S Anand

Thornston Bell’s How I work with Agents suggests actively using remote machines for coding. I’d struggled with this for many months, and finally managed to set up my Windows laptop for remote coding. How? Tell my wife to tell the maid to never switch it off. (It doesn’t have battery.) Tell ChatGPT to install Remote Desktop Commander - and schedule it to run on boot. Now agents can use it. Tell ChatGPT to install Tailscale so I can SSH into it and copy files. Tell ChatGPT to create a sync-plutonium.sh that pushes files from my Linux system (graphene) to the Windows machine (Plutonium). That last step was the critical enabler. This means that most of the files on my regular laptop is also on the home laptop, and it has the same context. ...

I think it’s a miracle to see the sheer number of technologies that can come together with AI agents orchestrating them. I’m right now on a flight from Brussels to Dubai, and the Wi-Fi works. So, I’m dictating this blog post via PixelBoard, an AI-coded port of Gboard that lets me use Gemini for voice typing on Android (which is quite good!). I’m also browsing my Asterix comic book collection. These are on my Windows laptop in Singapore, which I’ve connected via Tailscale. I have no idea how to configure Tailscale, and ChatGPT did that for me. BTW, Tailscale is one of those services that I didn’t see a use for until I used it, and now will never turn it off. It creates a VPN between my phone, traveling laptop and home laptop, so I can browse files, SSH into each other, run HTTP servers, etc. All securely. ...

The Innovation team has built a few more demos since the last update. Three interesting learnings: We can speak in one language and be heard in another, live, in a normal Google Meet call. A person in another city can use their hands and a phone to sculpt a 3D object on your laptop. AI can search what was heard, not just said, and can check scientific claims by actually reproducing them. New capabilities Translate a live meeting into almost any language (Hritik). At Friday’s VIA talk, I spoke and the audience heard Filipino, Hindi, Tamil and Telugu with a short delay. Hritik built a desktop app that creates a virtual microphone and speaker for Meet. It translates both ways: what others hear from you, and what you hear from them. It took him a day or two to vibe code, and comes as a Windows, Mac or Linux app. I estimated about 0.6 US cents a minute in my trial. ...

I’ve been playing around with mobile sensors recently and one such experiment is the voice choir. Here’s how it works. I’m the presenter. I visit voice choir, create a room, and show the QR code. People see the QR code (via screen-sharing or projector) and open on their mobile phones to join my room. I press “Start”. They hear a tone and they should hum at the same pitch. They can see if their pitch is above or below and adjust. I get a data stream of their pitch. Over time, we see if we can hum at the same pitch, or how close we converge. I record this as a visualization. We played this in Straive across about 20 people who joined the room. Here’s the video: ...

This week, I learned: Neural Networks Are Already Clean argues that in modern LLMs, most neurons have one function, not arbitrary overlapping functions (like we thought earlier). This becomes clearer when you see the learning steps, e.g. the “iy” neuron -> “diy” -> “do it yourself”. Without the “diy” in the middle, it’s confusing what “iy” has to do with “do it yourself”. Models probably learn by generalizing concepts repeatedly. Interpreting models has the bitter lesson, too: just tell a powerful agent to interpret it. Modern LLMs have switched from ReLU to SwiGLU. Why? ReLU is on-off and communicates no information when off. SwiGLU is a smooth function that whispers less relevant information - and that gives smarter models more context. Gemini 3.8 Flash is SLIGHTLY cheaper than Gemini 3 Flash Preview when transcribing 1 min of audio - #ForNow until Dec 31. After that, a higher pricing kicks in. ChatGPT ArtCraft extended their open source tools to cover MS Office, Adobe, and Autodesk #ForNow. Others are following suite. The Remade Wiki has includes OneNote, QuickBooks, Power BI, Outlook, MS Project, Visio, Discord, Jira, Linear, Monday, Corel, … #ForNow Cloudflare ported the TypeScript compiler to Rust. Increasingly, language choice is becoming fluid. Tiny Little Office uses a number of interesting tricks: The entire document is in the URL fragment, which is as much as 2 MB for Chrome! That means the entire document can be shared as a single QR code (if it’s not too large). Docs, spreadsheets, presentations, diagrams are all Markdown-based #ForNow and agent-friendly. They can be embedded as code fences inside each other. It uses domain-specific compression tailored to its language. It also uses ~ instead of - for base64 - to avoid wrapping issues with mail clients. It uses directives for agents. The way it is organized is interesting! document.currentScript.replaceWith(...) can be used as a nifty way to dynamically replace content, effectively creating a mini-templating language. Via Simon Willison. Standardization and personalization are independent axis. In fact, standardization can make personalization easier. ChatGPT Before the printing press, people used to spell words differently. Shakespeare, for example, had different spellings of his name. With the printing press and distribution of publication, spelling became standardized. But interestingly, it standardized by freezing the current conventions. So some oddities of the spellings people used are now a formal part of the language definition. In pharmacies, we call them “compounders” because they actually used to compound, i.e. mix, medicines - personalizing them to each individual. That faded away as standardized tablets became more common. Fonts are becoming more sophisticated. Some features in newer fonts are: Icons: NerdFonts is an example of a font class with 10K+ icons embedded - like 󰊢 GitHub, 󰈙 files, or 󰀨 terminals. Opt-in Ligatures: Display multiple characters as one symbol, e.g. => as ⇒, != as ≠, or >= as ≥, letting users pick what to enable. Variable weight: Continuously adjust thickness, e.g. weight 450 or 575 instead of being limited to Regular (400) and Bold (700). Smart width: Make characters narrower or wider, adjust shapes based on neighbors (making mi look more evenly spaced), etc. while preserving mono-space. “No one cares more about your case than you, so take control and send lots of follow-ups.” Things to know if you get cancer. The article has usefuls tips for important things in life, in general - not just cancer. Agents are making this easier. Because Amazon has a fair pricing policy, a strange consequence is that if Amazon sellers raise prices on Amazon they’re pressured to raise prices elsewhere too! So, increasing Amazon seller fees tends to increase prices across the board. How Amazon pushes up pricess all across the Internet Will Jev destroy its servers to save 5 lives? Will other models? A lovely set of experiments based on the trolley problem. Mistakes I made Week ending 25 Oct 2026 ...

I conducted a session on Mon, 19 Oct 2026 at TDS Course Ideation — Open Design Meeting, Sep 2026 - Remote. Speakers: Anand S Summary: A week after inventing agent-friendly assessments in public, the TDS team meets running code, student questions, checking budgets, a dropped $500 experiment, leaky graders, and a pass rate that only counts who scored above zero. Here’s the link to the session Links: Video (60 min) Transcript Captions Audio (60 min)

The Innovation team built a few more demos last week. Three interesting learnings: Construct a 3D world you can walk through - from a picture. Real-time video analytics is increasingly easier with decision models. Small models supported by rules tend to perform well. 3D Worlds Turn one photograph into a 3D world. Jivraj used NVIDIA Lyra and other world models to create 3D worlds (from pictures) that you can walk through. ...

I conducted a session on Sun, 18 Oct 2026 at AI Product Leadership (AIPL) 2026, Module 5 Session 1 — LeadUp Universe with E&ICT Academy, IIT Kanpur - Online (Zoom). Speakers: Anand S Summary: A leadership workshop on delegating to AI stalled on a hard question; the instructor let AI act on the room, then asked it how to fix the workshop, and the session ended on an untested experiment for knowing when to stop AI. ...

This week, I learned: I tested a few tools that help agents work with mobile devices. On Android, apart from adb, mobile-mcp seems better than Android-MCP or mobilerun (which has a different purpose, though) #ForNow. More importantly, agents controlling mobiles with USB debugging seems quite seamless. HeyPuter is cloning every software #ForNow into open-source apps. I expect more people will do this. Consumer software moats will probably erode faster than enterprise software (which has regulatory and other moats). My colleague built his own mobile music player yesterday using Claude Code and rea to reverse engineer the YMusic APK. Another example of technically capable users building their own (disposable) software. Fingerprints are the new cookies. I was surprised to see that the server could identify me correctly even in Incognito mode. Cover your tracks lets you test your browser privacy and mine was unique among ~369K users. My user agent, system fonts, Canvas fingerprint, WebGL fingerprint, audio compression float differences, WebGL Vendor & Renderer, and HTTP Accept Headers were the biggest unique-ness identifiers.. Thinking will become a hobby. Interesting point. After all, with the mechanical revolution, exercise became a hobby. (Interestingly, schools teach very little exercise - or most other hobbies.) Claude Code just told me that “Version 1.0.10 was published only 2 days ago, so to be supply-chain cautious I’ll pick a release that’s at least 2 weeks old.” That’s pretty circumspect of it - and I learnt a new term: “supply-chain caution”. Paraphrasing Andrej Karpathy: LLM capability is widening - something I’m seeing in my interactions, too #ForNow. 75% of the population has barely seen LLMs. 20% are free-tier users (searching, writing, maybe booking a flight) who see occasional use. 0.2% see large, complex projects one-shotted: apps, math proofs, … ~5,000 people see swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Human review and comprehension are falling behind: “archeology” of the OpenAI-HF incident, studying the 722 OpenAI proofs… That’s because we don’t have a reservoir of big, difficult problems we really care about; and the jagged edge: digital, verifiable and economically valuable domains grow faster; and access is uneven: free-tier, paid-tier, internal. Cloudflare acquired Deno. “After that year we will end our development of the Deno runtime.” Good for Cloudflare, pity about Deno. It was a good kick in the rear for NodeJS. Ryan’ll be porting celld into workerd. What I learnt is: workerd might be a realistic alternative to write web servers - instead of NodeJS, Express, etc. Durable Objects (worker + storage) seem to be a more powerful infrastructure component than I thought. They’re powering Queues, Workers, Git storage (artifacts), and more. Wallhop lets you skip paywalls #ForNow. Built by Josh as a 12ft.io replacement forking everywall/ladder. From How Anthropic Builds And How Engineering Will Change Soon | Thariq Shihipar: Examples - especially personal examples - are still an excellent way to prompt models. Agents do what the typical user wants pretty well. Focus your personalizations on how you want things done differently from the typical user. Learn vocabulary and intuition in areas where AI needs help. Visual design, mathematical ideation, economic theory, … Things move so fast (at least in code) #ForNow, so plan to deliver value within a month or two. For longer projects, wait for the next generation of agents to change the economics. Mistakes I made Week ending 18 Oct 2026 ...

Sometimes, you need multiple approaches for different parts of a problem. Increasingly, agents are making this easier. For example, at MSCI, we’re using Google Translate to translate PDFs. Sometimes it does a great job. For example, here’s Hyundai’s E&C Sustainability Report, 2026, in Korean. It was translated perfectly by Google Translate. At other times, it does a terrible job. For example, here’s Pakistan’s Power Cement Annual Report 2026 in Urdu: ...