S Anand

Students of my course were given an assignment. Submit a picture story (no words) that others will understand and like. Explain others’ picture stories and rank them. Here are the results. Firstly, why this exercise? Because it teaches three skills I believe are important in the AI era: Creating unique content Communicating with clarity Marketing your ideas This is exactly what they were evaluated on. Uniqueness: How similar was their story to others'? Understanding: How well did others understand their story? Preference: How much did others prefer their story over others'? Here are some stories I enjoyed. Click for details. ...

Note: This continues my nasty habits series: licking, scraping, and nibbling - in which I mentioned fiddling with nails. There are three irreplacable possessions in my room: My phone, because it authorizes lots of services. My laptops, because they have un-backed-up data. My toenails, because the good ones are rare. Here are two good ones I’ve had for a few months. The ones best for fiddling are from the toe thumb. They typically have: ...

I was reading Asterix on my flight from Brussels to Dubai when I remembered a colleague’s request. I typically convert my workshops into narratives like this and this. They wanted another event converted. Usually, I have the full transcript of my events. In this case, I just had a few paragraphs of notes. Far from enough. On the other hand, I was reading Asterix. And AI’s my magic potion. So I figured: Why not create a comic story? Using real faces? While reading Asterix? ...

Using the same approach as specification and verification I looked at how I review agents, i.e. what I comment on after they share an output. This page features the 28 review techniques I use. Some interesting ones: Show your style: I tell it why it doesn’t sound like me, and how I would have written it. Real example: “Still not in my style - revise more in line with these principles.” Pause and resume: Tell it not to exceed the usage limits. Real example: “We are at 96% usage of the 5h limit - so pause now and we can resume in a few hours.” More like this: Tell it what you liked and go in that direction. Real example: “Looks good. Give me 10 more.” Take the best of each: Give it other models’ output and pick the best from each. Real example: “Here is ChatGPT’s response. Take what’s better, drop what’s worse, follow up on new ideas this gives you, and revise your response.” Say “I meant…”: Clarify your real intent. “Sorry, I meant round off the 95% activity window in EACH namespace.” These are based on ~6.7K real responses. Skim through them and if you spot something interesting, test it out. If it works for you, share it with others.

This Thursday, I flew Indigo from Singapore to Chennai. I had no WiFi and got a lot of (slightly difficult) reading done, such as: Machines of Loving Grace Against the Personal Theory of Agents Paul Graham’s The Top Idea in Your Mind How I Built the Most AI-Pilled Company in the World Catching up on Simon Willison’s blog Actions from a long pending book cluster summary (The Beginning of Infinity, Conjectures and Refutations, The Logic of Scientific Discovery, The Fabric of Reality, and Enlightenment Now). Several tweets, blog posts, and ChatGPT / Claude chats. I also drafted prompts to run later. In a disconnected flight, I’m less distracted because: ...

I conducted a session on Wed, 04 Nov 2026 at ED5518: Data Visualization for Engineers - Department of Engineering Design, IIT Madras, Chennai. Speakers: Anand S Summary: A live-lab class on testing visualizations and phone apps: commit to an answer before discussing, check that a chart is true and that it works for its audience, use AI as a different kind of reviewer rather than a stand-in for people, and ask busy people “A or B?” ...

The Innovation team has been experimenting with 3D interaction, audio, video and AI agents. Three things struck me: We can manipulate a 3D molecule with our hands, or try different furniture in a virtual room, using a browser. Sound search can find things a transcript never records. And a small specialist model can diagnose a machine at a tiny fraction of an audio LLM’s cost. AI can help us improve videos and business decisions when its suggestions are checked against evidence, not just written convincingly. New ways to interact and create Hold a 3D molecule in your hands (Sujal). At our Innovation Team meeting, I used hand gestures in front of my camera to manipulate a colourful 3D ATP synthase molecule: pluck, slice, scale, rebuild and explore its parts. The browser recognizes the gestures; a paired phone can also control the scene. It is related to Sujal’s remote 3D pottery experiment. ...

Since agents do most of the work, specification (telling it what to do) and verification (making sure it did it right) is more important than execution. This is what I’m often asked about. Of the ~600 questions people asked me this year, half were deciding what to do / ask for and every sixth question was about checking if it worked. I checked. For example: “What should we ask agents to do when we only have a dataset and no clear use case?” ...

I conducted a session on Mon, 02 Nov 2026 at TDS Course Ideation — Open Design Meeting, Sep 2026 - Remote. Speakers: Anand S Summary: In the fourth open TDS design meeting, the teachers ask what is left to teach once an agent can read and solve the exam — while doubling a spending cap students are forecasting, finding only eight drawings that fool every AI guess, and admitting a marketplace rewarded trading over usefulness. ...

This week, I learned: Enterprise software migration seems a massive medium term opportunity - Ethan Mollick. On the other hand, liquid software where anyone can tweak their own softare is emerging. “But I’m not working for my agent, it works for me. It’s a computer. It’s not a person I have to keep busy and keep managing (and checking it’s managing it’s own agents).” - Ben Tossell OpenAI announced that ChatGPT Chat (except Instant) will start getting metered from December 2026. This is a big deal for me because: I prefer ChatGPT Chat / Work to Codex because it can access my past conversations. Chat (in my ChatGPT $20 Plus) isn’t metered visibly and feels unlimited. By giving ChatGPT a plugin to control my computer, I get most of the benefits of Codex. But this free use will last only a month. I need to see how well GPT 6.1 Terra fills that gap - i.e. is it good enough to beat GPT 6 Sol and cheap enough that I can run my chats without worrying about exhausting limits? Clairic is an extraction model from Cloudflare. It’s a Decision model (or System One model) like Jev: fast and lightweight. But this focuses on extraction of text, numbers, dates, even forecasts. It provides the confidence as well as input position of the text for reference. Anthropic recommends using the main agent rather than subagents. Single agents on smart models work well unless you need independence #ForNow. Ruby chocolate is the fourth variety of chocolate - alongside dark, milk, and white. (Might be a marketing claim than verified.) I tasted it. It’s fruity, slightly sour, not bad. My order of preference among the melted chocolates I tasted in a spoon at Chocolate Nation, Antwerp: Gold. Caramel toffee butter cream . Delightful! White W2. White chocolate. Something I usually enjoy. I was surprised I liked Gold more. 823. Milk cocoa caramel chocolate. Slightly darker. Power 41. 41% cocoa Caramel with less sugar. Ruby. Fruity sour taste. Arriba. Strong cocoa flavor. 811. Bitter. The rest were too bitter I had no idea there was so much innovation in chocolates. Most of the ones I like are a century old. Good to see some revival in the last decade. ChatGPT 1880s: Truffles. chocolate that melts immediately in the mouth. 1907: Hershey’s Kisses. 1908: Toblerone. 1912: Pralines. chocolate shell with creamy filling. 1920: Chocolate-coated ice cream (like Magnum). 1923: Filled chocolate bars. 1923: Nougat-caramel chocolate bars (like Five Star, Mars). 1923: White chocolate. 1926: Chocolate syrup (Hershey’s). 1928: Peanut butter cups : Combined sweet chocolate with salty, savory peanut butter for a striking flavor and texture contrast. 1932: Chocolate oranges. 1935: Aerated chocolate with tiny air bubbles. 1935: Chocolate-coated wafers (KitKat). 1936: Malted chocolate balls (Maltesers) 1949: Soft-melting chocolate centers (Lindor) 1951: Chocolate-hazelnut spread (eventually Nutella) 1969: Spherical filled chocolates (Lindor) 1971: Chocolate eggs (Cadbury Creme Egg) 2012: Blond chocolate: white chocolate with biscuit and toffee notes. 2017: Ruby chocolate: pink, fruity, sour. 2021: Dubai chocolate: Pistachio cream, cruncy. Looks like GPT 6.1 Terra is mostly as good as Sol but cheaper. I haven’t tested it yet. On one hand, modern CSS has several new features. On the other hand, I’ve stopped writing code and delegated it to agents, so this is of no use to me. Instead, what I should be thinking about is: what new patterns does this enable, and what should I be asking for in prompts? Ethan Mollick: “Ask yourself: “how do I make what I am doing even more ambitious?” Something to practice actively, given the growing abilities of agents. Anthropic is comfortable that no single person has an architectural view of Claude Code. I guess architecture is also being taken over by agents. Addy Osmani: “No member of the team has a full mental model of Claude Code in their head, nor do we think anyone needs to. Rather, when anyone wants to learn about a piece of the codebase, they ask Claude to generate an explainer about that exact slice. It only takes a few minutes and the explainer is always up to date.” Good advice from Thornton Bell Humans write for humans. Agents for agents. Be more ambitious. Give it more eyes - logs, observability, … Code on remote machines. Ask for 5 variations. (I’m not doing enough of this yet.) Use schedules and triggers. (I’m not doing this at all, so far.) Codex introduced an experimental #ForNow --enable instant_interrupt flag that looks promising. It’s still steering, i.e. not instantly stopping any existing requests or tasks (hence wasting effort), but doesn’t wait for the entire response either. Not sure how it works but I just enabled it and will evaluate it. Code-mode yielding PR, model-response preemption PR. In Codex you can @-mention another Codex session. That’ll give it access to an earlier session’s context. In the past, I copy-pasted session transcripts, saved them in files, or pointed Codex at the session directory. This is more convenient. PixelBoard has pretty impressive cvoice typing. Google has a Gemini-powered “Rambler” voice recognition system (based on Gemini 3.5 Translate, with offline fallback) on Android phones, but not available via GBoard. PixelBoard enables that. ChatGPT Mistakes I made Week ending 01 Nov 2026 ...