirements, forming the core operating system of the entire prompt. This part begins with a clear task statement, establishing an action framework for the model so that it can identify, examine, and measure each argument through repeatable steps. The analysis protocol can usually contain three levels: First, require the model to locate the core arguments and vulnerable claims from the text. Second, stipulate for each argument the assessment lenses that must be applied, such as logical structure, evidential foundation, rhetorical clarity, and argumentative resilience. Finally, clarify the analytical mindset: maintain a ruthlessly critical stance while always aiming to be constructive, and apply the ‘most damaging plausible interpretation’ to ambiguous statements to test argumentative strength. You can customise the types and depth of the assessment lenses according to your own research needs. ## Detailed Critical Analysis Protocol ### Argument Identification Identify up to [number] central arguments and any particularly vulnerable claims in the provided text. ### Assessment Criteria For each argument, systematically examine it through the following lenses: - **Logical Structure:** Identify fallacies, assess validity and soundness of reasoning. - **Evidentiary Foundation:** Evaluate the quality, relevance, and sufficiency of supporting evidence. - **Rhetorical Clarity:** Detect ambiguity, equivocation, or manipulative language. - **Argumentative Resilience:** Check for unaddressed counterarguments and internal consistency. ### Analytical Approach Maintain a ruthlessly critical yet constructive stance. Apply the 'most damaging plausible interpretation' to ambiguous claims in order to test robustness. For each analysed argument, provide: a concise summary, a detailed critical analysis linked to the criteria above, a vulnerability rating (1–10), and actionable suggestions for improvement. 5. Output Format The rigour of the analysis process must ultimately be solidified through the structure of the output. If the model only generates a prose-style commentary, tracing the basis for any particular judgement becomes extremely difficult. Therefore, the prompt needs to specify a clear output format. For example, require the output as a single Markdown document, providing for each analysed argument a summary, critical analysis, vulnerability rating, and improvement suggestions, and conclude with a comprehensive executive summary. At the same time, the language and academic style to be used can be stipulated here. ## Output Format 1. Produce the critical analysis as a **single, well-structured Markdown document**. 2. Begin with the title of the input document. 3. For each analysed argument, include: Argument Summary, Critical Analysis, Vulnerability Rating (1–10), and Improvement Path. 4. Conclude with an executive summary of the most critical overarching weaknesses. 5. All output must be presented in clear, precise academic English. 6. Input Content After everything is ready, the final step is to paste the complete paper, chapter, or notes into the input section at the end of the prompt. It is this action that activates all the preceding silent rules, making the text the sole factual source for every judgement the model makes. Therefore, the text you provide must be complete; do not omit any paragraphs, footnotes, or data that might conceal key arguments. ## Input `[Paste the FULL TEXT of the essay, academic article, or argumentative work to be critically analysed here.]` Worked example The sections above are not only a tutorial outline. they are a prompt template you can turn into a single file. When you are done, you have a full critical-analysis prompt, one self-contained instruction set the model can follow every time. Once you have settled on that prompt, you can register it as a skill in your toolchain so you do not paste the whole protocol on every run. In VS Code with the Claude Code extension, for instance, you can ask the agent to install the file as a project skill and then invoke it on a document in one message, like the following: Please help me install @project/How to Analyse and Critique Research with AI/critique-research.md as a skill in this project, and then use this skill to Analyse and Critique the article @project/How to Analyse and Critique Research with AI/test.pdf. Here the model returned a layered memo, argument blocks, ratings, and an executive summary, rather than a single slab of prose.<img loading="lazy" decoding="async" class="aligncenter size-full wp-image-144385 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-1.png" alt="" width="2730" height="1576" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-1.png 2730w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-1-300x173.png 300w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-1-1024x591.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-1-768x443.png 768w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-1-1536x887.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-1-2048x1182.png 2048w" sizes="auto, (max-width: 2730px) 100vw, 2730px"> Against a vague one-liner such as ‘Please help me Analyse and Critique xxx,’ the structured prompt keeps the output easier to scan and easier to map back to sections of the paper you are reviewing.<img loading="lazy" decoding="async" class="aligncenter size-full wp-image-144393 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-2.png" alt="" width="2730" height="1576" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-2.png 2730w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-2-300x173.png 300w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-2-1024x591.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-2-768x443.png 768w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-2-1536x887.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/05/08-How-to-Analyze-and-Critique-Research-with-AI-2-2048x1182.png 2048w" sizes="auto, (max-width: 2730px) 100vw, 2730px"> Visual Presentation Pure Markdown text has several limitations: its formatting is relatively uniform, important points are difficult to emphasize visually, and the final appearance often depends heavily on the editor or rendering environment. To improve readability and presentation quality, you can use the following prompt to transform Markdown into a richly styled standalone HTML document. This allows the content to be displayed in a cleaner, more structured, and more visually engaging way. For example, you can use the prompt below to convert your own content. You are an expert editorial web designer, front-end developer, and long-form publication formatter. Your task is to convert the provided markdown document into a polished, standalone HTML reading experience suitable for a premium think-tank, academic journal, or strategic analysis publication. Requirements: - Single self-contained HTML file - Embedded CSS + JavaScript only - Responsive layout - Elegant academic/editorial aesthetic - Serif body text, sans-serif headings - Sticky left-side table of contents - Reading progress bar - Smooth scrolling - Collapsible major sections - Active TOC highlighting Structure: - Title area with metadata - “Helicopter View” overview section - Main numbered sections with concise subsection structure - Minimal but clear visual hierarchy - Subtle callout boxes for key critiques - Simple vulnerability/risk badges - Footer note Style: - Calm, intellectual, modern - Long-form editorial publication aesthetic - Avoid dashboard UI or generic markdown rendering - Use restrained editorial colors and generous spacing Content rules: - Preserve the original structure and analytical tone - Do not heavily rewrite content - Do not over-summarize - Reduce excessive bullet points where possible - Prefer concise analytical prose with selective emphasis Goal: Transform the markdown into a publication-grade analytical article rather than a raw markdown export. After submitting the prompt, wait for the Agent to process the content. Once generation is complete, you will be able to preview the rendered HTML result directly.<img loading="lazy" decoding="async" class="aligncenter size-full wp-image-144409 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.45.36.png" alt="" width="1014" height="1231" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.45.36.png 1014w, https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.45.36-247x300.png 247w, https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.45.36-843x1024.png 843w, https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.45.36-768x932.png 768w" sizes="auto, (max-width: 1014px) 100vw, 1014px"> Conclusion High-quality critical research is, in essence, a structured process of evidence analysis. It is not simply ‘finding fault,’ but testing a paper’s logic, evidence, and argumentative boundaries through systematic stress testing. In this process, the most suitable role for AI is not to replace the researcher in making judgements, but to help organise the structure, identify problems, and solidify the analytical workflow. Only when all judgements can be traced back to the source text and re-verified does AI critique truly hold research value. Appendix The sample input for this guide is a publicly available research brief. The prompt and the generated output (in both Markdown and HTML) are available in the Bandung Circuits repository open-sourced by Global South Insights.
How to Summarise Papers and Books with AI
AI can generate a text that ‘looks like a summary’ in seconds, but the real problem is not whether the model can write, but that many outputs are not suitable for research, teaching, or long-term knowledge management. They are often linguistically fluent and structurally complete, yet lack faithful preservation of the original text’s logic, context, […]
<img loading="lazy" decoding="async" class="aligncenter size-full wp-image-144419 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI_1000667.jpg" alt="" width="1000" height="667" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI_1000667.jpg 1000w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI_1000667-300x200.jpg 300w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI_1000667-768x512.jpg 768w" sizes="auto, (max-width: 1000px) 100vw, 1000px"> AI can generate a text that ‘looks like a summary’ in seconds, but the real problem is not whether the model can write, but that many outputs are not suitable for research, teaching, or long-term knowledge management. They are often linguistically fluent and structurally complete, yet lack faithful preservation of the original text’s logic, context, and evidential provenance. A truly usable literature summary does not merely compress content into something shorter, but preserves the original argumentative structure and conceptual relations as far as possible, and makes key conclusions traceable back to the source for verification. This article therefore focuses not on writing ‘longer’ prompts, but on how to build a repeatable, checkable, and maintainable process for AI-assisted summarisation — specifically of long-form academic texts such as journal articles, book chapters, monographs, and lecture or interview transcripts. The same scaffolding does not transfer cleanly to news, marketing copy, or short-form web content; those genres call for different prompts. Why Many AI Summaries ‘Look Right but Are Actually Unusable’ The problem with many AI summaries lies not in obvious errors, but in ‘vague accuracy.’ The model will automatically complete the logic, smooth out arguments, and rewrite statements carrying limiting conditions into seemingly definitive conclusions. This problem is exacerbated when the model summarises based only on abstracts, partial segments, or a mixture of several sources. Another core issue is the loss of structural alignment with the source. Many summaries silently collapse the original’s chapter and section organisation into a single tidy stream of prose — readers cannot tell which part of the summary corresponds to which part of the source, and any later attempt to revisit a specific argument is forced to re-read the original from scratch. They are suitable for rapid browsing but cannot truly enter serious knowledge-production workflows. How to Use AI to Summarise Articles The walk-through below builds the prompt in five numbered sections. Some sections are fixed — their wording carries the design decisions that make this prompt work, and rewriting them tends to break the prompt rather than tailor it. Others are variable — placeholders that only become useful when you fill them with content for your own scenario. Before reading the sections themselves, it helps to know which is which: 1 Role — Mostly fixed. Keep the ‘chronological, narrative-focused summary’ framing and the ‘self-contained yet faithful’ wording — these are what set the deliverable type. The list of genres (article, book chapter, podcast, talk transcript) can be trimmed or extended to match what you actually summarise. 2 Objectives and Audience — Variable. You fill in the Primary Objective, Target Audience, and Tone. The example shown in that section is a worked sample from the source template — read it as a benchmark of specificity, not as text to copy verbatim. 3 Execution Protocol (3.1–3.8) — Fixed. Keep the eight sub-protocols as written; they encode the load-bearing rules of the design. The one parameter commonly tuned is the length cap in §3.1 (10,000 words is the source template’s default — lower it for short articles, raise it for monographs). 4 Output Format — Fixed. Keep as-is unless your downstream pipeline requires a different shape (e.g., JSON instead of Markdown). 5 Input — Variable. Replace the placeholder with your actual source text on each run. 1. Role Definition When people first try to get AI to analyse a paper, they often simply input a line such as ‘please summarise this article.’ Such blunt instruction may appear efficient, but in fact it pushes the model into a vague decision space. For AI, ‘summarising’ in itself is not a task with clear boundaries: it could become a superficial listing of keywords, a compression of information lacking clear hierarchy, and more often than not, it devolves into vacuous correctness. The root of the problem is that we have not delineated clear boundaries of responsibility for the AI at the very beginning of the interaction. A model that has been explicitly assigned the identity of an ‘expert summary assistant,’ with duties and limitations defined, will produce output of markedly different depth and structure compared to a generic model without role setting, even when given the same text. It is worth being specific about which kind of summary this role is for. In this guide we focus on a chronological, narrative-focused summary — one that follows the author’s own ordering of ideas rather than reorganising them into a critique, a structural blueprint, or a cross-text comparison. Those other goals deserve their own dedicated prompts, and the role definition for each will differ accordingly. Naming this constraint at the role level prevents the model from drifting into analysis or restructuring later on. Therefore, the starting point for any high-quality summary is to clothe the model in a professional identity and let it work with a clear self-understanding. For example: ## Your Role You are an expert **summary assistant** tasked with producing a **chronological, narrative-focused summary** of an academic article, book chapter, podcast interview, or talk transcript. Your primary goal is to capture the text's **flow and content** from beginning to end in a way that is **self-contained** yet entirely **faithful** to the original. You should avoid hallucinating information or injecting your own opinions. You must strictly follow all instructions regarding scope, structure, and faithfulness. 2. Objectives and Audience After defining the role, it is necessary to establish more specific objectives and context for the task. The intended users and ultimate purpose of the summary determine its form. Therefore, this section should clearly fill in the primary objective of the summary, the target audience, language style, and so on. A common failure here is to leave the audience description vague — ‘researchers and students,’ for instance. The more concrete the reader profile, the better the model can calibrate vocabulary, density, and what it assumes the reader already knows. As a benchmark for the level of specificity to aim at, the source template behind this guide names its audience as advanced doctoral students in fields such as philosophy, historical sociology, Marxism, intellectual history, and anthropology — a single line that tells the model both the disciplinary register and the assumed level of background. Your own audience line should be roughly that specific. A worked example, lifted directly from the source template, looks like the following. Treat it as a reference shape rather than something to copy verbatim — keep the three-block structure (Primary Objective / Target Audience / Required Tone), but rewrite the bullets to match your own scenario. ## Objectives and Output Goals ### Primary Objective of the Summary - Provide a **sequential, comprehensive** overview of the source text's arguments, ideas, and evidence as presented by the author. - Serve as the reader's single best tool for understanding how the text's **main points evolve** and connect from start to finish. - Minimise interpretive detours: **focus strictly on summarising** the original text rather than analysing, critiquing, reorganising, or adding external information. --- ### Target Audience for the Summary - Advanced doctoral students in fields such as **philosophy, historical sociology, Marxism, intellectual history, and anthropology**. - Readers who require a **straightforward, meticulously structured, and accurate** grasp of the text's argumentation **in the precise order it is presented by the author**. --- ### Required Tone of the Summary - Academic, clear, precise, and coherent. - Neutral and objective, **without** extensive theoretical framing or rhetorical analysis of the source. - A thorough and faithful retelling that preserves the source text's natural progression and emphasis. 3. Execution Protocol Next, the execution protocol for the summarisation needs to be broken down into a series of rigorous sub-protocols, forming the core operating system of the entire prompt. This is the longest and most consequential part of the prompt: rather than collapsing it into a single block of ‘do these things,’ it should be structured as a numbered protocol the model executes step by step. Each sub-protocol corresponds to a concrete decision the model would otherwise make implicitly — and inconsistently. The eight sub-protocols below mirror the lifecycle of producing a summary, from setting scope, through structuring and writing, to final self-checks. 3.1 Scope and Length Specify which parts of the original must be covered, and how long the summary can be. Two things matter. First, scope: cover all major sections, arguments, and significant references in the order they appear, and do not compress in ways that would distort the author’s emphasis or the overall structure. Second, length: give an upper bound (e.g. up to 10,000 words for a long, dense source) but ask for conciseness where it does not sacrifice completeness. 3.2 Required Structure This is where most generic summaries collapse — they read fluent but feel structureless. Force the model to follow a fixed scaffold: Helicopter view: open with one or two short paragraphs stating what the text is about, how it is organised (a brief roadmap of its sections), and any key themes that will recur. Sequential walk-through: organise the body strictly in the same order as the source. Mirror the original’s section headings as your sub-headings, and use bullets, short paragraphs, or numbered subsections to break down each section’s arguments, evidence, examples, and transitions. Key elements to surface throughout: major claims and theories; definitions of concepts and terms as the author uses them; significant references (thinkers, texts, events the author invokes); author-provided context or background; examples or case studies used to illustrate arguments. Conclusion: briefly restate the overall thesis as the author articulates it, plus any closing thoughts, implications, or calls to action. 3.3 Quotations and Paraphrasing Direct quotes are valuable but expensive. Permit short direct quotes only for emblematic, defining, or striking passages that uniquely illuminate the author’s style, a key assertion, or a critical definition. Prefer precise paraphrase for general arguments. If the source text is not in English, state explicitly whether the summary is quoting an existing translation or producing its own. 3.4 Clarity and Explanatory Notes Two rules in tension. On one hand, break dense or abstract arguments into clear, accurate explanations suitable for the intended audience, and define specialist terminology as the author uses it. On the other hand, do not import external critiques, your own analysis, or theoretical frameworks not present in the original. The only exception is minimal background context: if the author leans on an obscure reference (a thinker, event, or prior debate) without explaining it, a brief parenthetical clarification is allowed — but only to make the author’s own argument intelligible, never to introduce new analysis. 3.5 Faithfulness and Completeness Three commitments. No omissions or additions: do not skip major sections or supporting points, and do not insert interpretations not found in the source. Order and logic: rigorously follow the sequence in which the author presents ideas — and if the original is itself disjointed or non-linear, reflect that faithfully rather than silently tidying it up. Accuracy: dates, names, events, and direct quotes must match the source exactly. 3.6 Style and Formatting Specify the academic register and how the summary should be navigable. Use Markdown headings and subheadings liberally to mirror the source’s structural divisions. Use transitional phrases that reflect the author’s stated logic — for example, ‘Building on this point, the author then discusses…’ or ‘Having established X, the text turns to Y…’ — so that the reader sees how the original moves, not just what it says. 3.7 Deliverable Requirements State what the finished artefact should be: a self-contained summary that lets a reader unfamiliar with the original gain a cohesive, start-to-finish understanding; a chronological, narrative flow that reports each portion in the order originally presented. Equally important is stating what this prompt is not — it is a narrative summary, not an ideological critique, a rhetorical dissection, or a comparative analysis. Those are separate prompts in the same toolchain (the companion TextKillerCritique template in this directory is one such); keep this one strictly to the linear ‘story of the text’ approach. This boundary is what lets multiple prompts coexist without overlapping. There is also a quieter boundary worth making explicit: the deliverable is a standalone narrative document, not a traceback or research-aid index. Structural alignment with the source comes from mirroring section headings (see §3.2 and §3.6), not from per-paragraph page numbers or [Section X]-style anchors attached to each claim. If your downstream use genuinely needs that kind of precise pointer back to the original — for citation harvesting, argument-by-argument verification, or evidence auditing — treat it as a separate task with its own prompt, rather than stretching this one to cover it. 3.8 Final Check Close the protocol with an explicit self-check the model must run before delivering: Adherence to the specific task: no drift into ideological positioning, rhetorical analysis, or comparative tables. Complete yet streamlined: all essential content and arguments covered, without interpretive commentary. Ready for graduate-level reference: polished enough to serve as a reliable, stand-alone resource for the intended audience. Putting it together, the protocol section of the prompt looks like the following skeleton: ## Detailed Summarisation Protocol You are to execute the summarisation according to the following detailed protocol. ### 1. Scope and Length Specify which parts of the source must be covered and the maximum length of the summary, balancing completeness against conciseness. --- ### 2. Required Structure **Helicopter View** Open with a short paragraph stating what the text is about, how it is organised, and the key themes that recur. **Sequential Walk-Through** Organise the body in the source's own order, with sub-headings mirroring the original's structural divisions. **Key Elements to Surface Throughout** Major claims, definitions of concepts and terms, significant references, author-provided context, and any examples or case studies. **Conclusion** Restate the author's overall thesis and any closing thoughts or implications. --- ### 3. Quotations and Paraphrasing Reserve direct quotes for emblematic or defining passages; prefer precise paraphrase elsewhere. Specify how translations are to be handled. --- ### 4. Clarity and Explanatory Notes Break down dense arguments and define terms as the author uses them. Do not import external critiques. Allow minimal parenthetical context only for unexplained obscure references essential to the author's argument. --- ### 5. Faithfulness and Completeness No omissions or additions. Follow the source's sequence and logic — including any disjointed or non-linear structure. Ensure factual accuracy of dates, names, events, and quotes. --- ### 6. Style and Formatting Academic register; Markdown headings mirroring the source; transitional phrases that reflect the author's own logical moves between sections. --- ### 7. Deliverable Requirements A self-contained, chronological, narrative summary. Not an ideological critique, not a rhetorical dissection, not a comparative analysis — those belong to separate prompts in the toolchain. --- ### 8. Final Check Before delivery, verify: no drift into other task types; complete yet streamlined; polished as a stand-alone reference for the intended audience. 4. Output Format The prompt also needs to set clear output format requirements, for example that the output file must be in Markdown format, strictly follow the text-formatting conventions specified in the prompt, and clearly state that no external citations or bibliography are required. This serves as the systematic packaging of all the preceding specifications, ensuring the model knows how to organise them into a deliverable whole. ## Output Format 1. Produce the summary as a **single, well-structured Markdown document**. 2. Adhere strictly to the output specification, especially regarding the use of headings and subheadings to mirror the source text. 3. No external citations or bibliography are required. The focus is on the input text. Output as pure markdown text. 5. Input Content Finally, in the input section at the end of the prompt, the complete paper, chapter, or transcript needs to be pasted in as the primary content, activating the entire process. ## Input `[Paste the FULL TEXT of the academic article, book chapter, podcast interview transcript, or talk transcript HERE for summarisation. Ensure the text is clean and readable.]` Worked example The sections above are not only a tutorial outline; they are a prompt template you can turn into a single file. When you are done, you have a full summarisation prompt, one self-contained instruction set the model can follow every time. Once you have settled on that prompt, you can register it as a skill in your toolchain so you do not paste the whole protocol on every run. In VS Code with the Claude Code extension, for instance, you can ask the agent to install the file as a project skill and then invoke it on a document in one message, like the following. Please help me install @project/How to Summarise Papers and Books with AI/summarise-papers.md as a skill in this project, and then use this skill to summarise the article @project/How to Summarise Papers and Books with AI/test.md The model then produced a long-form summary with clear headings and a stable thread through the source’s own order of ideas.<img loading="lazy" decoding="async" class="aligncenter size-full wp-image-144337 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-1.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-1.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-1-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-1-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-1-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-1-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-1-2048x1340.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> By contrast, a minimal line such as Please help me summarise xxx tends to return something that reads fluent but thin on structure and weak on tying claims back to the text. The same document, run with the explicit prompt above, came back with sectioning you can skim and content that hangs together against the original.<img loading="lazy" decoding="async" class="aligncenter size-full wp-image-144345 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-2.png" alt="" width="2400" height="1570" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-2.png 2400w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-2-300x196.png 300w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-2-1024x670.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-2-768x502.png 768w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-2-1536x1005.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/05/07-How-to-Summarize-Papers-and-Books-with-AI-2-2048x1340.png 2048w" sizes="auto, (max-width: 2400px) 100vw, 2400px"> Validating the Output Section 3.8 of the protocol is the model’s self-check. It catches certain drift patterns — sliding into critique, padding with interpretation, going off-format — but it cannot tell you whether the summary is actually a faithful representation of the source. The model has no way to compare itself against the original. That comparison is the reader’s job, and it deserves a short, repeatable routine of its own. Without it, the whole pipeline is open-loop: you have a process that should produce a good summary, but no mechanism that confirms a given run did. The failures worth checking for are rarely ‘the summary is wrong in obvious ways.’ They are the quiet ones: Section coverage. Open the source’s table of contents alongside the summary. Every major section of the source should be locatable in the summary as a sub-heading or a clearly demarcated block. Missing sections are common when the source is long, when its chapter structure is weak, or when one section is far denser than the others. Hedge preservation. Pick three to five claims in the summary that read as confident assertions. Find the corresponding passages in the source. Models have a well-documented tendency to silently rewrite hedged statements (‘the author tentatively suggests…’, ‘X may be the case under conditions Y…’) as flat declaratives. If the source had qualifiers and the summary has dropped them, that is over-confidence drift — exactly the ‘vague accuracy’ failure mode the introduction warned about. Definition fidelity. For any specialist term the author introduces or uses in a stipulative sense, check that the summary’s gloss matches the author’s usage rather than the term’s general meaning. Over-smoothing of stipulative definitions is the single most common quality failure on theoretically loaded texts. Quote accuracy. Direct quotes should match the source word-for-word, including punctuation. Random spot-check two or three. Phantom references. Sample one or two of the ‘significant references’ the summary names — thinkers, texts, events. Confirm the author actually invoked them, in roughly the role the summary describes. Hallucinated references are rare in modern models but not zero, and they are catastrophic if they survive into downstream citation. Budget roughly ten to fifteen minutes for this the first few times. After a handful of runs on the same kind of source you will learn which failure mode your specific genre is prone to, and the routine compresses to whichever subset still earns its time. Visual Presentation Pure Markdown text has several limitations: its formatting is relatively uniform, important points are difficult to emphasize visually, and the final appearance often depends heavily on the editor or rendering environment. To improve readability and presentation quality, you can use the following prompt to transform Markdown into a richly styled standalone HTML document. This allows the content to be displayed in a cleaner, more structured, and more visually engaging way. For example, you can use the prompt below to convert your own content. You are an expert editorial web designer, front-end developer, and long-form publication formatter. Your task is to convert the provided markdown document into a polished, standalone HTML reading experience suitable for a premium think-tank, academic journal, or strategic analysis publication. Requirements: - Single self-contained HTML file - Embedded CSS + JavaScript only - Responsive layout - Elegant academic/editorial aesthetic - Serif body text, sans-serif headings - Sticky left-side table of contents - Reading progress bar - Smooth scrolling - Collapsible major sections - Active TOC highlighting Structure: - Title area with metadata - “Helicopter View” overview section - Main numbered sections with concise subsection structure - Minimal but clear visual hierarchy - Subtle callout boxes for key critiques - Simple vulnerability/risk badges - Footer note Style: - Calm, intellectual, modern - Long-form editorial publication aesthetic - Avoid dashboard UI or generic markdown rendering - Use restrained editorial colors and generous spacing Content rules: - Preserve the original structure and analytical tone - Do not heavily rewrite content - Do not over-summarize - Reduce excessive bullet points where possible - Prefer concise analytical prose with selective emphasis Goal: Transform the markdown into a publication-grade analytical article rather than a raw markdown export. After submitting the prompt, wait for the Agent to process the content. Once generation is complete, you will be able to preview the rendered HTML result directly.<img loading="lazy" decoding="async" class="aligncenter size-full wp-image-144362 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.27.19.png" alt="" width="942" height="1203" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.27.19.png 942w, https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.27.19-235x300.png 235w, https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.27.19-802x1024.png 802w, https://thetricontinental.org/wp-content/uploads/2026/05/Screenshot-2026-05-22-at-11.27.19-768x981.png 768w" sizes="auto, (max-width: 942px) 100vw, 942px"> Conclusion The greatest value of AI is not to replace reading, but to help humans organise reading more efficiently. A high-quality academic summary is, in essence, a sequence of disciplined moves rather than a single generative act: first set the scope (what kind of summary, for whom, in what register), then fix the structure (the eight sub-protocols that govern coverage, order, faithfulness, and self-check), then generate, and finally validate against the source rather than against your own sense that the output ‘reads right.’ When AI is placed inside that four-beat rhythm — scope, structure, generate, validate — it stops being a text machine that returns whatever sounds plausible, and starts being a piece of research infrastructure: outputs you can trust enough to cite, hand to a collaborator, or build a literature note on top of. Appendix The sample input, the prompt, and the generated output (in both Markdown and HTML) are available in the Bandung Circuits repository open-sourced by Global South Insights.
A Systematic Method for Controlling AI Writing Style
Style is not a preference. It is a specification. Without one, the machine writes in a single voice. Every large language model (LLM) produces prose with the same tells. The contrast rhetoric (‘X isn’t just Y, it’s Z’), the deluge of dashes, the rule of three, the smooth pivot to a generic profundity — once […]
Style is not a preference. It is a specification. Without one, the machine writes in a single voice. Every large language model (LLM) produces prose with the same tells. The contrast rhetoric (‘X isn’t just Y, it’s Z’), the deluge of dashes, the rule of three, the smooth pivot to a generic profundity — once a reader knows the pattern, it is unmistakable. Last year, Forbes’ ‘Seven Tells of AI Writing’ catalogued them; the Field Guide to AI Slop arrived at the same diagnosis from a different angle. And the prose is now everywhere. A report by Graphite found that since November 2024, AI-generated articles on the internet have outnumbered human-written ones. A single, machine-uniform voice has become the majority voice of the written web. The cost of that uniformity is not visible in any single sentence. It becomes visible when the default register is applied to writing whose distinctness was the analytical content. Consider a passage from Tricontinental dossier no. 69, How the International Monetary Fund is Squeezing Pakistan (2022): Pakistan’s balance of payments problems have long been managed by the country’s main ‘export’ — its geostrategic value to Washington. When the United States invaded Afghanistan in 2001, it needed Pakistan’s support, and so it removed its economic sanctions against the country and provided it with economic, security, and military aid. In the same period, owing to Pakistan’s strategic importance in the ‘War on Terror’, the Paris Club rescheduled $12.5 billion out of the total of $13.5 billion of the debt that Pakistan owed to it. Ask a large language model to produce a paragraph on the same material — Pakistan, the IMF, US strategic interest after 2001 — and the output, however fluent, will be of a different kind. A representative run, produced by ChatGPT in May 2026, returned: Following the 2001 United States-led invasion of Afghanistan, Pakistan became a central strategic ally in the so-called “War on Terror,” a shift that significantly reshaped its external economic relations. In return for military cooperation and logistical support, Pakistan received renewed financial assistance, debt relief, and diplomatic backing from Western powers and international financial institutions. In December 2001, the Paris Club agreed to reschedule approximately US$12.5 billion of Pakistan’s bilateral debt, including substantial concessional terms and extended repayment periods. This restructuring eased immediate fiscal pressures and helped stabilize Pakistan’s foreign reserves, but it also deepened the country’s long-term dependence on external creditors and geopolitical alignment with the United States. The post-2001 period thus illustrated the close relationship between strategic security cooperation and international debt governance in the contemporary global order. The factual material is the same. Some critical markers survive — the scare-quoted ‘so-called “War on Terror”‘, the $12.5 billion figure, the named consequences of ‘dependence’ and ‘alignment’. But the analytical core has dissolved. The dossier’s signature move — treating Pakistan’s geostrategic value as the country’s main ‘export’, a critical redeployment of commercial vocabulary that exposes the commodification of sovereignty — has no counterpart. The proportionality of the rescheduling ($12.5 billion out of $13.5 billion, almost the entire bilateral debt) is reduced to a single figure that no longer carries the political weight. The dossier’s grammar, which positions Pakistan’s economic situation as structurally managed by Washington before naming the relation as such, is replaced with active prose in which Pakistan ‘became a central strategic ally’ — an actor entering an exchange, not a country pinned by one. And the paragraph closes with the AI register’s signature move: a balanced ‘but also’ formulation that absorbs the political critique into a wider perspective, followed by a pivot to a generic claim about ‘the contemporary global order’. The model is not unable to be critical. It is unable to make the conceptual moves that turn critical vocabulary into a structural argument. Vague instructions to the model — ‘write formally’, ‘sound analytical’, ‘write like Tricontinental’ — do not recover what was lost. When any instruction underspecifies, the model falls back on a default register: a statistical average of the text it was trained on, smooth, agreeable, and undifferentiated. The challenge for any research institution with a distinct analytical voice is therefore the same: how to instruct a model precisely enough that it produces writing in that voice, rather than the average voice. If a method could be found, the AI register — the default register that AI writing produces, borrowing the stylistics term for the variety of language a context of production generates — could be systematically eliminated. The AI Register Is Structural, Not Incidental Most people’s first response to the AI register is to vary the prompt. If ‘write formally’ fails, try ‘write like a senior policy analyst’ or ‘use shorter sentences.’ Each instruction produces a marginally different result — yet the same machine smoothness persists underneath. The instinct is not wrong. The diagnosis is. The problem is not the instruction; it is what the model reaches for when any instruction falls short of full specification. The Style Mimicry pattern in the published PLoP paper ‘A Pattern Language for Knowledge Engineering with Large Language Models’ (2025) offers a precise diagnosis. A large language model carries a default, neutral, helpfully bland writing style. Users can modify it with simple commands, but these commands often fail to capture the implicit rules of a genuinely specific style. The output ‘feels wrong’: it may technically meet the requirement (it is ‘formal,’ for instance) but lacks the authority, wit, or intimacy characteristic of the target voice. The problem is structural. The model has been trained on vast quantities of text, and its default style represents a statistical average of all that writing: smooth, competent, agreeable, and utterly generic. It is the prose equivalent of neutral grey paint: inoffensive, functional, and entirely forgettable. The average is not politically neutral. The training corpora are overwhelmingly Northern, Anglophone, and produced by the institutions that build, host, and consume AI tools — the corporate web, the academic journal, the US policy blog. The default register is what writing sounds like at the centre of that corpus. For any institution whose voice has been formed at a different distance from that centre, the model’s default arrives as someone else’s accent. Consider a researcher tasked with writing a policy brief. This genre demands strict stylistic discipline: highly formal, analytical, direct, concise. Policy briefs are written for decision-makers who have minutes, not hours. Every sentence must earn its place. When a researcher instructed the AI simply to ‘write a formal brief on this issue,’ the output was professional enough at first glance but missed the genre’s critical features on closer inspection. It was too long. It lacked authoritative tone. It required heavy revision. The problem was vagueness of instruction. An abstract ‘write formally’ cannot convey the implicit rules accumulated over years of a particular writing tradition, the specific cadence of policy argumentation, the expectation that claims are supported by evidence rather than embellished with ornament, the unwritten requirement that a brief sounds as though its author has spent a career in government rather than a career writing blog posts. Nobody told the AI how such a brief should read, so it retreated to its default style, producing text that was formally adequate yet generically flat. This diagnosis points to a clear line of action. If the root cause of the AI register is default-style regression driven by vague instructions, then the solution is to decompose style from a holistic sensory impression into specific, operational descriptions, then feed those descriptions to the AI as precise instructions. This requires a systematic analytical framework capable of turning ‘write it like this’ from a wish into an engineering process. Stylistics Converts Style from Intuition to Engineering Consider again the researcher writing a policy brief. The first attempt, with an abstract instruction, produced text requiring wholesale revision. The second attempt changed approach entirely. The difference lay in the precision of the instruction. That precision came from a specific academic discipline. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-144152" class="wp-image-144152 size-full img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/seven-layer-stylistics-framework.png" alt="" width="2134" height="1250" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/seven-layer-stylistics-framework.png 2134w, https://thetricontinental.org/wp-content/uploads/2026/05/seven-layer-stylistics-framework-300x176.png 300w, https://thetricontinental.org/wp-content/uploads/2026/05/seven-layer-stylistics-framework-1024x600.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/05/seven-layer-stylistics-framework-768x450.png 768w, https://thetricontinental.org/wp-content/uploads/2026/05/seven-layer-stylistics-framework-1536x900.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/05/seven-layer-stylistics-framework-2048x1200.png 2048w" sizes="auto, (max-width: 2134px) 100vw, 2134px"> The seven-layer stylistics framework: decomposing the holistic concept of ‘style’ into observable, analysable linguistic strata Linguistics has a sub-discipline devoted entirely to the study of language style: stylistics. In Stylistics: A Resource Book for Students (2025), Paul Simpson proposes a seven-layer analytical framework that decomposes a text’s style into seven observable, analysable linguistic strata: phonological patterns (the sound effects, rhythm, and prosody of text), graphological representation (visual presentation including punctuation and layout), morphological structure (how words are formed and inflected), lexical choice (diction characteristics such as formality and emotional register), syntactic structure (sentence organisation, length, and construction), semantic implication (literal and figurative meaning, metaphor and imagery), and pragmatic use (discourse-level features: tone, point of view, overall structure). The framework’s core value is this: it converts ‘style’ from a holistic, sensory impression into specific, operational descriptions. When applied to a target text, the seven layers yield a structured ‘style profile’ prescribing how each linguistic stratum should be selected. The transformation is decisive. Where previously a researcher could only say ‘make it sound like The Economist,’ now the instruction specifies exactly what that means at every linguistic level: what kinds of sentences, what register of diction, what rhetorical structures, what relationship between author and reader. The intuition ‘I know it when I see it’ is replaced by a specification that anyone, including a machine, can follow. Imitating a style thereby becomes a two-step engineering process. Step one: analyse the target text with the seven-layer framework to generate a structured style profile. Step two: use the style profile as part of the instructions, directing the AI to produce new text according to the features prescribed at each layer. <img loading="lazy" decoding="async" aria-describedby="caption-attachment-144144" class="size-full wp-image-144144 img-responsive" src="https://thetricontinental.org/wp-content/uploads/2026/05/style-profile-two-step-process.png" alt="" width="2134" height="1250" srcset="https://thetricontinental.org/wp-content/uploads/2026/05/style-profile-two-step-process.png 2134w, https://thetricontinental.org/wp-content/uploads/2026/05/style-profile-two-step-process-300x176.png 300w, https://thetricontinental.org/wp-content/uploads/2026/05/style-profile-two-step-process-1024x600.png 1024w, https://thetricontinental.org/wp-content/uploads/2026/05/style-profile-two-step-process-768x450.png 768w, https://thetricontinental.org/wp-content/uploads/2026/05/style-profile-two-step-process-1536x900.png 1536w, https://thetricontinental.org/wp-content/uploads/2026/05/style-profile-two-step-process-2048x1200.png 2048w" sizes="auto, (max-width: 2134px) 100vw, 2134px"> The two-step engineering process: transforming vague stylistic wishes into precise, actionable AI instructions through style profile generation The policy brief experiment puts this framework to the test. The earlier attempt, using the abstract instruction ‘write formally,’ failed. The second attempt changed approach entirely. Two high-quality policy brief examples were provided, and the AI was asked to analyse them using the seven-layer stylistics framework and produce a detailed style guide. The guide made precise prescriptions at each layer. Under lexis, for instance, it noted that vocabulary is consistently formal and official, devoid of emotional language, preferring specific technical terms over generalities. Under graphology, it observed that numbered enumeration (‘first, second, third…’) imparts clarity, order, and a systematic impression. Under syntax, it reported that sentences are long and structurally complex, using formal logical connectors (‘therefore’, ‘however’, ‘in view of’) to pack considerable information into single sentences. This style guide was then fed back as part of the instructions for drafting a new brief. The result: structure, tone, and vocabulary closely matched the target genre. Editing time dropped significantly. The style guide has another important property: reusability. Once generated, it becomes part of the information reserve, applicable to countless future writing tasks. The creation of a style profile is a one-time investment with continuous returns. For a research institute producing regular policy briefs, the same profile can guide dozens of writing tasks without modification, ensuring consistency across authors and over time. A passage from Dalaya Ashenafi Esayiyas’s ‘Sovereignty or Surrender: Confronting Africa’s Comprador Class’ (2025), the seventh Pan-Africa Newsletter, provides a concrete example of the framework in action: The trajectory of Ghana’s political economy illustrates how a comprador bourgeoisie facilitated neoliberal subjugation, transitioning from Kwame Nkrumah’s socialist Pan-Africanism to becoming an IMF ‘success story’. The 1966 coup against Nkrumah, supported by CIA intervention as revealed in declassified documents, initiated the dismantling of his industrialisation projects. By the 1980s, Jerry Rawlings, once a revolutionary leader, adopted IMF structural adjustment programmes, privatising state enterprises and cutting social spending in Ghana. This shift was institutionalised through three key mechanisms. First, through policy capture, since the World Bank-trained Economic Management Team assumed de facto governance, sidelining ministerial authority. Second, through the implementation of debt as discipline, with IMF loan conditionalities prioritising raw cocoa and gold exports over industrial development, entrenching extractive dependency. Third, through elite co-optation that neutralised opposition, as Rawlings’ former socialist allies were absorbed into consultancies and NGO roles, effectively sanitising dissent. Together, these processes reconfigured Ghana’s economy to serve global capital at the expense of sovereign development. Applying the seven-layer framework to this passage extracts a precise profile. At the pragmatic layer: the passage names its structural diagnosis (comprador bourgeoisie as transmission belt for neoliberalism) in the opening clause, before any evidence is marshalled — the argument is the rhetorical premise rather than the rhetorical destination; the closing sentence (‘Together, these processes reconfigured Ghana’s economy to serve global capital at the expense of sovereign development’) states the political consequence in plain terms, closing the argumentative arc rather than gesturing outward. At the lexical layer: ‘success story’ sits in scare quotes, critically redeploying the IMF’s own triumphalist vocabulary to expose it as a designation of subjugation rather than achievement; analytical concept-coinages — ‘policy capture’, ‘debt as discipline’, ‘elite co-optation’, ‘sanitising dissent’ — compress each structural mechanism into a named category in the analyst’s terms rather than borrowing the institution’s framing; proper-noun precision (Nkrumah, Rawlings, the World Bank-trained Economic Management Team, the 1966 coup) anchors the argument in named historical actors and named institutional bodies. At the syntactic layer: sentences are long and subordinated, but the structure is enumerative (‘First… Second… Third…’) rather than causal-chronological — the argument is delivered as a typology of mechanisms, each named before it is explained, with embedded action verbs (‘assumed’, ‘prioritising’, ‘absorbed’, ‘sanitising’) that specify what each mechanism does rather than only what it is. Once extracted, this profile becomes the instruction set. The AI produces new writing in the source’s register rather than its own default. This process now has open-source tooling. The stylistics skill packages the seven-layer stylistic analysis into a single command. It runs inside an agentic AI environment such as Claude Code. Installation is straightforward: npx skills add eXtremeProgramming-cn/stylistics After installation, running /stylistics extract article.md against any text produces a complete style guide, including an analysis summary, normative rules, a quick-reference checklist, and a domain vocabulary. Researchers need not write their own analytical prompts; a single command extracts the style profile of any target text. The detailed analytical prompt for the seven-layer framework was itself distilled by AI from Paul Simpson’s textbook. A researcher guided the AI through the material to synthesise a structured, practical analytical method — academic knowledge transformed into a tool for AI itself. The AI for Social Science (AI4SS) framework — the Bandung Circuits’ intervention on research sovereignty in the age of AI — calls this ‘full-disciplinary coordination’: the discipline provides the analytical structure; AI provides the capacity to distil and execute it; neither could produce the instrument alone. A style profile can make any voice more like itself. What it cannot determine is whether that voice has anything worth saying. A Style Profile Answers Only the Fifth Question With stylistics’ systematic method and the engineering process of style profiling, the AI register appears eradicable. Yet eliminating the AI register may yield polished output that is still analytically empty, absent the insight that only a human perspective can provide. In ‘Knowledge Engineering: Six Critical Questions for Knowledge Production in the Age of Artificial Intelligence’ (2026), ‘form of expression’ is positioned as the fifth question (the sixth — the researcher’s distinctive contribution — is the meta-question the framework serves rather than a step within it). The same body of knowledge can be rapidly re-expressed in multiple formats: academic papers, policy briefs, video scripts, social media posts. But the first four questions — problem orientation, epistemological framework, information reserve, and methodology — define the supporting structure of knowledge. Possessing stylistic skill does not confer ideology, knowledge base, or analytical method. A style profile solves only the question of how to say something. What to say remains entirely the researcher’s responsibility. By way of contrast, the popular prompt engineering framework CO-STAR serves as a cautionary example. Its six elements are Context (background information), Objective (the task), Style (how information is presented), Tone (emotional quality), Audience (who reads it), and Response (output format such as JSON or prose). Four of the six elements (Style, Tone, Audience, and Response) address how it is said or formatted. What is missing is what to say: epistemological framework, information reserve, methodology, viewpoint and insight — the substantive dimensions that determine whether a piece of writing says something worth reading. The policy brief experiment illustrates the gap directly: the style profile specified sentence length, vocabulary register, and logical connectors; it said nothing about what position to take on the IMF’s role in Pakistan’s debt crisis, which figures to cite, or whose analysis to trust. The Knowledge Engineering framework’s placement of ‘form of expression’ as the fifth question — after problem orientation, epistemological framework, information reserve, and methodology — reflects a principle that runs deeper than the framework itself. Confucius spoke of wén zhì bīn bīn (Analects 6.18: ‘质胜文则野，文胜质则史。文质彬彬，然后君子’) — refinement and substance held in proportion. ‘Wén’ (stylistic expression) and ‘zhì’ (substantive insight) are both indispensable, but they are not symmetrical. The priority of ‘zhì’ over ‘wén’ is the priority Marx would later name in materialist terms: “it is not the consciousness of men that determines their being, but, on the contrary, their social being that determines their consciousness” (Preface to A Contribution to the Critique of Political Economy, 1859). Substance grounds form, not the other way round. Words without elegance do not travel far. But elegance without substance lacks even the qualification to travel at all. A style guide is itself a reusable asset: a researcher at a resource-constrained institution can develop one suited to the organisation’s positioning, and the entire team can share it. But that guide cannot decide for the researcher whose side to stand on, what questions to ask, or which sources to trust. Style is ‘form of expression,’ an engineerable capability, but it cannot substitute for the more fundamental dimensions of knowledge engineering: problem orientation, epistemological framework, information reserve, methodology. The Human-in-the-Loop Provides Purpose, Not Approval The significance of stylistic tools becomes clear only within a larger picture. The AI4SS framework proposes four pillar capabilities, one of which is ‘full-channel output.’ The core claim: a researcher’s in-depth analysis can simultaneously reach different readerships as an academic paper, a policy brief, a newsletter column, a social media post, each channel demanding its own stylistic and format conventions. This means researchers need to find the appropriate expression for each outlet. Without stylistic tools, the researcher must either find a style-matched editor for each channel or spend considerable time polishing different genres alone. For research institutions in the Global South, where editorial resources are scarce and language barriers compound the challenge, this constraint has practical consequences: good analysis fails to reach the audiences that need it, weakened by the wrong packaging rather than by weak ideas. Stylistic tools change the equation. Once a style profile is generated, it becomes part of the institution’s information reserve — a reusable knowledge asset that can be applied to countless writing tasks and shared across team members. A resource-limited research institute can have one person develop multiple style profiles and distribute them across the team. The same analysis of IMF conditionality in Pakistan can be sent to progressive media readers in the Tricontinental dossier register, or delivered to a finance ministry desk in a policy brief. The knowledge is singular. The voices are plural. AI handles the repetitive labour of stylistic polishing. The researcher handles what no machine can: deciding whose side to stand on, what questions to ask, which sources to trust. The AI4SS framework names this the ‘human-in-the-loop’ principle — not because the human approves the machine’s output, but because the human’s analytical work is what gives that output its purpose. Stylistics engineers wén. What the Global South needs from its research institutions is zhì — the analytical position, the political commitment, the knowledge of conditions no model was trained on.