Kasturi Postcards

[Kasturi Postcards @rangaeunny]

What Changed Between Two Conversations With a Fintech Founder
https://t.co/IolcmWP8IE

[Kasturi Postcards @rangaeunny]

Without scaling up eco-agriculture, ethanol blending will strain India's precarious farmlands
https://t.co/XTnqMP9eln

[Boring_Business @BoringBiz_]

Guy who has absolutely zero idea what the Bloomberg Terminal does commenting on Claude killing the Bloomberg Terminal

[Himanshu Sinha @hsinha1445]

Jensen Huang said AI has 5 layers of value. India doesn't have a presence in any of them.

⚡ Layer 1 — Energy. A hyperscale AI campus now draws 1–2 gigawatts — a mid-sized nuclear reactor, for one building. China added nearly India's entire installed grid in new capacity last year.
💾 Layer 2 — Chips. The silicon brain and everything that makes it.
→ GPUs: Nvidia (US), AMD (US), Broadcom (US) design. TSMC (Taiwan) fabs at the cutting edge.
→ HBM, the high-speed memory beside every GPU: ~90% Korea.
→ ASML (Netherlands) has a monopoly on the one machine that prints the most advanced chips.
→ Silicon wafers ~60% Japan. Photoresist ~90% Japan.
🏭 Layer 3 — AI infrastructure. The data centre and everything around the chips.
→ Hyperscale cloud: AWS (US), Azure (US), GCP (US); Alibaba (China), Tencent (China).
→ Servers and AI-rack cooling: Supermicro (US), Vertiv (US), Schneider (France), Eaton (US).
→ Commodities: copper (Chile, Peru), niobium (~90% Brazil), rare earths (~85% processed in China).
🧠 Layer 4 — Models. Closed: OpenAI (US), Anthropic (US), Google (US), Meta (US). Open: DeepSeek (China), Qwen (China), Kimi (China).
💻 Layer 5 — Applications. ChatGPT (US), Copilot (US), Cursor (US), Claude Code (US), Agentforce (US). Mostly US. Increasingly Chinese.

China has a presence in all 5. Korea owns HBM. Taiwan owns the cutting-edge factory. Netherlands owns the machine that makes it possible.

India:
Layer 1 — grid stretched, industrial power expensive and patchy. 24/7 clean power is hard to deliver today.
Layer 2 — no frontier chip factory. Tata-PSMC (India-Taiwan) at ~28nm is a decade behind AI chips. India's chip design talent works for Nvidia (US), AMD (US), Qualcomm (US), Intel (US). Value flows to US balance sheets.
Layer 3 — India builds the data center buildings (Yotta, Adani, Reliance) and generic industrial power and cooling gear (BHEL, Crompton, Blue Star). But no hyperscale cloud, and no specialized AI-rack cooling or power shelves. Every Indian AI startup runs on AWS (US) or Azure (US).
Layer 4 — Sarvam, Krutrim (India). Real teams, orders of magnitude below the frontier.
Layer 5 — Zoho, Freshworks (India) are real SaaS businesses, but their AI features — like most Indian AI-app startups — are thin wrappers on OpenAI (US), Anthropic (US), Google (US). And not agentic. Agents are where the flywheel lives. India has no agentic platform at that scale.

This is a 30-year-old choice. India bet on services and not manufacturing. TCS, Infosys, Wipro, HCL (India) built a ~$250B export industry. It paid off. But services sit above the stack — they don't own any layer of it.

India's AI Mission is ~$1B. China's is in the hundreds of billions. That's not a gap to close — it defines the game.

[Rony @Ronycoder]

Instead of watching an hour of Netflix, watch this 2 hour hour Stanford lecture will teach you more about how LLMs like ChatGPT and Claude are built than most people working at top AI companies learn in their entire careers.

[Kasturi Postcards @rangaeunny]

India Idoesn't have a single source of truth for mailable addresses and it reflects in the 90 lakh voters deleted from electoral rolls
https://t.co/XLx3DjiEEm

[Kasturi Postcards @rangaeunny]

Cricket runs on Indian money. But India needs cricket to mean something. And that meaning depends entirely on five nations being able to keep the game alive.
https://t.co/jgn1oswnKI

[Kasturi Postcards @rangaeunny]

Last week I wrote about why delivery platforms should stop moving weight.

This week I dive into the unit economics services, frameworks for finding viable opportunities and what separate real businesses from good intentions.
https://t.co/2oo06PlxCO

[Kasturi Postcards @rangaeunny]

@aaravj2406 @JournoPranay @grok grok is still rolling on the floor laughing. Wait till grok stands up.

[Kasturi Postcards @rangaeunny]

What do these have in common?
Emergency Childcare, Legal Micro-Consultations,
Pet Emergency First Response,
Coding/Tech Micro-Mentorship, |
Sleep Hygiene Coaching ?

They're all micro-services where discovery takes longer than delivery.

https://t.co/1IKYFgZ0Gm

[Ian Miles Cheong @ianmiles]

Marc Andreessen: AI coding doesn’t eliminate programmers — it redefines them. The job is no longer typing code line by line, it’s orchestrating 10 coding bots in parallel, arguing with them, debugging their output, changing the spec, and pushing them toward the right result. But here’s the catch: if you don’t understand how to write code yourself, you can’t evaluate what the AI gives you.

The next layer of programming isn’t writing scripts — it’s supervising AI that writes them. Today’s best programmers spend their day jumping between terminals, managing multiple coding bots, fixing mistakes, and refining instructions. The irony? You still need deep fundamentals, because without them, you won’t know when the AI is wrong.

The job of the programmer has changed. Now it’s about arguing with coding bots, debugging AI-generated code, and understanding why something doesn’t work or isn’t fast enough. AI abstracts the work — but only people who truly understand code can tell if the abstraction is doing the right thing.

Programmers aren’t going away — they’re becoming 10x, 100x, even 1,000x more productive. Tasks are changing, the job is changing, but humans are still overseeing the process, evaluating results, fixing errors, and making judgment calls. AI changes how we code, not who is responsible.

The future programmer isn’t replaced by AI — they’re upgraded by it. You still need to learn how to write and understand code, because when the AI gets it wrong, humans are the ones who have to know why. That up-leveling of capability is the real revolution.

[Kasturi Postcards @rangaeunny]

We’re living longer than ever, yet we haven’t solved caregiving while our demography is still still young. Your takeaway from this piece can either be an acknowledgment of a reality, or a business idea worth working on.

https://t.co/12JGSA76sW

[Neil Patel @neilpatel]

Most marketers assume AI “finds the best content” wrong. AI skims just like humans do, and if your content is messy, unstructured, or hard to parse, it gets skipped. Clean headings, clear sections, fast summaries. That’s what gets cited. If your content looks like noise, AI moves on. Structure = rankings.
#ContentMarketing #AISEO #TopicalAuthority

[Kasturi Postcards @rangaeunny]

Last week, IndiGo handed a perfect case study for capability traps that enforce selection pressures.

TLDR: IndiGo didn’t bend the market to its will. The environment selected IndiGo because every other model was unsustainable.
https://t.co/IGf5hEXk1b

[Kasturi Postcards @rangaeunny]

I stumbled on Darwin's selection pressure theory while researching NBFCs and trying to make sense of the existence of 9000+ NBFC in India.
Peppered moths in Manchester and finches in Galapagos islands helped me understand selection pressures in markets. https://t.co/AA5ISyF6pv

[Kasturi Postcards @rangaeunny]

@IndianGems_ nationalism

[Kasturi Postcards @rangaeunny]

@gunsnrosesgirl3 ketchup

[Kasturi Postcards @rangaeunny]

Why did your Provident Fund become a waiting game of for 25% of your savings
https://t.co/1ZLeL3qTuD

[Kasturi Postcards @rangaeunny]

The right prompt architecture can override an LLM's default politeness protocols entirely. The quality of output depends not just on what you ask, but how you frame the relationship.

Have a spinning toy when you do seek advice.

https://t.co/cHRLLRpVbC

[Kasturi Postcards @rangaeunny]

A good day to resurface this research on silver, the day it touched historic $50
https://t.co/RFmx1Y2YDP