I conducted a session on Wed, 12 Aug 2026 at ED5518: Data Visualization for Engineers - Department of Engineering Design, IIT Madras, Chennai. Summary: AI can generate charts and analysis. The enduring skill is knowing what deserves to be visualized, challenged, and communicated. Here’s the link to the session Links: Transcript Audio (72 min)
Last week at VizChitra, I ran a “Dialogue” session. A new format for me. I usually speak 80% in my workshops. In this dialog, I spoke 20%. The group discussed. PART A I showed 6 charts and said, “Pick the best.” Then I shared the audience & purpose and asked: “For THIS audience and purpose, will you publish, fix, or kill it?” INSIGHT: almost no one said, “Ship”. That’s good – these were all drafts. ...
On Sat 13 Jun 2026 at 3 pm, I conducted an online workshop on Data Stories with AI. Registration link: https://forms.gle/dNkUxtJ2PVqNMNcE9 In this workshop, the audience used ChatGPT and Claude, mostly, to: Find data Analyze it Extract insights Visualize as stories It’s a data visualization using AI workshop for journalists - but you don’t need to know data, visualization, journalism, or even technology. But this is a practical workshop. You’ll be doing stuff and sharing your results. ...
I conducted a session on Wed, 29 Oct 2025 at IIT Madras — Department of Engineering Design - Chennai, India. Summary: LLMs can generate, interpret, and even invent visualizations. The analyst’s role shifts toward asking better questions, testing novelty, and judging whether a visual is useful. Here’s the link to the session Links: Transcript
We created data visualizations just using LLMs at my VizChitra workshop yesterday. Titled Prompt to Plot, it covered: Finding a dataset Ideating what to do with it Analyzing the data Visualizing the data Publishing it on GitHub … using only LLM tools like #ChatGPT, #Claude, #Jules, #Codex, etc. with zero manual coding, analysis, or story writing. Here’re 6 stories completed during the 3-hour workshop: Spotify Data Stories: https://rishabhmakes.github.io/llm-dataviz/ The Price of Perfection: https://coffee-reviews.prayashm.com/ The Anatomy of Unrest: https://story-b0f1c.web.app/ The Page Turner’s Paradox: https://devanshikat.github.io/BooksVis/ Do Readers Love Long Books? https://nchandrasekharr.github.io/booksviz/ Books Viz: https://rasagy.in/books-viz/ The material is online. Try it! ...
My VizChitra talk on Data Design by Dialog was on LLMs helping in every stage of data storytelling. Main takeaways: After open data, LLMs may the single biggest act of data democratization. https://youtu.be/hPH5_ulHtno?t=01m24s LLMs can help in every step of the (data) value chain. https://youtu.be/hPH5_ulHtno?t=00m47s LLMs are bad with numbers. Have them write code instead. https://youtu.be/hPH5_ulHtno?t=06m33s Don’t confuse it. Just ask it again. https://youtu.be/hPH5_ulHtno?t=05m30s If it doesn’t work, throw it away and redo it. https://youtu.be/hPH5_ulHtno?t=20m02s Keep an impossibility list. Revisit it whenever a new model drops. https://youtu.be/hPH5_ulHtno?t=20m02s Never ask for just one output from an LLM. Ask for a dozen. https://youtu.be/hPH5_ulHtno?t=22m20s Our imagination is the limit. https://youtu.be/hPH5_ulHtno?t=26m35s Two years ago, they were like grade 8 students. Today, a postgraduate. https://youtu.be/hPH5_ulHtno?t=00m47s Do as little as possible. Just wait. Models will catch up. https://youtu.be/hPH5_ulHtno?t=31m45s Funny bits: ...