S Anand

Recently, I’ve re-used my own writing / transcripts as context to LLMs. For example, I’ve used: My meeting transcripts to answer interview questions My blog posts to write news articles My chat history to extract AI-related advice This repurposing can be used for so many things. For example, before delivering a talk to journalists “Review my Feb 2026 LLM posts and generate a single-sentence, ELI15 high-impact use case for journalists.” gets me list of use cases. Now, all I have to do is show what I did and share how it’s relevant for them, like: ...

Our brains remember some things better. Explaining that way makes it stick. Here are the eight things, most important first, that help you: Structure explanations memorably: Face. You remember faces before facts. So cast characters: “Imagine you’re a courier carrying a packet.” Prefer archetypes to real names — less baggage, more imagination. Place. You’re reading down a list now — and the top feels more important. That’s spatial wiring. Turn any concept into a map. Use higher, deeper, nearer, inside, … Tale. You read #1 and #2 first because they came first. Your brain built a cause from that sequence. Time creates cause for free. “Because” makes anything believable. Scale. “Two feet tall” lands instantly. “60 cm” forces you to convert. Your brain doesn’t measure — it compares. Give it reference objects, not just numbers. Deliver explanations memorably: ...

Priyanka was ghost-writing an interview request from PC Quest for Ankor. Two questions were a bit technical: Straive combines data engineering, analytics, AI, and content services. At a technical level, how are enterprises stitching these capabilities together architecturally and operationally when addressing complex business problems at scale? GenAI systems tend to behave unpredictably when exposed to real workloads. What engineering patterns, monitoring approaches, or runtime safeguards are becoming essential to maintain reliability, performance, and cost control in production settings? … and she asked if I could review. ...

In Feb 2024, Claude 3 Opus was the best model, at $15/MTok. In Jul 2024, GPT 4o Mini reached that quality at 10% of the price. In Dec 2024, DeepSeek v3 reached that quality at 1% of the price. Video See the interactive version If the price continues to fall 10x every 11-12 months or so (and it has been), then in a year, a Claude 4.6 Opus like model will cost 1/10th of the $5/MTok today, and in 2 years, 1/100th of that. ...

I got an email from Google Cloud on my work account “excited to introduce you to Gemini Enterprise”. Once I signed up, it said, “you have 30 days to try Gemini Enterprise – Business edition at no cost.” After that, it costs US $21/user/month, which I can subscribe to here. The main differences from Gemini Pro (consumer accounts) seem to be: Data Privacy. Google won’t read or use your data to train. (In Pro, you need to turn it off explicitly. Here, it’s the default.) Admin Controls. Admins can turn off connectors, manage users, retention policies, etc. Copyright Indemnification. If AI infringes copyright and you get sued, Google will find the case. But if you’re using Gemini via your Google Workspace account (i.e. your work account already has Pro subscription), then it makes no difference - it’s all the same. ...

High Scepticism + High Humility = Scientist. Editor. Indecisive. “Let’s test it.” Good for high-stakes, irreversible decisions. System 2 thinking is slow and effortful. But if you do this too often or too long, you miss the window or other opportunities. High Scepticism + Low Humility = Critic. Troll. Red Hat. “You are wrong.” Good for stress-testing and auditing. To prevent/anticipate failures. But it’s toxic and demoralizing if you do it too much. ...

I have a bad memory. (I need to write about that. I keep forgetting to.) It’s worsening. Yesterday, I misplaced my debit card for the first time. Or maybe the second…? Which reminds me, I just forgot a call I have now! (Panic.) (15 min later.) So, anyway, therefore, I log stuff meticulously. Like what I did each day, what I ate, what I weigh, what pained me, etc. But the best logging is automated. My phone logs where I am. My bank logs what I spend. My calendar logs who I meet. ...

You can use AI to submit not just talk proposals but entire articles from your past work. Ranjeeta said Built In wants an article and had written one on my behalf. If someone’s going to write for me, I’d rather pick an AI! So here’s what I did: Research the audience So I asked Gemini to research and suggest topics: I received a request to write an article for Built In (https://builtin.com/), an online community and publication for startups and tech companies. ...

Developing taste & judgement are an essential skill in the AI era. # # But taste is different from knowledge and takes more time. Gaining knowledge is a software upgrade. It strengthens existing synapses. It’s fast, reversible, no new “cables” required. Taste is a hardware upgrade. It destroys inefficient pathways, grows neurons for new pathways, and wraps axons with myelin speeding up signals 100x. (London cab drivers literally have a larger hippocampus.) Taste takes time. How we acquire taste depends on the environment. ...

10:20 am. After submitting my VizChitra 2026 talk proposal, did a quick analysis of the submissions. Copy the HTML from the submissions page and paste into Gemini. Ask it: “Given this HTML, share a JS snippet I can copy and paste into DevTools that will return an array of objects containing all the useful information about each submission.” Paste the JS snippet into DevTools and get the structured result. Here’s the breakdown of submissions (excluding exchibitions): ...