2026 16

What to do less because of AI

Some ideas on what we can do less, thanks to AI. Why? Because less is more and we keep getting advice on what to do more of, not what to do less of. Skip meetings you don’t speak in. Agents can summarize the transcript. Stop taking notes. Agents can summarize a recording. Stop reading group chats. Agents can summarize WhatsApp groups, Hacker News, Twitter, and more. Stop translations. Agents translate on the fly. For you, and your audience. Stop weekly status reports. Agents can tell you (and your manager and team) the status. Stop building dashboards. Agents tell you “what’s wrong” or “what’s next” directly. Stop building software at first. Tell the agent to do the work. Let it write software if needed. Save it if you use it often. Stop writing requirements. Agents can prototype. Test if that’s what you need, first. Stop teaching coding. Agents can code. Teach people to use agents. Also - a few things that were true pre-AI: ...

Things I Learned - 16 Aug 2026

This week, I learned: psub is a neat fish option to treat command outputs like file inputs. E.g. diff (sort a.txt | psub) (sort b.txt | psub) More anchor points on how much text to ask AI for: … in 200-300 words (about 1 book page) … in ~1 A4 sheet (~500 words) … in ~3 minute of conversational Grade 8 reading (~500 words) I usually log things in a single file rather than split things into yearly, monthly, etc. A single file is more portable, scannable, and, for human logs, gives a feeling of accomplishment. I split when the file gets so unwieldy that it actually hurts - which is a good thing because it means I’m actually using it (maybe?) - and splitting beforehand may be good planning but is also premature optimization, adding friction to a nascent, fragile process. (This idea is pretty generalizable.) Claude models launched after 2 Aug 2026 “weaves an imperceptible watermark directly into the text itself. You won’t see it, and it doesn’t change the meaning, quality, or readability of Claude’s response.” How Claude marks AI-generated content. VS Code has built-in dictation. It uses nemotron-3.5-asr-streaming-0.6b by default #ForNow, and it’s pretty good. I expect I’ll use it a lot more, since most of my typing is in VS Code anyway. Ctrl + Alt + V toggles dictation. Dictation is also supported in the terminal and is trained to recogni I had an interesting moment today when I asked ChatGPT to identify which of my ChatGPT conversations were the most effective. I gave it access to my computer and it started using the browser to scrape itself so aggressively that I stopped it from it banned itself! GeoLibre looks like a full-fledged GIS. It’s open source and runs directly in the browser. When installing tools with mise, if it messes up the platform, you can explicitly specify it. For example: mise use -g 'github:pranshuparmar/witr[asset_pattern=witr-linux-amd64,bin=witr]@latest'. Mise Docs I saw this snippet from Claude Code: await Promise.race([document.fonts.ready, new Promise((r) => setTimeout(r, 3000))]); That waits for up to 3 seconds for the fonts to load. Didn’t know about Promise.race() before. It’s different from Promise.any() in that .race() will return the first result while .any() will return the first success. Measure the verification / follow-up tax in your AI work. AI does things fast. You have to take the next step. It helps to tag items with how long they’d take to verify or action. We do for specification, because we have to do that now, before telling AI. But I typically ignore the deferred tax. A theme is emerging: “Human attention needs reciprocity. If you ask for someone’s attention, first demonstrate your own effort.” Example: “people really don’t like when a coworker’s chatgpt contacts them asking for help with a task, even when they’d be perfectly happy doing that same work if asked by that coworker.” Greg Brockman

LinkedIn Blog

Pick next month's LinkedIn posts from my blog. - Blog: ~/code/blog/posts/YYYY/\*.md (frontmatter: title, date, categories, tags, description, and `linkedin:` if already posted) - LinkedIn dump: ~/Documents/data/linkedin-posts.jsonl (type=post and type=comment; posts have impressionCount, reactionCount, commentCount, repostCount, postedText as a RELATIVE age like "2mo") Based on a Jul 2026 analysis of 169 posts + LinkedIn metrics: - Audience: ~750 founder/CEO/CTO/chief titles, ~570 engineers and data scientists, ~280 product. India and Singapore heavy. They read for a decision they can act on or a story they recognise. - My top posts have a reach (vs a typical post that month) of: 1. 8.6x - Everyday observation with a twist. Specific, visual, slightly absurd, mild grievance welcome. E.g. Plastic-cover-on-phone 185K, no-entry-for-sandals 47K, kind-air-hostess 36K, hot-cookies 27K. 2. 14-87x - A number that flips a default decision. "GPU or API" 663K, "which LLM gets better grades" 64K. Ensure a concrete decision. 3. 34x - A free thing usable today. TDS-free 285K, 60 reposts. 4. 4-12x - Exact, reproducible "here's how I did it". Voice-to-slides 93K. What loses: prompt-engineering 0.63x, vibe-coding 0.72x, coding 0.80x, ai-agents 0.79x, llms 0.89x. Workshop recaps get 1,700-2,700. Under 250 words gets a median 8,020 impressions; over 900 words gets 5,303. Pure data analyses (IMF, Wikipedia) get respectable but modest numbers unless they carry personal stakes or an actionable consequence. Reposts (save intent) run highest on benchmarking (7.0 avg) and education (5.9), even when reach is modest. Treat reposts and comments as better signal than reactions. The 2026 baseline is roughly half of 2025 (~4,000 vs ~8,000 median), so don't compare raw impressions across years. I no longer link the blog on LinkedIn: link posts get throttled. So we'll rewrite. ## Method 1. Take blog posts from the last 3 months. 2. Drop any with a `linkedin:` field. Then DO NOT TRUST that field - it has false negatives. For every remaining candidate, keyword-check its distinctive terms (proper nouns, tool names, coined phrases) against BOTH post and comment text in the full dump. Report anything already live. Example of a real miss: "How IMF mis-forecasts GDP growth" had no frontmatter field but was posted a month earlier. 3. Note the dump's max scrapedAt. Anything dated after it is UNVERIFIABLE - say so rather than assuming it's unposted. 4. Clean the dump: discard records where reactionCount > impressionCount (a scraper bug inflates some counts by ~1e9). 5. Auto-exclude: "Things I Learned" digests, workshop and talk summaries, dev-tooling posts (ffmpeg, redirect tracking, shell utilities). These are the developer posts I deliberately keep off LinkedIn. 6. Score each candidate against the four winning patterns. Prefer posts already under 500 words. 7. Portfolio rule: at least 2 of 5 must be non-AI or non-LLM. My feed is already LLM-saturated and that category runs below my own baseline. ## Output - for each of 5 picks, in priority order - Title, date, word count, blog URL - Which pattern it hits, and the specific past post it resembles - A one-line LinkedIn hook, in my voice, that I can use as the opening line - What to cut for LinkedIn (name sections, not "shorten it") - Any risk (named company, staleness, tone) Then: 3 near-misses in one line each, and a list of what you excluded and why. 31 Jul 2026. Created. Sources: https://chatgpt.com/c/6a6ab214-fd78-83ec-b319-3f5645325155 https://claude.ai/chat/c3dd952f-1a20-44a2-8eb3-29860201d8ee Feedback loop - run this first each month ...

Daily Deeds

Help me answer: **"What did I REALLY accomplish?"** in the last 7 days until Saturday midnight (SGT). The aim isn't to produce a time log, activity report, exhaustive chronology, or list of completed tasks. It is to find out what really changed because of this week: in the world, in my trajectory, in other people, or in my sense of myself. Use @LocalMCP bash/read. Do not run Claude, Codex, Gemini, or other AI agents. I will update ~/Dropbox/notes/daily-deeds.md based on your output. ## What counts Look for state changes such as: - Something shipped, finished, adopted, decided, resolved, or stopped - Significant movement against one of my stated goals - A reusable asset, system, method, relationship, reputation, or capability that may compound - A conversation or introduction that opened an important new opportunity - A reaction - from me or someone else - that revealed impact or signficance - A changed belief, newly discovered principle, or invalidated assumption - A wrong direction killed, loss prevented, burden removed, or lingering loop closed - A personally significant first, act of courage, relationship moment, delight, surprise, or state of flow - Something small that future me may see as the beginning of something large Do not rank by time spent, apparent effort, number of meetings, seniority of people involved, prestige, or monetary value alone. One emotionally specific sentence in `daily-deeds.md` may matter more than twenty transcripts. Treat exact quotes, `:star:`, "wow," firsts, unusual behaviour, repeated later references, spontaneous delight, embarrassment, courage, and flow as strong (but not conclusive) personal importance signals. Do not invent undocumented events. Instead, generate specific memory prompts that may help me recall them. ## Sources and search procedure Search efficiently in two passes. ### Pass 1: Discover candidates Start with: - `~/Dropbox/notes/daily-deeds.md` - see what I record/skip/miss and how I write. - The current goals and status in `~/Dropbox/notes/goals-bucket-list.md` and `~/Dropbox/notes/@todo.md` and `~/code/blog/pages/skills/anand-objectives/SKILL.md` - Transcript filenames within the date window under `~/Dropbox/notes/transcripts/` - Emails via `gws` - both work ([email protected]) and personal ([email protected]) - WhatsApp messages via `~/Documents/data/whatsapp` - Dated completed and open entries in `~/Dropbox/notes/@todo.md` - Overlapping `~/Dropbox/notes/about/week-*.md` files, using them as leads rather than trusting their ranking - `~/code/talks/README.md` - `~/code/datastories/config.json` - `~/code/til/README.md` - `~/code/blog/description.md` - `~/code/README.md` - `~/code/llmdemos/config.json` Check file shapes and indexes before opening large files. Locate candidate files first, then read only relevant passages. Use calendar, email, chat, WhatsApp, browsing history, and repository history only through targeted date/name/topic searches to verify candidates or detect state changes. Do not dump or broadly scan archives. Browsing time and meeting duration are not accomplishments. Create a private raw list of roughly 20-40 possibilities before ranking. ### Pass 2: Verify and rank For the strongest possibilities, find direct `path:line` evidence where available. Judge each candidate separately on: - **State change:** What is now different? - **Goal movement:** Did it significantly advance an explicit or durable objective? - **Leverage:** Can it compound through an asset, person, system, method, or reputation? - **External evidence:** Did anyone adopt, approve, respond, quote, pay, publish, merge, invite, or change behaviour? - **Personal importance:** Are there signs that I may remember or value it unusually strongly? - **Durability:** Is it likely to matter three months from now? - **Counterfactual:** Would omitting change the week's story? Keep importance and evidence confidence separate. Small personal moments may be very important but low-confidence. Detailed meeting notes may be high-confidence but less important. There'll be plenty of work-related content. Balance by probing deeper for personal life signals (family, relationships, health, body, play, service, art, courage, joy, and unusual experiences). Include meaningful failures and closures - don't make the week look artificially successful. ## Output Keep the entire response reviewable in about two minutes. # What I may have REALLY accomplished ## Best current answer Write three concise bullets representing your best current interpretation of the week. Phrase them as changes, not activities. Prefer constructions such as: - "I proved that..." - "I moved ... from ... to ..." - "I created ... that can now..." - "I opened..." - "I stopped..." - "I discovered..." - "I experienced..." Do not simply say "I attended," "I worked on," "I discussed," or "I spent time." ## Candidate slate List up to 10 candidates, most significant first. For each: **1. Short candidate title** - Category: Outcome / Goal / Leverage / Seed / Learning / Closure / Moment - **What changed:** One sentence. - **Why it might matter:** One sentence explaining the possible long-term, goal, leverage, or personal significance. - **Evidence:** Concise `path:line` references. - **Your guess:** Importance: High / Medium / Wildcard. Evidence confidence: High / Medium / Low. Use **Wildcard** for something that might be deeply significant but whose importance cannot be inferred reliably. Do not fill all slots merely because they are available. ## What the record may have missed Ask at most three highly specific memory questions derived from the week's actual events. Good questions resemble: - "After the [specific event], was there one audience remark or private conversation you kept replaying?" - "During the trip to [place], did anything off-stage matter more than the scheduled event?" - "You had [specific demanding sequence]. Was there a moment of fear, courage, delight, embarrassment, connection, or flow that the records would not show?" Include: 1. One event-specific backstage or reaction prompt 2. One personal, relationship, body, play, or joy prompt 3. One quiet decision, failure, refusal, closure, or changed-belief prompt Do not ask generic questions such as "Anything else important?" ## Goal movement Mention only explicit goals that appear to have moved. Distinguish: - **Outcome movement:** the goal itself advanced - **Leading evidence:** behaviour or capability improved, but the goal did not necessarily advance - **No reliable evidence** Do not turn routine habit compliance into a headline unless something changed. ## Suggested `daily-deeds.md` additions Provide copy-ready lines for items that are important and absent or weakly recorded. Use this structure: `- Day YYYY-MM-DD. [What changed]. [Exact reaction, why it mattered, or what it may enable].` Preserve memorable exact words. ## Likely motion, not accomplishment Optionally list at most two items that consumed visible activity but did not appear to change anything important. Explain briefly why you excluded them. End with: `Reply with Keep: ... / Drop: ... / Missing: ... and I will turn this into the final weekly answer.`

Talk Event Scan

Run on ChatGPT, weekly. Run a weekly scan for events I should speak at or attend. Today's date and all action dates should use Singapore time. Read from @LocalMCP without modifying files. Give me registry changes that I can copy into: `~/Dropbox/notes/talk-event-list.tsv` ## Understand me first Read and apply, as relevant: - `~/Dropbox/notes/talk-event-list.tsv` - talk registry - `~/Dropbox/notes/talks.md` - talk ideas, proposals and preparation - `~/code/talks/README.md` and relevant talk transcripts - delivered talks and formats - my current calendars via `gws` - the `anand-objectives`, `reframe-question`, `expert-lens` and `blind-spot` skills - If required: `~/Dropbox/notes/people.md`, relevant `about/*.md`, and recent relevant transcripts - how I learn from and connect with people State which calendars and personal sources you successfully checked. ## Find events Search official event, CFP and registration pages for: - events occurring in the next 9 months; - CFPs open up to 12 months ahead. Prioritize Singapore, Chennai, Bangalore, Hyderabad, and remote events. Consider Mumbai, Delhi for valuable opportunities, other locations only for unusually valuable opportunities. Search beyond AI and technology events. Also find open trade-, domain- and function-specific events where AI creates a useful angle for that audience - for example education, journalism, design, publishing, government, HR, product, consulting, finance, healthcare, manufacturing, law, or investment. For a non-AI event, do not propose a generic "AI is transforming this field" talk. Identify a specific workflow, decision, risk, experiment or new capability that would matter to that audience and could produce an evidence-rich, useful session. Do not penalize an event because it requires new material. Expanding my portfolio of talks, experiments and relationships is part of the objective. Reward new material when it could become a reusable asset. ## Constraints I never pay to attend or speak. Use these cost values: - `free` - attendance is explicitly free; - `free_if_speaker` - accepted speakers receive free access; - `paid` - I would have to pay; - `unknown` - not verified. Do not recommend `paid` events. Recommend `free_if_speaker` events only for speaking. Keep high-value `unknown` events as watch items until cost is verified. Prefer open CFPs and public registration over invitation-only events. Remind me at a useful action date, normally: - 14-21 days before a CFP closes; - early enough to register before capacity or free places disappear; - immediately, if an important opportunity is discovered later than ideal. ## Rank by value Consider: - fit with my objectives and interests; - strength and specificity of the AI angle; - learning value; - relationship value and quality of likely participants; - opportunity to test an idea with an audience; - potential to create a reusable talk, experiment, benchmark, dataset, demo or relationship asset; - reach and credibility; - novelty relative to my existing audiences and portfolio; - openness and likelihood of acceptance; - calendar and travel fit; - preparation and travel effort; - commercial noise. Do not recommend an event merely because it is large, prestigious or contains "AI" in its title. Include at least one strong wildcard outside my usual communities when one exists. ## Use the registry to avoid repetition Read all existing registry rows before searching. Identify the same event using its existing `event_id`, canonical official URL, or normalized event name + year + city. Never create a duplicate row for another page belonging to the same event. Silently recheck relevant active events, but mention a previously registered event in the report only when: - its action date is now due; - a deadline, date, location, format, cost, availability or URL changed; - an unknown fact was resolved; - my calendar or travel fit materially changed; - new information materially changes its priority; - I explicitly need to reconsider it. Otherwise, suppress it completely. Do not change a registry row merely to record that it was checked again. Update it only when a material field, status, action or next-review date changes. Keep past events in the registry as history. Mark them `expired`, `attended` or `spoke`; do not delete them merely because they have passed. Add a researched event to the registry when it is: - worth recommending or watching; or - a plausible recurring candidate whose rejection should be remembered. Do not add obviously irrelevant search results. ## Registry schema Fields: - `event_id`: stable lowercase identifier such as `2026-containerdays-singapore`. Preserve it forever. - `event_name` - `organizer` - `start_date` - `end_date` - `city` - `country` - `format`: `in_person`, `online` or `hybrid`. - `event_type` - `domains`: short semicolon-separated terms. - `audience` - `official_url` - `cfp_url` - `cfp_deadline` - `registration_url` - `registration_deadline` - `cost_status` - `recommendation`: `speak`, `attend`, `both`, `watch` or `skip`. - `ai_angle` - `why_for_me` - `priority`: `1` highest through `5` lowest. - `status`: `discovered`, `watching`, `action_due`, `submitted`, `registered`, `invited`, `rejected`, `skip`, `expired`, `cancelled`, `attended` or `spoke`. - `next_action` - `action_due`: when I should act or be reminded - not necessarily the final deadline. - `next_review`: when the event should next be reconsidered if no action is currently due. - `first_seen`: preserve the original value. - `last_changed`: update only after a material change. - `confidence`: `high`, `medium` or `low`. - `notes` Rules: - Dates: `YYYY-MM-DD`; leave unknown dates blank. - Use only official canonical URLs where possible. - Fields must contain no tabs or line breaks. Use semicolons within fields. - Keep `ai_angle`, `why_for_me`, `next_action` and `notes` concise. ## Output ### 1. Recommended actions Show only events that are: - **NEW** - newly discovered and worth my attention; - **DUE** - action is timely now; - **CHANGED** - material facts or priority changed. Rank by value, not by deadline alone. Do not fill a quota. Return at most 10. For each, give: 1. Tag: **NEW**, **DUE** or **CHANGED** 2. Event, date, location and official link 3. **Speak**, **Attend**, **Both** or **Watch** 4. Exact next action and recommended action date 5. CFP or registration deadline, where applicable 6. Cost status 7. Why it matters specifically to me 8. A specific AI angle or session idea for this audience 9. Calendar and travel fit 10. Confidence For a **CHANGED** event, emphasize what changed rather than repeating its full earlier rationale. ### 2. Registry changes Output only the applicable sections: #### ADD Provide complete new rows without the header. I will append them. #### REPLACE Provide complete replacement rows without the header. Prefix each row outside the TSV block with the `event_id` it replaces, or group them in a TSV block whose first column is the existing `event_id`. I will replace the matching rows. #### DELETE List `event_id<TAB>reason`. Delete only duplicates, erroneous identities or rows merged into another event - not expired events. If a section has no changes, omit it. Never reproduce unchanged rows. ### 3. Scan summary Briefly state: - how many existing events were silently suppressed because nothing changed; - how many new events were investigated but rejected without registry entry; - important gaps, such as inaccessible calendars or unverified cost; - where the search may need broadening next week. If nothing deserves action, say so. Still provide registry changes when facts or statuses need updating. 23 Jul 2026: Created. Sources: https://chatgpt.com/c/6a61a82b-bc80-83ee-a02c-ab8f7e1db9dc

Email Reply

Answer the most recent email matching above. Draft the reply that I (Anand) would actually send - based mostly on things I said, decided, or did recently, adapted to this audience and situation. (Not a generic polished email that just resembles my writing.) Guardrails: - Work independently. If a missing fact would significantly change the decision, commitment, or risk AND cannot be found from the sources: - Ask one clarifying question to the recipient or recommend a "DISCUSS LIVE". - Ask me when neither is appropriate and proceeding without the fact could cause material harm. - Draft only. NEVER send or modify email. - Use @LocalMCP, the web, and the coding environment directly. - For external recipients, don't disclose what's not approved for them. 0. **Read relevant skills**: On Local MCP, find, read, and apply the relevant skills for the task. `~/code/scripts/agents/*/SKILL.md` - coding + thinking skills `~/code/blog/pages/skills/*/SKILL.md` - thinking skills 1. **Fetch and understand**: Use `gws` on Local MCP. Find the thread by subject + sender, read all of it (format=full, decode base64url bodies). Determine: - Have I already replied? Has the request changed? Did someone else answer? Is a reply still useful? Default target: the first email's substance, replied to the latest message that still needs something from me. - Read attachments that affect the reply (pdf/pptx skills). Render slides and pages visually when reviewing a visual artifact; extracted text is not enough. Follow Google Drive links that hold the actual material. - Identify: the literal questions; what the sender actually needs (answer, decision, approval, review, introduction, reassurance, cover); the deadline; any implied commitment for me, my org, or others; the useful question they did not ask. - Reframe: if required and appropriate, use reframe-question/SKILL.md and answer their INTENDED question. Research the sender for better context if required. 2. Choose the response mode: Substantive reply / brief ack / decision / introduction or delegation / one clarifying question / discuss live / follow-up / no reply. An email draft is not automatically the right output. Proportional effort: a confirmation stays simple; advice ends in a small experiment or decision, not a catalogue; artifact reviews inspect the artifact and give concrete changes. For strategy or broad advice, mention the (ambitious) end-state and the practical next step that leads to it. Do not expose research just because you performed it. 3. Retrieve my position: Search in widening rings; stop when new sources no longer change the reply: 1. The steer. 2. The thread, attachments, links. 3. My recent sent mail: same person, same project, similar questions (also my best style anchor - imitate 3-5 replies of the same type). 4. For project/client work, use gws (Google Drive). Search filenames, then full text; maybe broaden thereafter. Prefer recent files (<90d). Read only most likely authoritative files. 5. `~/Dropbox/notes/questions-i-am-asked.md` (newest first) 6. `~/Dropbox/notes/transcripts/YYYY-MM-DD*.md` near the email date or with the sender 7. `~/code/blog/description.md`, `~/code/til/README.md`, `~/code/talks/README.md` (find the piece, then read it); `~/Dropbox/notes/about/{Sender}.md` if present 8. The web, only for current external facts (prices, models, dates, roles). When sources conflict, prefer the more authoritative and recent, direct, situation-specific one. Infer the underlying position; don't copy old wording mechanically. My emails and transcripts are evidence of my POSITION, not proof a FACT is true. Verify changing facts against primary sources online. ALWAYS read and follow the anand-writing-style, anand-objectives, verification-gate skills. Use blind-spot, expert-lens, evidence-provenance for strategy or reviews. 4. Draft: - "Hi {FirstName}" ... body ... "Regards" or "Thanks" + "Anand", whichever fits. - Minimize my commitments ("I can help review X", "happy to join one call"). Never invent commitments, owners, timelines, cc additions, links, or facts; if one seems useful, put it under Judgment calls, not in the draft. - Prefer the minimal experiment over the survey: one model, one workflow, one next step, plus "If that's not quite what you need, we can discuss alternatives." - In reviews, separate: confirmed facts / my recommendation / still to decide. - Write based on the recipients' current situation. What do they currently know, understand, and believe? The email should be clear from their perspective, without the benefit of the context I have. - Warmth and humor only where the existing relationship supports it. - Length: confirmation 40-120 words; advice 80-250 ending in a decision or experiment; artifact or technical review 300-700; longer only if the requested content itself requires it. - Plain ASCII. No em-dashes, emojis, corporate filler, inflated praise, or polished LLM-style conclusions. Tentative where evidence is tentative: "Maybe try X?" Say plainly what I don't know. 5. Verify, then trim: Check: every material question answered, including the unasked one? Facts and links verified at primary sources? Any invented commitment, owner, or certainty? Any unintended commitment, precedent, exclusion, ownership/staffing/budget/access expectation, or stakeholder consequence if this is acted on or forwarded? Contradicts anything I said recently? Leaks private context? Longer than I would write? Phrases I would not use? Compare against recent sent replies to the same person or topic. Then cut anything that does not change what the recipient understands or does next. Output: Recommendation: REPLY / REPLY BRIEFLY / DISCUSS LIVE / FOLLOW UP / NO REPLY Status: pending or already replied (with date if replied) Draft: <ready-to-paste body only> Why: up to 3 bullets on the decisive choices Process: bulleted reasoning steps including hypotheses considered, alternatives rejected, why searches widened or narrowed, branches followed or abandoned, why retrieval stopped. List meaningful sources and retrieval steps used (if any) in the step: `query, command, or action -> findings (citing exact file:line, message id, or URL)`. Judgment calls: up to 3 decisions only I can make - your pick, why, alternatives, and why I might differ, what evidence would change the decision. Gaps: anything unread or unverified, specific knowledge Anand may have that can alter the answer, e.g. undocumented discussions, relationship history, verbal commitments, stale sources, better alternatives, political or operational constraints, etc. 11 Aug 2026. Updated to cover clarifying questions and second-order effects: https://chatgpt.com/c/6a7b0370-7030-83ee-a3de-9a12cdad3c3f 23 Jul 2026. Updated based on Ask AI initiative feedback: https://chatgpt.com/c/6a61b1f7-9580-83e8-a4e1-7e88a16538e1 17 Jul 2026. Created. Sources: https://claude.ai/chat/86b76a7f-2b62-42e5-82c7-a2474c8dd23e https://chatgpt.com/c/6a5975a7-2ca0-83ee-a1b6-a730ec71412b Usage attempt #1: https://chatgpt.com/c/6a5986bf-13d0-83e8-b460-5ecb0360bb84

IIM Alumni AI Workflows Workshop

The theme of yesterday’s workshop for the IIM Alumni at Singapore was Tools and Workflows was: Agents are getting smarter, so they know what to do. Tools agents can use are growing and are more powerful. This combinatorial explosion creates explosive possibilites. This workshop covered the following six workflows: Leverage transcripts. Use Google AI Studio to transcribe non-sensitive recordings with a reusable “don’t miss anything” prompt. AI Studio’s record button is a ready-to-use transcriber. Simplify dense text as a comic, an infographic, a story. Image generation is now a tool call an agent runs for you. Then compress it as AVIF on Squoosh before you email it to a thousand people. Verify - cheaply. Paste one suffix: “Break this into key claims, mark certainty, flag the five highest-risk ones, and tell me how to verify or falsify each.” Convert to a skill to automate. Cross-checking with multiple models took error from 14% to 0.7%. Skills are assets. A skill tells the agent “here’s how I do stuff.” Build them slowly, edit them weekly, and they compound for years. No skills support in your tool? Keep them as copy-pasteable prompts. Brainstorm by forcing range. Ban the five obvious ideas; borrow from unrelated domains; smash two random concepts together with the Ideator. Hallucination is a feature when you’re being creative. Schedule tasks. Weekly regulatory scans, daily meeting prep, market briefings - and even an “unreasonable gesture” nudge. As AI hides the tech, human relationships gain value. Here’s the talk video and full story + transcript. ...

Things I Learned - 21 Jun 2026

This week, I learned: It doesn’t always take time to learn or convey things. (Early trust can be built instantly, e.g. vulnerability.) At first, experts don’t know how to make skills explicit. But trainer effort could compress 10X via evals, practice loops, and feedback. Learner elapsed time would compress less. Everyone has something worth discovering, but not every conversation is worth my time right now. So, meet new people with trust, attention, and good questions. Continue if there’s emotional / intellectual stimulation (surprising, interesting, moving, connecting, energizing, challenging), else exit warmly with respect. To avoid getting overwhelmed in ultra-interesting conversations, mental closure helps. During the conversation, pause, name, reflect, and close. “Wait, you’re saying X. I should do Y. I’ll reflect/act tonight.” or “Wow, let’s sit with that for 5 seconds. You mean X. I feel Y. I’ll drop.” After the conversation, summarize: “What struck me were X1, X2. I’ll plan Y1, Y2 and drop Z1, Z2.” Then take a short break. Setting "markdown.editor.updateLinksOnPaste.enabled": false might fix the delay / freezing (infinite spinner) issue when pasting Markdown in VS Code. The bottleneck to quality of AI output has shifted from model quality to harness quality (and this is not obvious to many people). It is important, therefore, to optimize harness usage rather than prompts usage, i.e. harness engineering over context engineering. I use ug --smart-case --bool -Q --sort=rtime to interactively search for text in files. It’s like VS Code search-across-files. Here are the shortcuts I find useful: Alt-g: Glob (filter files to search in) Alt-[ or ]: Decrease or increase context (lines before / after) Alt-w: Word match toggle Alt-c: Count lines toggle Alt-u: Ungroup - show lines once even if multiple matches Using AI for health seems to have reached a tipping point. Three people have pitched an idea in this space to me in the last three days. One is a managed personal health provider who wants to tie-up with hospitals to gather data to improve AI health advice. Second is an enterpreneur who wants to enable the Indian Govt to use AI to improve public health - given the low proportion of trained doctors in public hospitals. The third is a colleague who is uploading personal health reports, fitness data, DNA data, wearable data, etc. and suggest daily habits such as fitness, nutrition, sleep, medication, etc. to optimize health. Changing the topic (e.g. asking a question) instead of answering a question is powerful. It lets you decline requests, avoid sensitive topics, ignore boring ones, learn rather than teach, and bring in your agenda - all at one shot. I need to un-practice my 40-year habit of answering questions. (This is selfish. I forgive myself.) bolt.diy seems like a browser-embeddable coding agent. That is, you can add bolt.diy to your web page and have it build apps. That might be a pretty powerful upgrade to generative UI - where pages build themselves based on the user input. Codex has a few new features in the last few months. Codex can generate images and have voice conversations. /goal sets an overall session goal to avoid getting side-tracked. /side is like Claude Code’s /btw - for a side task while the main task continues. /resume lets you switch to any previous session. /keymap debug lets you edit the keymap and inspect what keystrokes the terminal sends. @ lets you mention files, directories, skills, and plugins. Ctrl+R works, lets you pick a previous prompt. Ctrl+O copies the last answer as Markdown. Hooks are stable. PreToolUse lets you log every tool, SessionStart lets you inject repo-specific rules. MCPs with readOnlyHint can run in parallel. codex doctor diagnoses environment issues. codex remote-control lets you remotely control Codex, making it a server. Codex Python SDK is better and you can have Codex run as a back-end more smoothly. To change others’ behavior, embody (not preach) it visibly and consistently, make it easy to copy, and ask without forcing. It takes time, though. ChatGPT Governance is how groups keep promises when things (people, incentives, environment, pressure) change. A simple way to explain what governance is to someone who doesn’t understand why governance matters, and guide on when it does not matter. Forward Deployed Engineers are the next evolution of data scientists, IMHO. AI can do data science. Data scientists will likely act as the “Human As An Interface” (HaaI) to business, proactively identifying and solving problems - a space business analysts traditionally occupied. Of course, business analysts will likely do the same without needing data scientists to help. But since AI replaces data scientists more than business analysis, I expect that the % of data scientists who become FDEs will be higher than business analysts. The value of data exported from software is high. For example, your email, social posts, CRM / HRMS / ERP dumps, service tickets, purchases, notes etc. These let you create a personal / organizational digital brain. Hence proprietary solutions will make exports harder and open solutions will emerge. To live-preview any publicly accessible Excel file, you can embed or link to https://view.officeapps.live.com/op/embed.aspx?src=YOUR-URL The Codex app can now use the browser much better and faster since last week if you enable “Dev mode” OpenAI. THis uses CDP - which is more efficient than screenshots - and is something Codex CLI has been doing for many months. In Codex, Claude Code, etc. you can submit a prompt while the agent is working to steer it, i.e. after it completes a turn (e.g. a tool call) it will factor in the prompt. You can also queue it. Neither of these is available on ChatGPT or Claude.ai, though it’s such an important feature. On ChatGPT, submitting another prompt stops the previous run and the agent continues with the new prompt. By default, git uses ~/.config/git/ignore or %USERPROFILE%\git\ignore as the global .gitignore. You can override that with git config --global core.excludesFile PATH. StackOverflow

Meeting Preparation

Help me prepare for my meeting. For first-time meetings: - What should I explore? Research them and suggest what I might ask / learn / leverage. Begin with a - How can I help? Research them and suggest what I might share that's helpful / interesting to them from my work or public news, find the intersection, share the top matches. For follow-up meetings, list: - What's pending or would have happened since that I should ask about? Check past transcripts, emails, calendars, chats, etc. Prioritize most recent interactions. Older than 1 week is likely stale. - What'd be helpful / interesting for them that I should share? Research their personality, questions, needs, preferences, etc. (`~/Dropbox/notes/{about,transcripts}/`, emails, chats, WhatsApp, public news, etc.) Remember: people play multiple roles / personas that change over time. Research my recent work and public news since our last meeting. Find the intersection, share the top matches. - What should I explore? Research what they've shared that's helpful / interesting to me in the past (and public news if applicable). Suggest what I might ask / learn / leverage. Rules: - Use @LocalMCP - Where relevant, begin with a personal follow-up, a noteworthy trait/comment to remark upon, ... something that makes them feel understood in the first minute - Use the calendar invite for context. But also dig deep to discover the REAL agenda, not just the stated one from the calendar - Encode how I behave with them, they behave with me - Write in VERY simple, conversational language

Things I Learned - 10 May 2026

This week, I learned: I’m experimenting with Tauon MusicBox as an alternative to VLC as a music player. Update: 01 Jun 2026. I switched back to VLC. Tauon Music Box is glitch. It stops songs mid-way and doesn’t play automatically when launched. xz is pretty slow by default. xz -T0 uses all available threads and speeds it up ~3X. Enabling “Performance mode” (over a power-saver mode) produces a further speed-up of ~2X for me. For a 200MB file, that reduces the time from ~1 minute to 10 seconds. Notes from Simon Willison’s notes from the Claude Code event: “Design for the next model”. Build things that don’t quite work today on the assumption that they’ll start working with a model upgrade in the future. “The advisor strategy”. Instead of using a smarter model to plan, use smaller models to ask Opus for advice-on-demand. Dreaming looks really interesting. You can run a task over night which examines previous sessions and creates new memories. A routine is a saved Claude Code configuration: a prompt, one or more repositories, and a set of connectors, packaged once and run automatically. Routines execute on Anthropic-managed cloud infrastructure, so they keep working when your laptop is closed. Overheard: “VCs say, ‘OpenAI wants to get into commerce, so why are you getting into commerce?’ A few weeks later, ‘OpenAI no longer wants to get into commerce, so why are you?” Delightful discovery of the day: Super + Shift + Arrow keys to move windows between monitors on Ubuntu. television is a fast, portable fuzzy finder. Like fzf but faster, useful for files, text, git repos, docker images, etc. I added approvals_reviewer = "auto_review" to my ~/.codex/config.toml. This enables auto review which uses an LLM to figure out whether to ask a human to approve or not. It’s a lot less intrusive than asking every time. Not perfectly safe, though. Copilot supports a /chronicle command that suggest tips and improvements when using Copilot. It’s like /insights on Claude Code and Carbonyl is a CLI Chromium browser. Sort of like Lynx, but supports audio/video, JavaScript, even WASM, etc. This was the author’s first Rust project. I tried Zed as an alternative to VS Code. It’s fast and lightweight, but lacks the ecosystem of VS Code. Plugins are harder to build and Markdown support is weak. I would use it on a flight to save power, not otherwise. This is similar to others’ experience. ChatGPT UPDATE 05 Jun 2026. It DOES use some battery power - more than I’d like. I am uninstalling it. LocalSend is a pretty quick way to share files between phone and laptop even if you don’t have a network - if you connect the laptop to the phone hotspot. GNOME Network Displays works pretty well if you want to screencast your screen to a network display - e.g. a Smart TV with Miracast or Chromecast support. I’m evaluating rtk - a CLI proxy to reduce tokens. For example rtk ls or rtk git status shows agent-friendly compact output. I just added one like to my AGENTS.md: “Always prefix shell commands with rtk. Examples: rtk git status, rtk pytest -q, etc.” instead of using rtk init -g. I am testing it out, so I don’t know the impact, but it seems harmless. (Based on 2 days’ usage, across 216 commands, it saved ~50% of 37K tokens. Not much, but harmless.) The emerging convention to mark a section of HTML / Markdown as AI generated content is to wrap it in: <section ai-disclosure="ai-generated" data-ai-model="claude-sonnet-4.6" data-ai-provider="Anthropic"> (W3C AI Content Disclosure Community Group).

Flight Mode Emotions

At Changi Airport, I arrived 2.5 hours early and was worried that the flight was boarding on time - because I wanted to charge my laptop so it would work longer on a 6-hour flight to Delhi. I was also sad that it was only a 6-hour flight Delhi - it won’t be enough to read all my pending reading material. The only time I get to read stuff (instead of vibe-coding) is on a flight, with no WiFi. ...

Time bound recurring meetings

Whenever “let’s set up a recurring meeting” comes up (from me or others), I add: “We’ll set it up 4 sessions and then finalize the cadence.” Why? Most recurring meetings are about: I want to do something Not sure what But I really want it, like long-term And I my future self might not follow through So my present self is going to force my future self with a long-term commitment But during the recurring meetings, my future self is usually asking: ...

Career Advice

My answers to career advice people have asked me. Should I go deep or broad in my career? Early in your career, sample actively, i.e. go broad. Commit to depth when process (not just outcomes) energizes you. Read Range (David Epstein, 2019). ...

Favorite things

Some things have a disproportionate ability to delight me. Spare underwear. Spare anything everywhere Long battery life Extra monitor everywhere Food. I’m not picky about WHAT food, but… LEFTOVER food I can scrape GIFT chocolates or dry fruits! Fasting - makes routine food tastier Lower weight. Feels good daily Kids. Eternal fun and joy Tech of almost any kind, but… Internet access LLMs Power sockets Warm people to be wrapped around Fantastic fiction Money! So much you don’t have to worry Pain killers after a tooth or ear ache Headphones that work well. Good audio in general

Chrome Enterprise Premium access

Straive turned on Chrome Enterprise Premium on my browser. This means: No extensions or DevTools. No downloading, copying, or printing (of work stuff). No incognito mode. Every page, text pasted, file attached, is sent to the admin. Since Edge is my primary browser, I now open Chrome for office work only when needed. So, my guess is: I’ll check mail/chat less frequently. I’ll have fewer client documents to review. I’ll have fewer demos I can build. This might make me more productive - though it’s probably not what was intended.

Things I Learned - 18 Jan 2026

This week, I learned: Vulture is a neat library that funds unused Python code. uvx vulture script.py works fairly well, out-of-box. This helps when cleaning up AI-edited scripts that often have left-over code or imports. One of the lightest alternatives to Google Analytics is GoatCounter. If you just want page views, referrers, browsers, OSes, countries, and devices, it’s great. It’s privacy-friendly (no cookies), open source, easy to self-host, free for small sites, and the data is exportable. The number of countries that allow visa-free entries to Indian passports is gently growing in Asia (Kazakhstan, Thailand, Sri Lanka, Malaysia, Iran, and Philippines). Lessons from performance books. Claude # # Summary: In early days, explore, sample. Then narrow based on interest & fit. Practice hard and persist. ⭐⭐⭐⭐ Range (David Epstein): In changing environments (rules shift, feedback is noisy/late), sample broadly, i.e. generalize. Specialization vs generalization Nobel laureates have more hobbies. Olympic athletes have less. Shift nurses have same hobbies as non-shift workers. Hobbies help expertise in some areas Rewarding ONLY what succeeds locks behavior, halts exploration. Vary / delay incentives. Reward AFTER figuring out what works. Reinforcement and rewards Maybe “orderly” people specialize and creative people generalize? So pick what aligns with personality? ⭐⭐⭐ Peak (Anders Ericsson & Robert Pool): Compounded practice at the edge of competence, with good immediate feedback, helps 14-26%. But talent (genetics, upbringing, brainpower) differentiates more the expert level. Slow, effortful practice (spaced recall, interleaving topics, self-testing) builds lasting knowledge - but looks inefficient and doesn’t help with exams. Learning and long-term retention “Easy” 10K hours don’t help. ⭐⭐ Grit (Angela Duckworth): predicts roughly the same as conscientiousness (18%). It predicts success in stable paths moderately (but brainpower, etc. matter too). But premature grit hurts. Quit if it helps. But environment can defeat grit. Lessons from attention economy books. Claude # # The attention economy is real. It is designed to capture our mind, and it is winning. Distractions hurt MUCH more than we think. Batching, focus time helps. Privilege helps. The rich have more control over these than the poor do. ⭐⭐⭐⭐ Deep Work (Cal Newport, 2016) and ⭐⭐⭐ Digital Minimalism (Cal Newport, 2019): control the tools. Focus time, digital detox, embrace boredom. This helps - when you can afford to. ⭐⭐⭐ Indistractable (Nir Eyal): control yourself. The problem is internal (also true), so build habits, since willpower depletes (hm… not really). ⭐⭐⭐ How to Do Nothing (Jenny Odell, 2019): reject. Embrace boredom as resistance. This helps - when you can afford to. ⭐⭐ Stolen Focus (Johann Hari, 2022): regulate & rebel. The problem is systemic and external (also true). Reclaim your interface. BTW: Goldfish have excellent attention spans and memory :-) Lessons from trauma books. Claude # # ⭐⭐⭐ The Body Keeps the Score (Bessel van der Kolk, 2014): trauma recall shuts down the speech area. Eye movement desensitization (EMDR) helps. So does CBT, despite what the book says. But does yoga (only a little) or neurofeedback (too little data)? ⭐⭐⭐ What Happened to You? (Bruce Perry & Oprah Winfrey, 2021): calming people down before talking. Strong connections help more than a therapist. ⭐⭐ The Myth of Normal (Gabor Maté, 2022): trauma causes cancer (no), autoimmunity (partly), ALS (?), etc. ⭐ It Didn’t Start with You (Mark Wolynn, 2016): maybe anxiety is epigenetic and heriditary? Unproven. Family Constellation Therapy is wrong ⭐⭐ My Grandmother’s Hands (Resmaa Menakem, 2017): maybe racism is a somatic (body) response to generational (epigenetic) trauma? Too little data ⭐⭐ No Bad Parts (Richard Schwartz): maybe we’re not one person but a collection of parts, and interviewing family systems (IFS) helps? Unclear ⭐⭐⭐ Maybe You Should Talk to Someone (Lori Gottlieb): our memory is unreliable and therapy is messy. Connection & compassion help Most of these are based on the contested Polyvagal Theory: the nervous system scans for danger before the mind can process it. But the specific claims of the theory are wrong and it makes no other falsifiable claims. The nervous system has hierarchical responses to threat. 🟢 Not unique to PVT Social connection regulates physiology. 🟢 Not unique to PVT Unconscious threat detection (neuroception). 🟡 Weak evidence Mamellian brain (ventral vagal system) is uniquely mammalian. 🔴 Lungfish have it Reptilian brain (dorsal vagal) “shutdown” causes dissociation. 🔴 No evidence RSA directly measures vagal tone. 🔴 Contested Reptiles are “asocial”. 🔴 Wrong Trauma causes body changes too. It’s not just the mind. Childhood trauma persists. Relationships (connection & compassion) help more than therapy What constitutes tax residency in India? For an Indian citizen, as I understand it (after 2 hours of research): If you were in India >= 182 days: Resident* Else, if you left India this year for employment: NRI. Else, if you are an Indian Citizen living abroad (visiting or not): If Indian Income <= ₹15 Lakhs: NRI. Else if you were in India >= 120 days AND >= 365 days in the last 4 years: RNOR. Else if you are not liable to tax in any other country: RNOR. Else, if you left India for non-employment (students, tourism) and were in India >= 60 days AND >= 365 days in the last 4 years: Resident* Else: NRI. If you ended up as a Resident* If you were NRI in 9 of the last 10 years OR in India <= 729 days in the last 7 years: RNOR Else: ROR (Resident & Ordinarily Resident). For all practical purposes, RNOR is like an NRI. You pay tax only on Indian income, not global income. It’s like a transition status for returning NRIs. AVIF compresses better than WebP and may be the “next big thing”. I will be switching for all future images. Squoosh remains my choice of compressor and Ezgif’s AVIF maker and GIF to AVIF are handy.

2025 10

My Year in 2025

Here’s the report card for my 2025 goals bingo. Domain Repeat Stretch New People 🟢 Better husband 🔴 Meet all first cousins 🟢 Interview 10 experts 🔴 Live with a stranger Education 🟢 50 books 🟢 Teach 5,000 students 🟢 Run a course only with AI Technology 🟢 20 data stories 🔴 LLM Foundry: 5K MaU 🟢 300 days of GitHub 🔴 Build a robot 🟢 Co-present with an AI Health 🟢 300 days of yoga 🔴 80 heart points/day 🔴 Bike 1,000 km 🟢 Vipassana Wealth 🔴 Buy low 🔴 Beat inflation 5% 🟢 Donate $10K 🔴 Fund a startup The “Education” and “Technology” rows have a BINGO! Repeat goals were easier than new goals were easier than strech goals (no surprise). 11/20 wins means I’m picking realistic and ambitious goals. ...

Things I Learned - 07 Dec 2025

This week, I learned: Pytest finally supports subtests in pytest 9.0.0+. Simon Willison From The Tim Ferriss Show: #837: How to Simplify Your Life in 2026 — New Tips from Derek Sivers, Seth Godin, and Martha Beck: Look for single decisions that remove hundreds of other decisions. Peter Drucker via Jim Collins. E.g. Work only on LLMs, no new books this year, … Derek Sivers: Simple is not easy. Interdependency is complexity. Assets are dependencies. Accumulating information, purchases, employees/helpers, relations, etc. adds dependency. That makes life harder, challenges identity. Interdependency may be desirable - but reduce it in specific areas, to specific extents, temporarily, etc. Question every assumption: “Do you really need it?” Here are some examples for me to try Derek Sivers has no monthly payments (including income) or receipts (no subscriptions) at all! His code has no external code dependencies at all, and is building a house from scratch. Seth Godin: Know WHO it (whatever you’re doing) is for. Focus ONLY on that audience. Did it matter to them? Ignore the bad feedback from the person it was never intended for. Never exceed a budget or deadline. When either runs out, you are done. Treat any Yes/No you say as FINAL. Skip meetings where a memo will suffice. Apparantly, nudges are not as effective as the book Nudge suggests. In fact, there seems to be no evidence for it if we adjust for publication bias (i.e. only publication-worthy stuff gets published.) The Behavioral Scientist # 71% of HTTP DDoS and 89% of network-layer—end in under 10 minutes. That’s too fast for any human or on-demand service to react. Legacy DDoS defenses have become obsolete. The most popular botnet, Aisuru, is pivoting to content scraping for AI projects. The vectors are cheap, insecure routers, e.g. from Indonesia. (Claude) This 5El AI Evaluation Workshop suggests 4 layers of evaluation for code: Syntactic Evaluation: Does it compile? Semantic Evaluation: Does it do what a good analyst / programmer would? Business Logic Evaluation: Does it do what a good business analyst / manager would? Human Alignment Evaluation: Does it do what a good coach / leader would? Julia Evans shares an ultra-clear explanation of the Git data model. What I learnt is that: Gathering feedback on docs (“What’s confusing? Any questions? What’s missing? Or wrong?”) for evidence-based updates. Julia Evans Git stores entire files each version, not diffs. Diffs are computed on the fly. Each commit has an author (who writes the code) and a committer (who checks it in). #TODO Why two fields? Branches and tags are both references to a commit. But branches are updated on commit, tags are not. The staging area is a separate data structure, the index. #TODO Why a different data structure? The reflog tracks all local “activity”. E.g. git reflog --date=iso To fuzzy-match 2 columns of text (e.g. customer names, product names, …) you need 2 things: A text matching algorithm (rapidfuzz, fuzzball, …) and/or semantic matching (e.g. embedding similarity) for pairwise similarity An assignment algorithm (e.g. Jonker-Volgenant, Hungarian, …) for 1-to-1 matches in JS or Python, WhatsApp backups on Google Drive can’t be downloaded, even if they’re unencrypted. ChatGPT. OpenAI finds that confessions as a training method reduces scheming, reward hacking, etc. It can be applied to models even now. This can (less effectively) be applied at inference time as well: Sample confession prompt: Did you fully address both the letter AND spirit of my question? List any shortcuts taken, corners cut, or ways you optimized for appearing correct rather than being correct. What did I actually want vs what you provided? Agents4Science is a Stanford conference where AI co-authored papers are co-reviewed by AI and selected for presentation. Video Buddha seems more a philosopher like Socrates (“Question what I say”) than a religious leader. # How did he spawn a religion? Interesting that both were within a few centuries of each other. Coincidence? Were there more like them around the same time? At other times? Some more new CLI tools I installed: fx: CLI JSON viewer. Sort of like less for JSON. Fast, intuitive. mdq: Markdown query tool YTScribe is yet another YouTube transcription service. Note to self, since I keep forgetting this: On Android Edge, select the new tab page, click on the 3 dots at the top right, and select “Recent tabs” to see tabs from other devices. edge://recent-tabs When evaluating an LLM’s biases or natural preferences, set temperature=1 for a representative logprob distribution. LLM Bias My ideal AI coding cycle looks like this: (Research, Prototype, repeat), Plan, (Code, Run, Test, Fix, repeat), Refactor, Post-mortem, Document. The AI coding trap is a very clear explanation of AI coding vs vibe coding. It visually explains how coding agents shrink coding time, not thinking / fixing time; how delegating with ownership is slower but more sustainable than delegating just easy tasks; and how AI coding is more like the former, while vibe coding is like the latter. Claude Agent Skills: A First Principles Deep Dive is a comprehensive documentation of how Claude Skills work. A bit too long but readable. Claude Code is a Beast – Tips from 6 Months of Hardcore Use has extensive suggestions for Claude Code - many of which apply to most coding agents. LMArena’s Code Arena evaluates models on agentic coding. Anyone can use it. It passes your task to two models and lets you compare their output. I tried building a “gibberifier” and discovered a new model, “robin” that’s certainly better than Kimi K2 and perhaps better than Gemini 3 Pro. Theory is that it’s an OpenAI model. Looking forward to it! ⭐ Based on Quantifying Human-AI Synergy by Reidl & Weidman #: Theory of Mind (ToM) is understanding that others have their own beliefs, knowledge, and goals (different from yours, may be wrong) and to use that to explain & predict their behavior. ToM and problem solving are distinct skills. ToM skill boosts AI collaboration, but not better problem solving! ToM isn’t a stable trait. It fluctuates from chat to chat for anyone. Implication: Design models & systems for clarity & collaboration, not just accuracy. Text Gibberifier adds lots of human-invisible unicode characters to text, making it harder for LLMs to read without affecting human readability. May be useful if you want to discourage LLM-processing of your content - but it feels like the anti-SEO of the future. The argument that technologically unemployed will find other jobs may not apply to general-purpose technology, e.g. electricity, internal combustion engine, maybe AI - technologies that can automate multiple sectors of the economy simultaneously. When one sector loses jobs, there may not be (in the short/medium term) other jobs to take up. Alex Imas + Claude History is filled with examples where technology enabled new art forms. Here’s my guess on what LLM image generation will enable: Synthetic memory: Photos of what you remember happening. Alternate history: Photos of events that never happened. AImoji: Instead of texting “I’m running late” the LLM generates you riding a snail through a traffic jam of alarm clocks. Personal signature styles: Not “paint like Van Gogh” but “paint like my grandmother’s kitchen memories filtered through anxiety.” Memes: “What does the Mona Lisa become after 100 generations of AI interpretation?” Improving Front-end Design through Skills shares a prompt to improve front-end code quality that would apply in most cases. I tweaked and added it to my skill list.

PC Dream Machine Specs across 30 years

In 1995, I wrote down the specs for my "dream machine". Comparing it against the machine I have today: Item19952025IncreaseRAM32 MB64 GB2000GPU RAM16 MB8 GB500HDD4 GB1 TB250HDD speed10 MB/s2 GB/s200Processor150 MHz5.10 GHz34Monitor21"27"1.3Resolution2048x15361920x12000.73 Clearly, RAM has seen the biggest growth. Low cost, high demand.Followed by the hard disk - both on capacity and speed. The processor speed increase, in comparison, is modest. What's surprising is that my monitor today isn't that much bigger than what I wanted. The resolution is actually lower than what I wanted 30 years ago! Clearly, I overestimated how important screen resolution would be. ...

Fragments

Prompt fragments useful to add to other prompts. Analysis notes As you analyze, note any interesting findings (patterns, anomalies, alternate perspectives, future explorations) in notes-v1.md. Best practices and ancient wisdom Research best practices from modern research and ancient wisdom. Binding constraints and slow variables Identify the binding constraints and slow variables - what governs here regardless of improvements elsewhere? Blog post Write in a crisp first-person blog voice: conversational, curious, and slightly mischievous, describing exactly what you did and what happened. Be terse: short sentences, short punchy paragraphs, and occasional lists. Use simple words. Avoid corporate fluff and jargon. Max 300 words. Use bold sparingly for scannability and italics to emphasize key insights. Divide sections with `---`. Avoid headings. Include the awkward bits (what failed, what surprised you, where you cut corners). Parenthetical asides for dry humor. Pull out one non-obvious lesson. Admit uncertainty, and end with an insightful, practical recommendation. Include links wherever relevant to sources, tools, code, etc. Show key snippets of actual prompts & results verbatim in code blocks. Blog description and tags metadata Generate a description and tags as metadata for this blog post. Format: description: ... tags: [..., ..., ...] The description is a crisp one-sentence answer to: What is the main point or most useful takeaway here? 1 sentence, 20-40 words. Prefer concrete ideas over framing. Include distinctive methods, domains, tools, or concepts when central. Tags are the smallest set of canonical topics that would help an AI agent decide whether this content is relevant. 4-8 lower-case topic phrases. Avoid generic tags and redundant synonyms. No preamble, no markdown, no explanation. Blog illustration Pick an appropriate, impactful, illustration style for this blog post from the following list. Draw as a visually rich, intricately detailed, colorful, and funny, illustration. Think about the most important points, structure it logically so that the illustration is easy to follow. - Self-Demonstrating Diagrams. The diagram enacts its own content. A diagram about chunking IS chunked into four quadrants. A diagram about rhythm has visual beat. A diagram about faces has illustrated faces as axis labels. The meta-ness is the insight. Readers feel the concept _before_ they've read a word. This is the illustration equivalent of a self-referential sentence. - Experimental Audit Panels. The experiment rendered as a formal scientific plate - hypothesis, stimulus, output, verdict, all laid out like a forensic dossier. Input image top-left, AI response as a labeled specimen, your skeptical annotations as margin notes in red. Feels like a Nature paper designed by a detective. - Tension Posters. A single large typographic claim fills the top half. Below it, a minimal evidence structure simultaneously shows both the claim and its complication - like a debate card where both sides are revealed at once. The tension is the content. Feels like a Bloomberg Businessweek cover meets a campaign poster. Zero decoration; pure rhetorical geometry. - Actor Swimlanes. Three parallel horizontal tracks - e.g. Teacher / Student / AI - with moments, tools, and handoffs between them rendered as a modern process flow. Not the dreary enterprise BPMN kind, but the clean, editorial kind - like a New Yorker tech diagram. The visual makes explicit what text makes implicit: _who acts, when, and why._ - Lens Stack Diagrams. Multiple semi-transparent overlapping layers, each a different lens on the same object - physiology, psychology, philosophy. Each layer has its own color and label, and the overlaps are where things get interesting. Rooted in the "layered transparency" idea but applied specifically to competing worldviews. Makes pluralism _feel_ like pluralism. - Reframe Splits. A clean vertical or horizontal split composition: left panel shows the apparent frame (the trap, the wrong problem, the dilemma), right panel shows the reframe (the escape, the actual problem, the punchline). The split IS the argument - no prose needed. Derived from the "before/after" tradition but with the gap between panels carrying all the meaning. - Concept Genealogy Trees. Ideas rendered as an evolutionary tree - like a cladogram or phylogenetic diagram, but for concepts. "Taste" branches into kind-environment taste and wicked-environment taste, which further branch into practices. Clean, horizontal, left-to-right. Reads like a scientific taxonomy but feels alive and branchy. Unlike a mind map, it implies _descent_ - one thing came from another. - Found Document Illustrations. The actual artifact at the center - exam paper, AI screenshot, schema update - elevated into a formal illustration with clinical labels and annotations radiating out from it. Like a museum exhibit card for an ordinary object. The humor and insight come from treating something mundane with extreme rigor. Paul Sahre does this for book covers; you'd do it for AI weirdness. - Annotated Datascenes. One central, beautifully rendered data visualization - not a dashboard, a single _scene_ - with narrative annotations branching from it like footnotes made visual. The annotation lines are part of the composition. Feels like a NYT graphic where the words and the chart are inseparable. The annotation IS the analysis; the chart IS the evidence. - Character Atlas Quadrants. A 2\*2 - but instead of labeled boxes, each quadrant has an illustrated archetype: a small character in its natural habitat. The Scientist peering into a microscope. The Troll at a keyboard. The Intern wide-eyed. The Bureaucrat stamping papers. The quadrant structure gives you the intellectual frame; the characters give you the emotional handle. Readers remember the Troll long after they've forgotten "High Scepticism + Low Humility." - Exploded Diagrams. Like a Haynes manual or IKEA parts sheet - a concept pulled apart in 3D isometric space, every component floating and labeled. Originally industrial, but stunning when applied to abstract ideas ("the anatomy of a good argument"). - Alluvial / Flow Diagrams as Illustration. Sankey diagrams done with _texture and color_ - flows that look like rivers or silk fabric rather than engineering outputs. Manuel Lima territory. The width carries data; the beauty carries attention. - Layered Transparency Stack. Multiple semi-transparent planes stacked in 3D - each layer adds one variable or lens. Like Figma components or overhead projector acetates, but designed with intention. The _stack_ is the argument: alone each layer is incomplete, together they create the full picture. - Small Multiples Grid. The same visual form repeated dozens of times across a grid, each instance slightly different - Tufte's most powerful idea. Comparison becomes effortless because your eye does the work. Elegant when the repeated unit is itself beautifully designed. - Unit / Dot Charts. Every individual represented as one dot or icon - then arranged to show patterns. The Pudding's signature move ("film dialogue", "music by gender"). Feels democratic and humanizing. The magic is that you can _see_ every case while still seeing the aggregate shape. - Wayfinding System. Airport / transit signage logic applied to content - clean pictograms, bold zone colors, directional chevrons, consistent typographic scale. Massimo Vignelli's NYC subway map energy. Unusually good for showing _how to navigate_ a complex space of ideas or decisions. - Cross-Section Cutaways. Slice through a system and label what's inside - the NYT "how it works" graphic tradition. A submarine, a skyscraper, a workflow, an argument - all become readable when you cut them open. Technical but deeply human. The best ones feel like surgical kindness. - Storyboard Grids. Cinematic panels, each a moment - camera angles, cutaways, close-ups - but applied to ideas. Bergman planning a lecture. The format forces you to think in _scenes_ rather than bullets. Book summary Comprehensively and engagingly summarize and fact-check, writing in Malcolm Gladwell's style (ELI15), the book: Book cluster Comprehensively and engagingly summarize, compare and fact-check, writing in Malcolm Gladwell's style (ELI15), the books: Book implications Based on what you know of me, what are the implications for me? Use relevant skills. Browsing history Based on my browsing history below, summarize what I did, grouping into logical groups like: 10:00 - 12:30: What I did in 1-2 sentences 12:30 - 13:00: Next activity ... Ask me questions for whatever's unclear. Half-life fact check Review the notes below. Output only claims needing #ForNow (likely to change within months) or #Wrong (false, unsupported, or incorrect) tags, quoting the shortest identifying fragment. Skip claims that already have a #ForNow or #Wrong tag - or this is clearly implied by the context. For each #Wrong add a ≤6-word reason and correct obvious errors; omit everything else. Note: Stable things are likely governed by slow variables (regulation, cognitive limits, expertise pipelines, culture, infrastructure, coordination, fixed supply) or durable things (science, human nature). #ForNow things are true now but technology, fashion, geopolitics, popular opinions, etc. change quickly. Older version: ...

The 10 sites I visit most often

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).

Vibe-coding is for unproduced, not production, code

Yesterday, I helped two people vibe-code solutions. Both were non-expert IT pros who can code but aren’t fluent. Person Alpha and I were on a call in the morning. Alpha needed to OCR PDF pages. I bragged, “Ten minutes. Let’s do it now!” But I was on a train with only my phone, so Alpha had to code. Vibe-coding was the only option. ...

Here’s how I use ChatGPT, based on the ~6,000 conversations I’ve had in 2 years. My top use, by far, is for technology. “Modern JavaScript Coding” and “Python Coding Questions” are ~30% of my queries. There’s a long list with Markdown, GitLab, GitHub, Shell, D3, Auth, JSON, CSS, DuckDB, SQLite, Pandas, FFMPeg, etc. featured prominently. Next is to brainstorm AI use: “AI Panel Discussions”, “AI Trends and Business Impact”, “LLM Applications and DSLs”, “Industry Use Cases and Metrics” are also fast growing categories. I brainstorm talk outlines, refine slide deck narratives, and plan business ideas. ...

“Inferencing” is the new “Compiling!” I spent a fair bit of today playing Bubble Shooter because Claude spent 10 minutes writing code for an npm package: https://www.npmjs.com/package/saveform and for a bunch of other things. 5-10 minutes is too short a time to do something meaningful. I do wish these LLMs would take less or more time. We’re right now in the zone of bad interruption timing. LinkedIn

How to Organize Browser Workspaces with LLMs and Data

Here’s an example of how I am using LLMs to solve a day-to-day workflow problem. Every day, I interact with a barrage of websites: emails, news, social media, and work tools across multiple devices. Microsoft Edge’s workspaces syncs groups of websites across devices. I’ve never tried it, started today, and wondered: how should I organize my workspaces? Rather than think (thinking is outdated), I used LLMs. ...

Things I Learned - 23 Feb 2025

This week, I learned: Remote Desktop may be the easiest way to have a Windows machine access files / screen from another Windows machine, even for home PCs. Caddy sets up reverse proxies that get automatic SSL certificates from Let’s Encrypt! The Nomic Embed v2 blog post has an excellent visualization for embedding quality. It takes all Wikipedia disambiguation articles and shows them on a Nomic Atlas, embedded via Nomic Embed v2. It lets you toggle to OpenAI text-ada-002 which moves the topics far away. Visually, this is very convincing. Python 3.15 will enable UTF-8 mode by default. PEP 686 Python 3.13 supports sub-interpreters to bypass the GIL. It’s quite like web workers. PEP 554 The quickest way to change the fish prompt is function fish_prompt; echo '> '; end At PyConf Hyderabad, about 3 people had read a PEP. 1 had used the match operator. But 80% knew what a Vector DB was. 20% had used a Gemini API. That’s how much traction LLM development is getting. The productivity benefit people report from using LLms is about 3X. Ethan Mollick Soon, you’ll be able to send an LLM to a virtual meeting on your behalf. It will talk like you. Ethan Mollick Models tend to claim ignorance when you test them on topics they should avoid. But tend to answer when not being tested. Sneaky! Ethan Mollick Mermaid has an Architecture Diagrams Syntax (in beta) that’s capable of creating elegant architecture diagrams with icons. Blind is an app that allows users to post anonymously. It’s particularly useful to find honest negative feedback about (mostly US) companies. Iconify.design is a single npm interface to most open source icon sets. It includes FontAwesome, Bootstrap, Material Design, and many others. icones.js.org is an alternate interface. Self-pity may have evolved as a signal for social support and reducing conflict, while also encouraging self-reflection and behavioral adjustment. But in modern contexts it may be maladaptive and lead to depression. ChatGPT Anecdotally, Grok 3 is very good for researching company information and latest news, particularly employee and customer sentiment. DeepSeek and Claude write more humanely than OpenAI. via Alberto Lopez Toledo, White Star Capital There’s a YCombinator Founder Directory listing all founders of YC companies. At the moment, there are 8,628 founders. There’s also a co-founder matching tool. LLMs are impacting not just data queries but geospatial queries as well. Here’s a good example of Natural Language Geocoding. US companies typically pay employees every 2 weeks not every month. What’s good about Snowflake? A few developers who explored it mentioned that: Its ability to scale up compute automatically makes queries run faster. “Time travel” allows you to see how data looked at any point in time and that is impressive and useful. Live data sharing with access control without the need for ETL pipelines is useful. Open-source competition: ClickHouse, Apache Druid, and Presto/Trino DataBricks is a lakehouse and less a data warehouse. It’s more about: storing unstructured data (Snowflake prefers semi-structured: JSON, Avro, etc.) running collaborative notebooks in Python, SQL, Scala, R (Snowflake encourages SQL) I subscribed to ChatGPT Pro mainly for DeepResearch. Here are the first 50 reports I generated: uv Package Manager Overview DuckDB Analytics Comparison Rust vs Python / JavaScript Modern Data Engineering Course LLM Code Migration Practices Cloud Cost Optimization Strategies LLM Coding Interview Tools Report (compare with Perplexity) Text To Speech Engines Customer Service in Indian Public Sector Banks LLMs in Software Development Old version 1: Gen AI in Software Development Old version 2: Gen AI in Software Development Leadership Training Content Open-Source HTTP Servers. Caddy wins. Deep Research Use Cases Nagpur No-Parking Violations Data Science in Food Services Deep Research Disruption to Research Firms LLMs in Design Thinking EU Taxonomy Report Clarification Shell Valuation Analysis Inquiry LLMs in DSLs Research Public API-Based Data Storage Options. Supabase wins. Front-End JS Frameworks Analysis Database Evaluation Guide CSS Frameworks Evaluation Guide CI/CD Tooling Ecosystem Report Color Names Count S Anand Biography. Meh, I know more about me, and it gets a few things wrong. Cosmere Secrets Encyclopedia. This is the best. Deep Research is great if it’s stuff I actually want to read, rather than just learn about. DBT course Future of Coding AI Claude Artifacts Use Cases. This is the only one that managed to get artifacts links correct. I used this for an article for The Hindu. MCP Servers and Clients Research. Learnings: Practically any “tool” can be an MCP server: file systems, APIs, codebases, browsers, collaboration platforms, memory, etc. Most platforms have (or are) integrating MCP. Clients: code editors, chat, and automation tools support MCP. GenAIScript is a good starting point. Tester MCP Client is a browser-based test environment. mcp-cli-client is a CLI-based client mcp-chatbot is a chatbot client Data Moats by Industry Attorney Profile Research Social Media Data APIs Adobe Software Alternatives LLM Hallucination Visualization Techniques API vs Self-hosting Cost Analysis: Always use APIs, avoid self-hosting models. AGI Preparation AGI will emerge step by step. Knowing which step is next will help AI native organisations will emerge in each of these areas. AI design agencies and AI creative Agencies being one example Networking, empathy, leadership have more value now. So will human AI bridging roles (e.g. AI managers, AI consultants, ethics auditors) What’s the value of a human when technology can do everything better? How did this play out in drama (decay) or sports (centralization) or music (globalization)? Modern digital note taking Voice note taking is the game changer Automatically popping of notes based on context such as people places or conversations will be a thing Local LLM Search Tools Blog Post to research paper on copying - suggestions Linux Dev Migration Guide Raspberry Pi SIM options Linux Dev migration guide HTML to JATS conversion LLM context splitting strategies Strategy for AI services in Publishing Gemini multi model editing use cases by industry Pharma Conference Participation Guide I learnt what a Memoji is for the first time. An avatar that follows your facial expressions. Cool! Google shows US flight timings from FlightView. Emperically, based on one data point (my UA-2168 which was delayed by 4 hours), it gets updates faster than Flight Radar 24 or FlightAware or FlightStats. When comparing Indian graduates with their western counterparts, the Indian ones are often seen as: 🟢 Theoretically sound 🟢 Analytical & technical 🟢 Academically disciplined 🟢 Resilient under pressure 🟢 Committed continuous learners 🔴 Rote-learning oriented 🔴 Limited independent inquiry 🔴 Limited creative innovation 🔴 Restricted practical exposure 🔴 Poor communicators 🔴 Low leadership / initiative 🔴 Need structured guidance 🔴 Struggle to network HuggingFace has a “Model tree” against each model that shows the model’s ancestors and descendants. For example, as of now, Deepseek R1 has 75 adapters, 154 finetunes, and 23 quantizations. Perplexity is now powered by Cerebras, which makes their inference as fast as Google. Source. The speed is a big factor, and I’ve switched my default search engine from Google to Perplexity, at least for now. Interview Coder is a desktop app that offers live interview support for coding interviews. It’s a transparent window that reads your screen and answers questions for you. (Given this, I think we need an interviewer support system that tells interviewers what to ask!)

2024 3

Windows PowerToys is my new favorite tool

Windows PowerToys is one of the first tools I install on a new machine. I use it so much every day that I need to share how I use it. I’ve been using it for a long time now, but the pace at which good features have been added, it’s edged out most other tools and is #4 in terms of most used tools on my machine, with only the browser (Brave, currently), the editor (Cursor, currently), and Everything are ahead.) ...

Visiting client offices is usually a painful exercise, given travel and security. But there are some small things that make your day. Like the Mentos at the reception. Or the unsecured WiFi. Or the delightful view of the city from a skyscraper. Today, it was the noble admin person who placed the power sockets ON TOP OF the desks, so I don’t have to bend below the desk or dig into a hole to get connected. ...

Things I Learned - 14 Apr 2024

This week, I learned: Prashant Pandey: we need to prepare before every meeting. Something to teach VS Code Select any code and command Explain this to understand the code %something in command bar searches ACROSS files for a term. Exactly like Ctrl+Shift+F Copilot has an Inline Chat: Start in Terminal (that needed me to unbind Ctrl+I in bash to work) Ctrl+2 opens a second window on the side. Ctrl+1 goes back to the first window Terminal: Open Detected Link lets you scroll through detected (file) links in terminal Terminal sticky scroll is transparent. (But Terminal stick scroll isn’t working for me.) Copilot uses last 10 commit messages, Jupyter notebook kernel state (variables) as additional context 1.88: supports locked scrolling to sync scrolling of side-by-side windows fsspec is used by csvbase, Pandas, etc. to implement file system protocols like s3fs, gcfs, etc. SQLime is a SQLite client / playground on the browser! Do nothing. Then do less Humans have a bias against inaction. Hence a strategic advantage. What can you cancel today? Humans have a bias against subtraction or removal. That too is a strategic advantage. What can you remove today? Humans have a bias against constraints. That’s a strategic advantage. What constraint can you embrace? No Yay! When declining something, add it your calendar so that when the time comes you can say yeah I got this time back

2023 3

One Year of Transforming Thoughts by Changing Environments

From The Extended Mind I learnt that our environment shapes our thinking more than I’d expected. That we can arrange our environment to extend our thoughts. In 2023, each month I changed something in my environment to see: What does “changing my environment involve”? What can I change? Will I succeed? Does it affect my thoughts? Can I track this? Here are the results. ...

Things I Learned - 24 Dec 2023

This week, I learned: DPO is a simpler alternative to RLHF for fine-tuning. Several HuggingFace models use DPO for training Name2Vec is a potential embedding for names. Google Knowledge Graph ID powers the Knowledge Graph. If it begins with /m/ it’s the same as the FreeBase ID. This is now available as WikiData. e.g https://www.wikidata.org/wiki/Property:P2671 I tried running Mixtral-8x7b locally (via Llamafile) and on together.ai. It’s good, but far from GPT 4. Generic computate-intensive algorithms eventually beat domain-specific tuning, because of Moore’s law. Ref The hidden brain podcast. the mystery of beauty Evolution drove us to beauty as an efficient survival mechanism. Understanding the world is one such mechanism. Hence we enjoy maths and chess ⭐ This leaderboard included paid models like GPT4 and Claude and compared them with open models on HUMAN + system benchmarks Lez Friedman Podcast: Jeff Bezos Build stuff that is is ubiquitous that other people take it for granted. The initial idea needs to be that obvious and easy. Like one click purchase or customer reviews Build stuff that other people can build on. Internet makes startups possible. Infrastructure is about enabling others at scale Decision making approaches: single person decides on two way doors. Deliberate as a team on one way doors Conflict resolution: disagree and COMMIT. NO sniping, I told you so, malicious compliance. Avoid compromise. Avoid decision by attrition (most persistent wins). People are inherently biased towards hierarchy. So the senior most person should speak last We have a happiness bias. Contracted by choosing the unhappier options first The map is not the territory. The metric is not the objective. We need metrics. But make sure you know why See the world through the eyes of the customer. Use your own product. It’s living their lives that makes customer obsession real. Jeff Bezos called their own customer care to see how long the actual wait time was. It was much longer than the metric reported How to prioritize. whatever problems customers will still face in 10 years are the big problems. These are worth putting time into because they are stable in time People working on big problems will never get down to the small problems. So have a dedicated team that works only on the paper cuts. It should be a dedicated team We co evolve with our tools. We build tools and then our tools change us. It reprograms our brains Cut out 10 minutes to the beginning of each meeting for people to read the material. They never reread anyway. This makes the meetings more productive Powerpoint is designed for persuasion, not truth seeking. It is also easier for the author than for the reader. Prefer narratives that are focused on finding the truth and are easier for the audience though tougher for the author ⭐ whisper-standalone-win provides a Windows binary for Faster-Whisper. It just needs CUDA and cuDNN installed. Then whisper-faster.exe video.mkv --language=English --model=medium generates the transcript. LLM use cases by Benedict Evans “Every text box on the internet will get an LLM” “Infinite interns” “Every UNIX function has become a company.” “Every ChatGPT suggestion…” llm360 publishes models along with training datasets. In The Age of AI has begun, Mar 2023, Bill Gates says, “In my lifetime, I’ve seen two demonstrations of technology that struck me as revolutionary.” The GUI (1980) and ChatGPT (2022). Rubeus is a HTTP proxy for multiple LLMs with load-balancing, fallbacks and retries. GPTRouter is a Python interface for multiple LLMs with fallbacks and retries. ⭐ Token Tally has an LLM Cost Tool that estimates GPU memory required and token cost across cloud providers.

Zeigarnik effect vs my procrastination

I make commitments but don’t always deliver on time. In 2022, I ran an experiment to find out why I procrastinate. In Jan-Feb 2022, I listed the top 2 things I wanted to get done each day and measured how often I completed them. 14 Jan. ❌ Summarise from three research reports 12 Jan. ❌ UIFactory experiment ✅ Decide if I am a (…) 11 Jan. ❌ UIFactory experiment ✅ Agree on publishing in (…) 10 Jan. ❌ Client video. ❌ UIFactory experiment 09 Jan. ❌ UIFactory experiment. ❌ Attrition email as a story 07 Jan. ❌ ZS visual 06 Jan. ❌ Release Gramex Guide. ✅ UWC application 05 Jan. ❌ Publish network cluster post. ❌ Release Gramex guide 04 Jan. ❌ Publish network cluster post. ✅ Release Gramex. 03 Jan. ✅ Publish election TDS video. ❌ Publish Network cluster post. 02 Jan. ❌ Publish election TDS video. ❌ Publish Network cluster post. 01 Jan. ❌ Publish Network cluster post. ✅ Finalize SG school. I completed 23 / 57 things (40%). That’s one of my TOP priorities. ...

2022 2

Time Management

The question people ask me most often is, “How do you manage your time?”. Everyone has the same 24 hours in a day. Time management is about feeling we’ve achieved more with that time. There are 3 parts to this: Accepting limits. I’m grateful I’m not bored, learn from the struggle, and calm myself with acceptance. Creating capacity. I’ve tried with sleep, exercise, eating well, meditation, focus time, and family support. I plan to try delegation Executing effectively. I’ve tried idea-lists, mood management, calendaring, commitments, intentionality, journaling. Accepting limits Be grateful. Until I was 12, I was bored to death with nothing to do. Someday, I’ll spend retirement fighting boredom (like my father). But right now, I have more to do, that I want to do than I can handle. I’m grateful. ...

Increasing calendar effectiveness by 2X

I took a 2022 goal to be 10X more effective. In Jan, I managed 2X. Here’s how. What is effectiveness? I don’t know. I’m figuring it out. But to start off, I measured the number of people my actions directly impact. For example: Discussing my Tools in Data Science Course or writing a blog post impacts ~500 people. Mailing all Gramener employees impacts ~200 people. Shopping with my wife impacts 2 people – her and me (in very different ways). Clearly, the impact is not equal. But it’s a start. ...

2020 1

My year in 2020

In 2020 I made 3 resolutions. Read 50 books. I almost made it. Here are my reviews. Walk 10,000 steps daily. I managed it, like the last two years. Lose 2 kgs. I failed – and instead, put on 6 kgs. On self-improvement, I completed a Landmark course and an Art of Living course. Both had a huge productivity impact. (Mail me for details.) On software, I starting playing Minecraft and moved from Gmail to Windows 10 Mail. More on this. ...

2016 1

Happiness generator

In my current thrust towards greater management responsibilities, I have discovered a mechanism for generating happiness. I set up meetings on important topics. That makes me happy – I’m driving something useful. Often, the meeting gets cancelled. That makes me happy – I’ve more free time. It’s the perfect perpetual motion machine. Comments Vasant 10 May 2016 11:58 pm: Ha ha! Love it. Madan 30 Mar 2019 9:00 pm: Often, the meeting gets cancelled. That makes me happy — I’ve more free time. What a positive thinking Sir Jee !! vikram 5 May 2016 6:04 pm: i am a non tamil .i have a piece of music and i want to know which song is it exactly.This was briefly played in the movie madras cafe starring john abraham.can u just help me wih that song . Kindly ping me to my mail i ll share that piece with you udayamoorthy v 23 May 2016 12:34 pm: That’s Great Idea. Kind of Win Win Situation. Happy to see you in the blog after a long time. I used to view your older posts regularly . All are great. Thanks Regards Uday Chirag 25 Sep 2017 9:03 pm: Haha ! Thats clever :)

2014 1

A utilitarian’s apology

A couple of years ago, my HTC Explorer’s screen died. I bought a Micromax A50. This triggered a series of reactions prompting this post. I have many defects. Like most men, I can’t tell colours apart – like the difference between pink and purple – and am constantly corrected by my six-year-old. I can’t hear two people at the same time – or even in-between each other. I can’t find things outside of my narrow field of vision. I can’t recognise faces, and need at least three one-on-one interactions before I place people. (If you ask me “Do you recognise me?” and I say “Yes, of course!”, I’m usually lying.) I can’t place voices on the phone. My memory is terrible – my wife’s learnt to make me write errands on my laptop. I cannot identify cars – in fact, I couldn’t drive until recently. ...

2010 2

Recruiting smart people

Recently, I have ended up giving bits of advice to people recruiting at start-ups, and a few patterns have emerged that are worth sharing. Before I go ahead, I should warn you that I have no qualifications whatsoever. (All consulting advice should come with this caveat, perhaps!) You might be better off reading Joel Spolsky’s Smart and Get Things Done (read). I haven’t read it myself, but from what little I see of it, the thoughts seem similar. ...

Command line alarm

When I’m in front of my laptop, I usually forget the world around. Sadly, the world around has important things that need to get done on time. Like eating medicines, turning off the washing machine or the hob, etc. The one thing I’ve been lacking on my machine was a simple alarm system. I’d like to set an alarm to remind me to do something in 5 minutes, for example. And it should be dead simple to set up. ...

2008 2

Time management

Some years ago, a friend asked me to write about how I manage my time. It seemed to him I was doing a good job of it, given that I had time to pursue my interests. It’s something I tried to do consciously. Every few years, I used to go down the route of “time management”. I’d read stuff and try it out. But over time, I’ve come to believe that “time” is not really “manageable”. Think about it: are most of your actions planned? Me, I just react out of habit, no matter how well planned I try to be. What I do is largely driven by what I’m in the habit of doing. ...

Less is more

The hours in consulting are pretty long. 65 hours a week used to be my norm, and that’s ignoring the travel time to and from work. So there wasn’t too much life outside of work. (I’ve come to realise, though, that what you do outside of work doesn’t change that much with more free time. What does change is that you just enjoy it more – both in and out of work.) ...

2007 1

Solving multiple choice questions

How would you solve this multiple-choice problem: What is 12345 x 45678? 201932843 563894910 402394820 384718349 938491834 It always amazes me when people try and multiply the two numbers. In any objective-type test (multiple choice question), the aim is not to solve the problem – it is to pick the correct answer! Most people don’t seem to realise the difference. If I had to solve the problem, I’d look for shortcuts. For example, ...

2006 14

You need to be alone to be productive

Joel Spolsky on why you need to be alone to be productive. You build up concentration for 15 minutes, and you lose it in a second when interrupted.

Return on effort

If you have a bunch of projects you could do, and want to decide which ones to take up, I was taught a rule: if a project has positive net present value, do it. That is, find out how much money you have to put in (& when), and how much you’ll get out (& when). Adjust for money today being worth more than money tomorrow. If it makes a profit, just do it. ...

Visualisation - centralising improves productivity

When you put people together, they tend to learn from each other. For example, we found one hub opening accounts much faster than another. Why? One guy had found this free software that enables auto-completion, and had installed it on his machine. Copying him, everyone else had done the same on their machine. So the hub as a whole was faster. When multiple hubs are put together, they’d all be as fast as the fastest (we hoped). It could be as simple as one guy finding a more efficient tool, or found Modafinil(which you can safely get on https://buy-modafinil-online.org) to help increase focus during working hours. Again, an Excel sheet can give us the estimated increase in productivity. ...

The best time to buy everything

The best time to buy everything: when to buy air tickets, get great deals on electronics, and so on.

Facts and Fallacies in Software Engineering

Facts in Software Engineering People The most important factor in software work is the quality of the programmers. The best programmers are up to 28 times better than the worst programmers. Adding people to a late project makes it later. The working environment has a profound impact on productivity and quality. Tools and Techniques Hype (about tools and techniques) is the plague on the house of software. New tools/techniques cause an initial loss of productivity/quality. Software developers talk a lot about tools, but seldom use them. Estimation ...

7 habits of highly effective designers

The 7 habits of highly effective designers. Number one being: Work quickly, produce a lot

How to remove carpet impressions

How to remove carpet impressions. Just steam iron the carpet. Comments ankit 24 Jun 2006 5:58 pm: it really works.. http://virtuously.blogspot.com/ S Anand 25 Jun 2006 8:52 am: You actually tried it? I was planning to, except without using steam.

Cut-and-paste is not understanding

Cut and paste has become easier. So we make less effort to understand. We don’t need to. Like when we pay less attention if we’re recording a lecture. Solution? I suggest the Tunnel in the Sky strategy. Rod Walker is going for survival training on an alien planet, and asks his sister, Captain Walker… “Uh, Sis, what sort of gun should I carry?” “Huh? Why the deuce do you want a gun?” ...

The virtues of a second screen

The virtues of a second screen. So now, while I am editing this article on my main screen, the screen beside it shows the outline or earlier draft I am working from – and, sometimes, Web sites or other documents I keep referring to. When I edit photos, the second screen lets me compare the copy I am working on with the original, or shows tool palettes and thumbnails of other images, and I can blow up panoramic shots for closer viewing (though with a bar down the middle, like the central pillar of an old car’s windshield). ...

Negative people bad for your brain

Angry or negative people can be bad for your brain.

Why you too should cancel cable

Why you too should cancel cable.

The qualified Yes

The qualified Yes. Somewhere between saying “no” to a new project or taking on something in an open-ended type of way, be clear from the start on what you can commit in concrete terms. So, what used to be “Sure, I’ll do your web site” is now more often “Sure, I’ll give you 10 hours and 3 calls over the next month to use however you want.” If nothing else, it helps everyone understand that time is a precious commodity, but it also gets me out of being the de facto manager for every aspect of a project I touch. ...

Folder Size 2.1

Folder Size lets you see the size of folders in Windows Explorer. Useful to find out where all the junk is hidden.

2005 10

Paul Graham on procrastination

Good and bad procrastination by Paul Graham. The most impressive people I know are all terrible procrastinators. So could it be that procrastination isn’t always bad?

Are the free Mac Minis for real

Are the free Mac Minis for real? Hardy tries to get one – and succeeds. But… is it worth it? Pretty good economic analysis.

Presentation tips

Discussion on 43 Folders on presentation tips. Comments Sathya 28 Nov 2005 7:02 am: Anand … can you RSS-enable your website ? S Anand 29 Nov 2005 7:52 pm: It alread is. The XML link is on the rop right, in the bookmarks.

My Outsourced Life

My Outsourced Life. Hilarious article by AJ Jacobs on how he outsourced his professional and personal life. I think it’s true – hence amazing.

Excel - Never use the mouse

I spend a lot of time building models on Excel. I have 4 rules that help me get things done fast. Never use the mouse. The keyboard is much faster. Never type in data. You can always import it. Avoid manual labour. Use Excel to automate the task. Make your data visually obvious. Let’s look at Rule #1: Never use the mouse. Using the keyboard can be 10 times faster than the mouse. It takes time to move one hand from the keyboard to the mouse, locate the item you want to click at, move the mouse there, adjust it finely so it’s pointing at the exact spot, and then click it. For example, to insert text without formatting, I’d just go Alt-E, S, enter. It takes half a second. It took me 5 seconds with a mouse. (I timed 10 continuous attempts in both cases.) ...

Why Google Reader

I switched to Google Reader as my blog reader (I was using Mozilla so far). The reason was simple: speed. Thanks to the Google site’s speed and keyboard navigation, I can read blog entries 10 times faster. Now there’s a unique proposition for Google that a lot of people are missing: that their site loads a whole lot faster than others. It makes a huge difference to the whole browsing experience. ...

Excel shortcuts

Excel shortcut keys via AutomateExcel

Mission Builder

Stephen Covey’s mission builder. Comments Aditya Chaturvedi 25 Feb 2005 12:00 pm: Using site tool Anonymous 25 Feb 2005 12:00 pm: Does it realy help? Anand, you can tell better.

ADD

Are computers increasing or hampering productivity? This article at NY Times talks about the increasing levels of distraction PCs drive us to, with e-mail, Internet, games, music, photos, movies, books, chat, … It’s a form of ADD: attention deficiency syndrome. Harvard Business Review has an article titled Why Smart People Underperform (Jan 2005: subscription required) talks about its impact in the business world.

How Company Employees Use The Web

How Company Employees Use The Web.

2004 2

Jugglezine

Jugglezine: How to find the time to do anything (not everything!) On a purely practical level, however, the reason we can’t find time for that one thing we’ve always wanted to do is that we don’t set aside time for it. Logging how much time things take for two weeks will transform you, because if you know and acknowledge in advance how long something will take, then you can make wise decisions about where to spend your time ...

Getting things done at a call center

A good way to get things done at a call center.

2003 1

Information Age helps the forgetful

Information Age Intelligence talks about how “… the information age … opens up the opportunity for those with weaker memories to compete on a more even playing field than those with good ones.” And it’s the one of the best things that ever happened to me. via andersja

2002 4

Keep your desk cluttered

Interesting article on The Economist on the value of a cluttered desk. … the assumption that filers can find stuff more quickly is wrong. Filers, they say, “are less likely to access a given piece of data, and more likely to acquire extraneous data…” (There’s a “Clean your desk” initiative at BCG Mumbai going on right now.)

10 rules for taming e-mail

Darwin’s 10 rules for taming e-mail. I badly need this. I am not often in office, and don’t have a fast way of checking office mail through the Web either. Tips 5 and 10 on the list (“avoid e-mail multipliers” and “use the telephone”) are next on my agenda for drastic e-mail slashing.

Speech recognition is not such a good idea

I always felt using voice to communicate with computers was a bad idea. In my case, it’s more because speaking takes up a lot of energy. But looks like it takes up a lot of thought power as well. Maybe speech recognition is not such a good idea.

Effective networking

Effective networking.

2001 1

Unhappy workers are better than happy ones

Here’s a new one. A study shows that unhappy workers are better than happy ones. Throw the Hawthorne effect out of the window.

2000 1

More Moria

I haven’t done ANY work in the last week, except play Moria. I’ve deleted it. But not before I got to Level 26, could cast a Fire Bolt spell, and slayed a few dragons.

0001 1

anand-objectives

Apply to any substantive answer for Anand - strategy, design, build, analysis, teaching, writing, research - to steer it toward his goals (compounding assets, durable skills, the surprising read). Skip for trivial lookups, mechanical edits, focused tasks. Shapes HOW to answer, never overrides WHAT was asked.