It’s incredible how far coding agents have come. They can now solve complete exams. That changes what we should measure. My Tools in Data Science course has a Remote Online Exam. It was so difficult that, in 2023, it sparked threads titled “What is the purpose of an impossible ROE?” Today, despite making the test harder, students solve it easily with Claude, ChatGPT, etc. Here’s today’s score distribution: ...
Is all AI content slop? I asked Claude to: Analyze this thread. Then explain it like a Malcolm Gladwell New Yorker article. https://news.ycombinator.com/item?id=45820872 It gave me a beautiful, engaging and insightful essay about a 300+ message debate about AI vs humans on routine tasks. https://claude.ai/share/60c5810f-5c81-4970-8026-a24bf89c3392 Is this slop? One phrase stood out: There’s an irony here that the commenter doesn’t quite state but implies beautifully: we’ve spent so long celebrating automation because humans are imperfect that we’ve forgotten we also value humans because they’re imperfect. ...
The OpenAI text-to-speech cost documentation is confusing. As of 2 Nov 2025: GPT-4o mini TTS costs $0.60 / MTok input and $12.00 / MTok audio output according to the model page and the pricing page. They also estimate this to be ~1.5c per minute - both for input and output. It supports up to 2,000 tokens input. TTS-1 costs $15 / MTok speech generated according to the model page but the pricing page says it's $15 / MChars. No estimate per minute is provided. Is supports up to 4,096 characters input. TTS-1 HD is twice as expensive as TTS-1 I wanted to find the approximate total cost for a typical text input measured per character and token. ...
Sometimes, technology creates truly memorable moments. Like when email connected me with my schoolmates in 1993. Or WhatsApp connected me with long-lost relatives in 2010. Today, Google Gemini took me back 55 years, converting the grainy black-and-white wedding photos of my parents into vivid high-resolution color images. So many people. Much younger. More alive. I look forward to when I can watch the video. Move around. Talk to them… Prompt: Convert this black and white photo to color. CAREFULLY ensure that the photo, especially faces, are EXACTLY the same. Use vivid colors and sharp photography, like in modern digital photos. Model: gemini-2.5-flash-image (nano-banana) Temperature: 0 ...
I charted the OpenAI GDPVal paper with industry compensation as the size and AI augmentation as color. Big green areas are we’re paying people where AI does better. Click here to see the interactive visualization. Clicking to see some actual tasks compared. I use this to check whom to ask advice: AI or professional. AI beats Personal Financial Advisors ~64% of the time. So I invested half my money using ChatGPT’s recommendation. (UTI Nifty 50, if you’re curious.) ...
I asked multiple coding agents and models to build the same app: Create a single-page web app at index.html that beautifully renders a GitHub user profile and activity comprehensively. Pick the ID in the URL ?id=…, default to ?id=torvalds. … and compared their quality, cost, and speed. My observations: Quality variance is the highest. Some models / agents produce great visuals, some average, some fail completely. Cost and time variance are lower among the successful models. About 2X variance in each. ...
I don’t charge for workshops. Altruism? No: it’s self-interest. “If you’re not paying for it, you’re not the customer; you’re the product being sold.” Andrew Lewis, via Tim O’Reilly, 2010. My workshop process is designed to benefit me first. I pick topics I want to learn, not stuff useful to the audience. Example: I picked DuckDB for my PyCon India 2025 talk to learn it. ...
I was testing LLMs’ sense of Tamil humor with this quote: Extend this post with more funny Tamil words that end with .ai - mentioning why they’re funny. Chenn.ai is the artificial intelligence capital of India. Kadal.ai Kad.ai Dos.ai Vad.ai Ad.ai Thal.ai Mallig.ai Aratt.ai And finally Podad.ai All spoken in namma bash.ai 😅 The Chinese models didn’t fare well. DeepSeek made up words. Mood.ai - An AI that perfectly captures your mood. Sokk.ai - The AI for when you’re bored. Thanni.ai - A hydration assistant. Qwen too. ...
Can ChatGPT give teachers data-driven heuristics on student grades? I uploaded last term’s scores from about 1,700 students in my Tools in Data Science course and asked ChatGPT: This sheet contains the scores of students … (and explained the columns). I want to find out what are the best predictors of the total plus bonus… (and explained how scores are calculated). I am looking for simple statements with 80%+ correctness along the lines of: ...
Last weekend, I fed Codex my browser history and said “explore.” It found a pattern I call rabbit holes – three ways we browse: Linear spiral - one page > next page > next. E.g. filing income tax, clicking “next” on the PyCon schedule. Hub & spoke - hub > open tabs > back to hub. E.g. exploring DHH’s Ubuntu setup, checking Firebase config. Wide survey - source > many, many pages. E.g. clearing inbox, scanning news. Then Claude Code built this lovely data story. ...
Yesterday, I discovered how much reasoning improves model quality. My Tools in Data Science assignment asks students to draft an llms.txt file for ipify and auto-checks with GPT-5 Nano - a fast, cheap reasoning model. I set reasoning_effort to minimal and ran this checklist: 1. Starts with "# ipify" and explains ipify. 2. Markdown sections on API access, support (e.g. GitHub, libraries). 3. Covers API endpoints (IPv4, IPv6, universal) and formats (text, JSON, JSONP). 4. Mentions free, no-auth usage, availability, open-source, safeguards. 5. Has maintenance metadata (e.g. "Last updated: <Month YYYY>"). 6. Mentions robots.txt alignment. Stay concise (no filler, <= ~15 links). If even one checklist item is missing or wrong, fail it. Respond with EXACTLY one line: PASS - <brief justification> or FAIL - <brief explanation of the first failed item>. With a perfect llms.txt, it claimed “Metadata section is missing” and “JSONP not mentioned” – though both were present. ...
Tools in Data Science Sep 2025 edition is live: https://tds.s-anand.net/. Major update: a new AI-Coding section and fresh projects. I teach TDS at the Indian Institute of Technology, Madras as part of the BS in Data Science. Anyone can audit. The course is public. You can read the content and practice assessments. I fed the May 2025 term student feedback into The Sales Mind and asked: What are the top non-intuitive / surprising inferences? What are interesting observations? What are high impact actions? Full analysis: https://lnkd.in/gVWVqaxN: summary, outliers, and action ideas. ...
The 11 sites I visit most: ChatGPT. It’s replaced Google as my default knowledge source. I prefer it over Gemini, Claude, etc. because the app has good features (memory from past conversations, code interpreter, strong voice mode, remote MCP on web app, etc.) The OpenAI models have pros and cons, but the app features are ahead of competition. Gmail. It’s my work inbox. Interestingly, I check it more (and respond faster) than social channels (e.g. WhatsApp, Google Chat, LinkedIn). It also doubles up as my task queue. WhatsApp. It’s my default phone + messaging app. A fair bit of my work communication happens here, too. Prime Video. I mainly watch The Mentalist. Totally love Patrick Jane! Google AI Studio. Mostly for transcription. It’s better than Gemini on UI, ability to handle uploads, file-formats, etc. It’s also free (though the data is used for training.) My Talks page: https://sanand0.github.io/talks/. I give 1-1.5 talks a week, mostly on AI/ML topics. I use Marp to render Markdown slides and publish it here. Google Chat. It’s Straive’s social channel. I can’t use it from my phone, so I log in only if I need to check if I missed something. LinkedIn. It’s where I post by default. I don’t use it for networking and only connect with people I’ve met and know well. YouTube. Mostly for movie clips over dinner. I occasionally watch educational content. LLM Foundry: https://llmfoundry.straive.com/. LLM Foundry is Straive’s internal gateway to multiple model APIs (I built it). I use it to experiment with models, grab API keys, and demo LLMs to clients. Squoosh. I compress every image, every time. Mostly into WebP (hands-down the best format today), typically lossless with an 8-color palette, or lossy at ~0-10% quality for photos. The list will change. But the reasons probably won’t: fast, simple, automatable, and practical (for me). ...
There hasn’t been a box-office explosion like Dangal in the history of Bollywood. CPI inflation-adjusted to 2024, it is the only film in the ₹3,000 Cr club. 3 Idiots (2009) is the first member of the ₹1,000 Cr club (2024-inflation-adjusted). The hot streak was 2013-2017: each year, a film crossed that bar: Dhoom 3, PK, Bajrangi Bhaijaan, Dangal, Secret Superstar. Since then, we never saw such a release except in 2023 (Jawan, Pathan). ...
Here’s how I track trending GitHub repos each week. I run a scheduled script that saves a clean TSV I can scan fast. It uses uvx gtrending to fetch weekly trending repos for: Rust: High-quality system tools. (Anything in Rust seems cool.) Go: Reliable CLI/infra tools. (Like Rust, most Go code seems good.) Python: Most AI/ML stuff TypeScript: Most modern JS codebases JavaScript: Most front-end utilities Shell: Productivity scripts I pipe results through jq to extract: ...
I’ve started vibe shopping, i.e. using ChatGPT to shop for small, daily items and buying without verifying. For example: “A metal rack for the floor: at least 2 ft * 1 ft * 2 ft, small gaps, popular options on Amazon.in.” https://chatgpt.com/share/68d61d68-7040-800c-936b-354749539308 “An optical wired mouse that’s smaller than usual, 4*+, popular, Prime-eligible for Chennai by the weekend on Amazon.in.” https://chatgpt.com/share/68d61e0d-420c-800c-bc71-821b9f9296a9 The best use is when I don’t know the right terms. In this case, the terms were wire rack and mini mouse. ...
Tools in Data Science Sep 2025 edition is live: https://tds.s-anand.net/. Major update: a new AI-Coding section and fresh projects. I teach TDS at the Indian Institute of Technology, Madras as part of the BS in Data Science. Anyone can audit. The course is public. You can read the content and practice assessments. I fed the May 2025 term student feedback into The Sales Mind and asked: What are the top non-intuitive / surprising inferences? What are interesting observations? What are high impact actions? Full analysis: https://chatgpt.com/share/68cba081-afc0-800c-9da3-75222e84a499: summary, outliers, and action ideas. ...
Here are the 10 most frequent sites I use (based on Microsoft Edge’s home bar): ChatGPT. It replaced Google as my default knowledge source. I prefer it over Gemini, Claude, etc. because the app has good features (memory from past conversations, code interpreter, strong voice mode, remote MCP on web app, etc.) The OpenAI models have pros and cons, but the app features are ahead of competition. Gmail. It’s my work inbox. Interestingly, I check it more (and respond faster) than social channels (e.g. WhatsApp, Google Chat, LinkedIn). It also doubles up as my task queue. Prime Video. I mainly watch The Mentalist. Totally love Patrick Jane! Google AI Studio. Mostly for transcription. It’s better than Gemini on UI, ability to handle uploads, file-formats, etc. It’s also free (though the data is used for training.) My Talks page. I give 1-1.5 talks a week, mostly on AI/ML topics. I use Marp to render Markdown slides and publish it here. Google Chat. It’s Straive’s social channel. I can’t use it from my phone, so I log in only if I need to check if I missed something. LinkedIn. It’s where I post by default. I don’t use it for networking and only connect with people I’ve met and know well. YouTube. Mostly for movie clips over dinner. I occasionally watch educational content. Playground. LLM Foundry is Straive’s internal gateway to multiple model APIs (I built it). I use it to experiment with models, grab API keys, and demo LLMs to clients. Squoosh. I compress every image, every time. Mostly into WebP (hands-down the best format today), typically lossless with an 8-color palette, or lossy at ~0-10% quality for photos. That’s my current home row. It will change. But the reasons probably won’t: fast, simple, automatable, and practical (for me).
In Feb 2025 at PyConf Hyderabad, I tried a new slide format: command-line slideshows in bash. I’ve used this format in more talks since then: LLMs in the CLI, PyCon Singapore, Jun 2025 Agents in the CLI, Singapore Python User Group, Jul 2025 DuckDB is the new Pandas, PyCon India, Sep 2025 It’s my favorite format. I can demo code without breaking the presentation flow. It also draws interest. My setup was the top question in my PyCon talk. ...
25 years ago, Mr. Krishnan (IAS) amused us with anecdotes of bureaucrats writing meeting minutes before the meeting. This week, I flipped that. I wrote slides after the talk. I call them AfterSlides. Why. I ran a couple of Ask-Me-Anything (AMA) sessions where the audience set the agenda. I learned their interests. They got answers. No slides prepared. How. I okayed recording with the organizers, recorded on my phone, transcribed with Gemini, and asked ChatGPT to generate the AfterSlides. ...