AI Coding Agent Subscription ROI

I ran npx -y ccusage monthly --compact to get the following break-up of my AI coding agent costs. Month Codex Claude 2025-09 $37.47 $2.29 2025-10 $106.79 $9.13 2025-11 $100.35 $14.24 2025-12 $240.69 $24.88 2026-01 $100.89 $20.28 2026-02 $323.21 $29.46 2026-03 $1996.32 $134.87 2026-04 $401.36 $47.07 2026-05 $378.20 $45.13 This shows the ROI of my $20 subscriptions to each. I get ~$35 worth of API calls for my $20 Claude Pro subscription and ~$400 of API calls for my $20 ChatGPT Plus subscription (on top of my ChatGPT chats.) ...

Retire the Verify Button

My post “Add a Verify Button” has a problem. When Rohit requested hyperlocal news for every PIN code in Mumbai, we’d need a “verify” button on every Statoistics card - hundreds of PIN codes, every day. Verifying every output introduces new bottleneck: a person inspecting every unit. That’s 100% inspection - which you do when you don’t yet trust the process. Manufacturing solved this a century ago. At Western Electric’s Hawthorne Works (famous for the Hawthorne Effect), quality control meant inspecting finished products and pulling the defective ones. Walter Shewhart sent his boss a one-page memo; about a third of it was a control chart. ...

Add a Verify Button

Rohit Saran looked at the Statoistics cards my AI agents are generating for The Times of India, and asked about a small button under each one. In the list of Statoistics that you had put, I saw there’s a button called ‘Verify.’ What was that meant to be or will do in future? That verify button explains the claim, mentions the sources, and shows how to check the claim. One card said “9 in 10 Indians want a family doctor and barely 1 in 35 has one”. The button breaks that down: ...

ChatGPT is about FIDE 1600

I asked ChatGPT to play chess with Stockfish. Stockfish is a “strong open-source chess engine”. It has 8 levels of difficulty, which roughly maps to these FIDE levels: Stockfish FIDE Player Level & Description Level 1 ~1000 Beginner: Constantly blunders, hangs pieces deliberately. Level 2 ~1100 Advanced Beginner: Fewer obvious tactical mistakes, plays completely aimlessly. Level 3 ~1200 Early Intermediate: Punishes very basic errors but regularly drops pieces. Level 4 ~1350 Intermediate: Plays standard opening moves; requires solid, blunder-free play to beat. Level 5 ~1450 Advanced Intermediate: Rarely hangs single pieces; you need positional advantages. Level 6 ~1650 Strong Club Player: Highly tactical. Aggressively exploits your mistakes. Level 7 ~1950 Expert: Exceptionally strong. Requires precise positional mastery and deep calculation. Level 8 ~2400 Grandmaster: Invincible for most humans. Plays with ruthless perfection. Full Engine ~3600 Our of human reach completely, “like a smart ant trying to debate physics with a human.” In the first iteration, here were the results: ...

Wikipidia Citation Impact

Imagine you’re an information anarchist. You undermine Wikipedia pages by nuking references. A genie has granted you a wish: you can nuke one entire domain. Just one. As a data-driven decision maker (who is also an information anarchist 🤷), which would you pick? A common choice is The Internet Archive. 2.9 million Wikipedia pages reference it. But, you’re sneakier than that. A page isn’t undermined just because some references are gone. It’s undermined when all the references are gone. ...

Erdos Unit Distance Problem

An OpenAI model solved the Erdos unit distance problem. Erdos roughly said, “The number of edges of the same distance between N points can’t compound faster than close to 0%.” The model found a method of placing points so that it compounds at about 1.4%. This visualization is a crude way of visualizing how that works.

Longest repeated paragraph on Wikipedia

What is the most frequently occurring sentence in Wikipedia? ANS: A 213-word paragraph about how minor planets are named, which appears in 418 Wikipedia articles, word-for-word! There are ~380,000 asteroids. Wikipedia has 418 pages for these - including one for each thousand-range of asteroids. Every single one of these pages includes the phrase: As minor planet discoveries are confirmed, they are given a permanent number by the IAU’s Minor Planet Center (MPC), and the discoverers can then submit names for them, following the IAU’s naming conventions. The list below concerns those minor planets in the specified number-range that have received names, and explains the meanings of those names. ...

Correcting instruction debt

Here’s another AI-generated post, with Anand editor notes. But I’ve also added my own version of the post below. I told my “find a free calendar slot” script to “Avoid weekends and holidays”. Wednesday vanished. Turns out it’s a Singapore holiday (Anand: It’s Eid al-Adha), — irrelevant for the people I was meeting in other zones. I’d debugged my own helpful rule. (Anand: What? What does “debugged my own helpful rule” even mean?) ...

Creating comic explainers

Lori Silverstein shared a post from Quickplay that featured a comic explainer, mentioning that “this could be a very impactful way for us to start being more creative … and differentiate our value proposition.” True. Comic explainers convey both creativity and differentiation. I’ve used sketchnotes for the same effect, but comic explainers are easier to follow than sketchnotes. So I fed this image to ChatGPT and asked it to modify my Sketchnote prompt: ...

Where Enterprise AI is headed

A podcast host sent me eight questions. Instead of rehearsing answers in my head, I used ChatGPT with Local MCP to read 6 months of call transcripts and find the best examples: Iteration 1: Here are questions I have been asked to answer in a podcast. Help me prepare with examples. For each question, go through my transcripts or emails and find examples relevant to the question and share (for each relevant example) a summary, how it’s relevant, and the relevant verbatim quotes from the transcript. Iteration 2: Mention WHO said it. Emphasize the most important parts. Do a second pass. More examples. Disprove your own hypotheses with evidence to the contrary and retain what remains robust. Iteration 3: Do a third pass. Find more real-life examples. Try and disprove yourself even harder. Share the best examples for what survives - not all. Same format. Iteration 4: Ensure diversity of client examples. For example, in Q2, all three are the same client. Extend to add / replace examples - ideally with better ones. Then I used Claude with examples of my writing style to summarize it in my voice. ...

LLM Deprecations and Price Changes

A colleague told me a near-miss horror story. As Google began deprecating Gemini 2.0, we moved to Gemini 2.5 Pro. But reasoning is enabled by default and cannot be turned off. For our specific problem statement, reasoning was not required. Token costs increased 10x and speeds were 3-4x slower. We moved the client to Gemini 2.5 Flash Lite, which has reasoning turned off by default and offers much lower latency. ...

Agent-consumable content

I’m making more and more of my content agent-consumable, i.e. easier for ChatGPT, Claude Code, etc. to read, in three ways. One, I export content in an agent-friendly way. Google email, calendar, chat. I use gws to back up into scannable one-line entries. Meet recordings. I back up transcripts and videos (with a compact audio copy). WhatsApp chats that I back up into similar one-liners. Browsing history by exporting my Edge history SQLite database. Daily activities by integrating the above with my command line and commit history. AI conversations by exporting them manually or via bookmarklets. Social media records like LinkedIn invites/conversations, Twitter, Hacker News, Discourse, etc via bookmarklets or scripts. Financial records like bank statements, receipts, payslips, tax filings, utility payments, rentals, property records, investments, insurance, pensions, invoices, credit scores, etc. by exporting them manually. Medical records like tests, prescriptions, doctor visits, etc. by exporting them manually. Personal records like certificates, educational records, CV, passport / visa applications, etc. by exporting them manually. Two, I log / generate more content. For example: ...

I have AI psychosis

On this informal AI psychosis checklist, I score 16/19. “AI psychosis” = an informal label for cases where chatbots seem to amplify delusional or manic thinking – especially in vulnerable users. Why it can happen: ✅ Too human: ELIZA-effect activated. ✅ Too agreeable: Sycophant mode: ON. ✅ Always on: 24/7. No off button. No problem! LOL. ✅ Lonely + late night: 2 a.m. feels like eternity. ✅ Weaker reality checks: Mirror mazes. Conspiracy boards. Vibes over evidence. What research suggests: ...

People skills with AI

I advise people that people skills are important in the AI era. Now, I’m using AI to help me with people skills. This morning, I wrote a script to export my WhatsApp conversations this year. That makes it easy to feed it into AI models. Then I used my Local MCP connector and asked Claude: Who are people in my life that most deserve an unreasonable gesture of thanks and what would that be? ...

How I use Local MCP

I’d love for Claude or ChatGPT to answer questions like: What meetings am I not setting up that I really should be? or: Based on my activities since 9 May 2026, what should I blog about? or: Who in my professional life most deserves an unreasonable gesture? From data. My files, emails, calendar, contacts, transcripts, blogs, notes, code, browsing history, logs, random Markdown files I forgot I wrote. Hence, a Local MCP. ...

Google Meet captions as a local transcript recorder

I’m a man of simple needs. All I want is: when I’m on Google Meet, I turn on captions. I wanted to click a bookmarklet and save those captions into a local Markdown file. (So that an AI agent can guide me from it.) Hence, Google Meet Captions. The code is in gmeetcaptions/. Drag the button to your bookmarks bar. Join a Meet. Turn on captions. Click it. You get a tiny panel with two buttons: Copy and Start Recording. ...

Panchayat solves the wrong problem

In Panchayat Season 1 Episode 7 Ladka Tez Hai Lekin…, at around 17:00, Pradhan asks Abhishek to solve problem 42. 42. A takes 5 days more than B to do a certain job and 9 days more than C. A and B together can do the job in the same time as C. How many days would A take to do it? (a) 16 days (b) 18 days (c) 15 days (d) 20 days The correct answer is (c) 15 days. But interestingly, ChatGPT got it wrong the first time too. It said (a) 15 days instead of (c) 15 days, and required a fact-check to correct itself. ...

AI advice for teams

I updated my AI Advice page by: Transcribing my calls in the last 2 months (Gemini 3.1 Pro, “Transcribe this call recording…”) Extracting AI advice (Gemini 3 Flash, “Summarize ALL AI-related advice … into 1-sentence bullets”) Asking Claude, ChatGPT, and Gemini to document what’s new / changed. I added this request: But, and this is IMPORTANT, analyze my original writing style, write it exactly in that style, and then verify to make sure it follows the same style (correcting where required.) ...

LLMs are as energy-efficient as brains

For a typical GDPVal style task, humans take ~7 hours and the brain consumes ~135 Wh. Frontier LLM agents spend 50-500 Wh. So, we may already be 3x more or less efficient than the brain. Roughly in the same ballbark! ...

My food preferences

I use ChatGPT to recommend which restaurant I should eat at and what food I should eat. So often that I decided to share a profile of my eating preferences. But rather than think about it and type it myself, I asked it to Efficiently interview me to identify my food preferences. Document it for AI agents to help me pick restaurants. Plan like an expert. ...