llm-prompts on S Anand

I count AI summarized books as "Read"

Sat, 27 Dec 2025 02:54:41 +0000

I have this nagging feeling (maybe you do too?) that it’s cheating and I’m not really learning if it’s so easy. The same voice makes me feel guilty when using coding agents to code or ChatGPT in meetings.

I’m telling that voice to relax.

I upload books to Claude and ask it to “Comprehensively and engagingly summarize and fact-check, writing in Malcolm Gladwell’s style, the book …”. I can read it in an hour instead of twelve. Four bullet points instead of forty. With (this surprised me) roughly the same number of insights I actually do something with.

I read books for pleasure, learning, and implementing.

That last bit is key, but the bottleneck isn’t the book. It’s me: how much I can absorb, retain, and act on. From what I can tell, between reading 300 pages vs 10, there’s not much difference.

The pleasure is intact

I worried I’d lose the emotional jolt – those mind-blown moments that make reading feel worth it. For science and self-help books, I haven’t.

For example, take this summary excerpt of How Minds Change

The irony is almost too perfect. To change someone’s mind, you have to stop trying to change their mind. You have to start by trying to understand it.
And when you do that—really do that—something unexpected happens. Sometimes their mind changes. And sometimes, if you’re honest with yourself, yours does too.

That blew my mind for a good 10 minutes.

Or, from Ants:

Think of a leafcutter ant colony as a high-tech Fungus Farm. There are four main players in this system: two are partners, one is a bodyguard, and one is a villain.

I loved the villain part!

There’s a learning bonus: fact-checking

When I ask Claude to fact-check the book while summarizing, I learn beyond the book. For example, I learnt that, among these longevity books:

Lifespan is largely rubbish.
The Telomere Effect has a decent core but builds fancy castles on shaky foundations.
Outlive is more careful with its claims, though less ambitious.

I learned this during the reading, not months later when some podcast corrected me.

You can also just… ask questions.

While reading Ants, “OK, aren’t most species superorganisms then? If yes, what’s the big deal?”
While reading The Cancer Code, “Why are free radicals produced? Give me examples. Are they always oxygen molecules that lack electrons? ELI15.”

The book doesn’t do that. The summary can. (I’m loving the ELI15 responses, BTW.)

I can read inaccessible books

I can now read Kamba Ramayanam in Tamil (a script I read quite slowly). Or Gitanjali, The Iliad, Dream of the Red Chamber, or more.

It’s not just language. I can read boring or intimidating books. On Growth and Form. The Road to Reality. The Structure of Evolutionary Theory. Brilliant but unapproachable.

Heck, I managed to read Ants after 30 years!

Sometimes the very first line of a summary hooks me so hard I can’t stop reading. That’s a strange thing to admit about a summary. But there it is.

I haven’t figured it out fully

I would read Brandon Sanderson or Jeffrey Archer this way yet. The point is the experience itself: the slow unfolding, the surprise, the voice in your ear. They write in a style I like. Why summarize that?

Biographies are trickier. The Choice’s summary made me cry. So, I do want to read The Choice in original - and the summary helped me prioritize it.

Histories? I’m not sure. Manga? No way.

I’m logging these on Goodreads as “read”. I don’t know if that’s kosher. The voice in my head has opinions. But I’m learning things I wouldn’t have learned otherwise, from books I wouldn’t have finished or started, with the same pleasure and actionability.

Maybe that’s cheating. But maybe the rules of our game have changed, and I haven’t learned them yet.

Update: 31 Dec 2025. Here are the books I read this year via AI summaries, along with links to the Claude summaries.

Sex at Dawn by Christopher Ryan, Cacilda Jethá Claude
The Molecule of More by Daniel Z. Lieberman and Dopamine Nation by Anna Lembke Claude
Noise by Daniel Kahnemann Claude
How to Change by Katy Milkman Claude
Lifespan by David Sinclair and The Telomere EFfect by Elizabeth Blackburn and Outlive by Peter Attia. Claude
How Minds Change by David McRaney Claude
The Obesity Code by Jason Fung Claude
The Diabetes Code by Jason Fung Claude
The Cancer Code by Jason Fung Claude
The Ants by Bert Hölldobler, Edward O. Wilson Claude
Price of the Modi Years by Aakar Patel Claude
Behave by Robert Sapolsky Claude
The Choice by Edith Eva Eger Claude
How Not To Die by Michael Greger Claude
Why We Sleep by Matthew Walker Claude
The Slight Edge by Jeff Olson Claude
The Origin of Consciousness in the Breakdown of the Bicameral Mind by Julian Jaynes Claude
Immune: A Journey Into the Mysterious System That Keeps You Alive by Philipp Dettmer Claude Gemini
The Gene: An Intimate History by Siddhartha Mukherjee Claude
The Structure of Evolutionary Theory by Stephen Jay Gould Claude
The Extended Phenotype by Richard Dawkins Claude
The Body Keeps the Score by Bessel van der Kolk Claude
The Culture Map by Erin Meyer Claude
Outcomes over Output by Josh Seiden Claude
The Song of the Cell: An Exploration of Medicine and the New Human by Siddhartha Mukherjee Claude
The Emperor of All Maladies: A Biography of Cancer by Siddhartha Mukherjee Claude
Reality is Not What it Seems: The Journey to Quantum Gravity by Carlo Rovelli Claude
The Happiness Hypothesis by Jonathan Haidt Claude
Why We Die: The New Science of Aging and the Quest for Immortality by Venki Ramakrishnan Claude
Same as Ever: A Guide to What Never Changes by Morgan Housel Claude
Build: An Unorthodox Guide to Making Things Worth Making by Tony Fadell Claude
Metabolical: The Lure and the Lies of Processed Food, Nutrition, and Modern Medicine by Robert H. Lustig Claude
The Language Instinct: How the Mind Creates Language by Steven Pinker Claude
How the Mind Works by Steven Pinker Claude
The Blank Slate: The Modern Denial of Human Nature by Steven Pinker Claude
The Stuff of Thought: Language as a Window into Human Nature by Steven Pinker Claude
The Demon-Haunted World: Science as a Candle in the Dark by Carl Sagan Claude
Entangled Life: How Fungi Make Our Worlds, Change Our Minds & Shape Our Futures Claude
Phantoms in the Brain: Probing the Mysteries of the Human Mind by V.S. Ramachandran Claude
Small Wins Every Day: 100 Powerful Ways to Transform Your Life and Health by Luke Coutinho Claude
The Tell-Tale Brain: A Neuroscientist’s Quest for What Makes Us Human by V.S. Ramachandran Claude

Update: 11 Apr 2026. I started adding this follow-up prompt:

Based on what you know of me, what are the things I should learn from these books? What might I do differently? Why? How?

Based on past conversations, AI knows me. For example, here were Claude’s thoughts:

Anand wants personalized life lessons from these books, filtered through what I know about him. Let me think about what I know:

Chief Innovation Officer at Straive, AI strategy, enterprise consulting

Faculty at IIT Madras, teaching Tools in Data Science to large cohort

Based in Singapore, Indian origins

Blogs daily at s-anand.net about AI experiments

Interests: data visualization, behavioral science, cross-domain pattern recognition, design

IIM Bangalore alumnus

Regular speaker at conferences

Core intellectual commitments: judgment and taste as scarce resource; verifiable/auditable AI outputs; Jevons Paradox applied to knowledge work; production costs collapsing shifts bottleneck to curation

Thinks in systems, economic, and forecasting frameworks with superforecaster-style probabilistic reasoning

Identifies as “LLM Psychologist”

Teaching an AI workshop for senior IAS officers at LBSNAA

That leads to high quality ideas. For example, it told me:

… you’re surrounded by people optimizing for the marathon — the visible, bounded deliverable. But Pheidippides’ actual run — the slow, unglamorous, unsexy one that actually won the war — was the one nobody watched.

What’s the Spartathlon version of your work? Probably: the long, patient work of changing how a client organization thinks, not just what tools it uses.

… make sure you’re spending some deliberate effort on it, even when there’s no one watching and no milestone presentation scheduled.

That led me to review transcripts for AI adoption impact. Answer: workshops help AI adoption most. I’m keeping an AI experiments list handy for impromptu workshops.

That’s real impact. In less time than I’d have taken to read a book.

Sure, I didn’t get what the books had to offer. I didn’t struggle. But I did get personalized value.

Thu, 20 Nov 2025 00:00:00 +0000

While meditating, I realized 75% of “LULL” is the letter “L”. (This sort of thing happens a lot when I meditate.)

MUMMY (60% M) and DADDY (60% D) have lower percentage, but are longer, so maybe get a bonus?

I asked Claude Code what would top such a list. It picked a dictionary, generated the 333 words with 4+ letters and >50% concentration.

What did I like best? “ASSESSES”. 5/8 letters are “S”. That’s nearly two-thirds.

Then it wrote an xkcd-style story! Here are snippets:

I wrote a Python script to analyze 370,105 English words. Then I questioned my life choices.

*Does “mmmm” count? Look, I didn’t make the dictionary. I just downloaded it from the internet.

Notice something? After length 6, it’s just S-words and E-words all the way down. (It’s the grammatical duct tape of English)

I didn’t analyze Welsh, but I’m guessing their L’s would be extremely competitive.

The story way more fun than the analysis!

Check it out: https://github.com/sanand0/research/tree/main/repeated-letter-words

Learning: Find good styles to copy from. Here’s my style catalog: https://github.com/sanand0/prompts/blob/main/styles.md

The Magic of Repeated ‘Improve It’ Prompts

Fri, 18 Apr 2025 10:02:37 +0000

What if you keep ask an LLM Improve the code - dramatically!?

We used the new GPT 4.1 Nano, a fast, cheap, and capable model, to write code for simple tasks like “Draw a circle”.

The we fed the output back and asked again, Improve the code - dramatically!

Here are the results.

Draw a circle rose from a fixed circle to a full tool: drag it around, tweak its size and hue, and hit “Reset” to start fresh.
Animate shapes and patterns turned simple circles and squares into a swarm of colored polygons that spin, pulse, and link up by distance.
Draw a fully functional analog clock grew from a bare face to one that builds all 60 tick marks in code—no manual copy‑paste needed.
Create an interactive particle simulation went from plain white dots on black to hundreds of bright, color‑shifting balls that bounce, die, and come back to life.
Generate a fractal changed from a single Mandelbrot image to an explorer you can zoom, drag, and reset with sliders and the mouse wheel.
Generate a dashboard jumped from static charts to a live page with smooth card animations, modern fonts, and a real‑time stats box.

A few observations.

Models are getting much more reliable. Even a low cost model like GPT 4.1 Nano wrote error-free code in ~100 retries.

When pushed, they tend to brag. They attach grand titles like “Ultimate Interactive Circle” or “Galactic Data Universe”. They sin out flash descriptions like “This dramatically upgraded clock features a pulsating neon glow, animated pulsing background glow, highly stylized tick marks, …”

A simple prompt like Improve it can spark new ideas, revealing features such as: