Nitthin

The endgame is local open models on hardware you own. People are waking up.

The “content creation” pipe-dream is being fed to people as a democratic, easy way to some money & fame. BUT, it conceals a larger unemployment crisis, even as 83% of GenZ in one survey said the ideal job was to be a content creator. Read my ground report: theprint.in/ground-reports…

You have no experience. You’ve never started a company. You’ve never had a full time job. Nike is going to kill you. You’re a kid. You don’t have technical skills. You shouldn’t build hardware. Apple is going to kill you. You can’t build hardware. You can’t measure heart rate non-invasively. Athletes don’t care about recovery. Under Armour is going to kill you. It won’t be accurate. You don’t listen. You’re an ineffective leader. You can’t recruit great talent. You’re going to have to pay every athlete. You can’t measure sleep non-invasively. It’s too expensive to research. Athletes are a small market. The product costs too much to make. The product costs too much to sell. Your valuation is too high. Consumers aren’t going to want it. Hardware is too hard. You should measure steps. Fitbit is going to kill you. You can’t build a marketing engine. You can’t raise enough money. You need a real CEO. Google is going to kill you. You can’t be a subscription. You can’t build a brand. You can’t do consumer in Boston. Your valuation is too high. You shouldn’t make accessories. You shouldn’t make apparel. Lululemon is going to kill you. You can’t predict Covid. Stay in your niche. You are going to run out of money. You can’t build a health platform. Amazon is going to kill you. You can’t measure blood pressure. You can’t get medical approvals. The market is too small. You don’t understand AI. The market is too competitive. It won’t work internationally. The supply chain is too complicated. You can’t build an AI. You can’t raise enough money. It’s too competitive. Healthcare isn’t going to want it. … Just keep going ✌️

Service quality is inversely correlated with switching costs. The harder it is to leave, the worst it gets. Banks, Insurance, dish-based networks, schools, real-estate. Name an exception.

The hard thing about interviewing smart people is when they state their strengths, there’s a boundary where that belief collapses. And the spoken version preserves the shape of the truth but hides the extremes that matter; until a specific category of adversity where the skill fails.

Perplexity faces a proposed class action lawsuit alleging it shared users' personal data with Meta and Google even in Incognito mode, violating CA privacy laws (@rburnson / Bloomberg) bloomberg.com/news/articles/… #a260331p71" target="_blank" rel="nofollow noopener">techmeme.com/260331/p71#a26… 📥 Send tips! techmeme.com/contact

The real gap in Indian digital finance isn’t detection, it’s proof architecture. Every verification system today is a lagging indicator, it works post facto. The ecosystem needs cryptographic attestation of identity and intent at the point of transaction, not forensic reconstruction after the damage is done.

I want to address what happened to Neeraj and me last week. Of course, it was quite shocking to us as well and honestly very disheartening. But today, we want to talk about what actually happened and more importantly, what we’re going to do about it. On March 21, we were taken into police custody in connection with a fraud complaint. Three days later, on March 24, a Thane court granted us bail, finding that prima facie, no case was made out against us. The fraud at the centre of this complaint was carried out through a fake website - "coindcx.pro" by impersonators who have absolutely no connection to our platform, our systems, or CoinDCX. No money moved through CoinDCX. No transaction occurred on our exchange. The complainant himself confirmed in court that he did not know us and had never met us. I'll be honest: our experience was deeply unsettling. Not because we doubted the facts -- we knew from the first moment that this had nothing to do with us. But because it made something painfully clear: the ecosystem we operate in doesn't yet have the tools to tell the difference between the people building this industry responsibly and the people exploiting it. Think about what this precedent means: if a scammer uses your brand, your name, your face in a fake website and defrauds someone, you can be arrested. Not the scammer. You. This Could Happen to Any founder, Any Business. That has to change. And we've decided that CoinDCX will lead that change - not with words, but with actions. Today, we are announcing Digital Suraksha Network (D.S.N.) - a ₹100 crore commitment from CoinDCX to build the cyber safety infrastructure that India's digital finance ecosystem needs but does not yet have. This is not a crypto problem. This is a problem across any company which has a digital footprint. Here's what we're building: → 24x7 WhatsApp helpline: free for everyone, not just CoinDCX users, to verify links, platforms, and offers before you transact. → Open Fraud Intelligence API: We have already documented 1,200+ fraudulent websites impersonating CoinDCX. That data sat inside our systems. Not anymore. We're building an open API to share this intelligence in real time and inviting every exchange, fintech, bank, and digital lender to contribute. A shared immune system for India's digital finance ecosystem. → Cyber Safety Infrastructure for Law Enforcement: The Digital Suraksha Network will fund training programmes for state cybercrime cells on blockchain forensics and digital asset tracing. → "Caution Before Transaction": a nationwide initiative to give every Indian the tools to participate in digital finance safely. We know that no single company can solve this. Fraud networks are sophisticated, cross-border, and evolving daily. Nowadays, they make use of AI that makes them exponentially harder to catch. But someone has to start to fix this problem from the root. We are putting ₹100 crore on the table because the ecosystem cannot afford to wait. I am asking every platform, every regulator, and every Indian who participates in digital finance to join us. We want to ensure that anyone building startups in India like us can do so with confidence, and not with fear.

🚨 CRITICAL: Active supply chain attack on axios -- one of npm's most depended-on packages. The latest axios@1.14.1 now pulls in plain-crypto-js@4.2.1, a package that did not exist before today. This is a live compromise. This is textbook supply chain installer malware. axios has 100M+ weekly downloads. Every npm install pulling the latest version is potentially compromised right now. Socket AI analysis confirms this is malware. plain-crypto-js is an obfuscated dropper/loader that: • Deobfuscates embedded payloads and operational strings at runtime • Dynamically loads fs, os, and execSync to evade static analysis • Executes decoded shell commands • Stages and copies payload files into OS temp and Windows ProgramData directories • Deletes and renames artifacts post-execution to destroy forensic evidence If you use axios, pin your version immediately and audit your lockfiles. Do not upgrade.

First mover advantage is usually first mover tax. You pay for market education and wrong assumptions. Fast followers inherit the validated playbook.

Bengaluru needs to provide therapy as a public service utility.

Increasing number of AI projects/products now are a better interface on the same broken process. That's not transformation. That's a renovation on a condemned building.

"Diversification reduces risk" is taught in every finance class. Diversification reduces variance. Risk is permanent loss. These are not the same thing.

Startups don't die from bad products. They die from good products nobody finds. Distribution isn't a growth hack. It's the entire game.

@linear Excited for the reframe and evolution roadmap

Issue tracking is dead. We are building what comes next. linear.app/next

AI doesn't replace jobs. It replaces tasks. The job becomes deciding which tasks to hand over. Execution gets cheaper. Judgment gets more expensive.

Your brain is excellent at risk. Tiger behind a bush? Flawless. Increase in prices due to a war 4000 kms away or compounding inflation over 10-15 years? Catastrophically bad.

@dwarkesh_sp Everyone thinks AI slop is the problem. Slop will be the default. Shannon identified there’s a hard limit on reliable signal in noise. We’re at the human version of this: cognitive channel capacity for spotting slop in a world when slop is the default, will be limited.

If AI scientists are writing millions of papers, many of which are slop, and some of which are incremental progress, how would we identify the one or two which come up with an extremely productive new idea? In 1948, Shannon was one of hundreds of engineers at Bell Labs working on how to cleanly send voice signals over noisy copper wires. His paper sat in the same technical journal as reports on reducing static and building better filters. How would you recognize that he has come up with this very general framework for thinking about information and communication channels, which over the coming decades would have enormous use from domains as far apart as cryptography to genetics to quantum mechanics? It seems like it can take fields multiple decades to recognize the significance of unifying new concepts. Because it is on that time scale that the fruits of such general concepts lead to new discoveries across many different fields. We’ve managed to solve this peer review problem for human scientists (at least somewhat). Now we’ll need to do it at a much greater scale for the mass of AI science that will be thrown at us.

So if the post claim payout is also delayed, the perception of not needing insurance "now" compounds: the cash exits your wallet today, for a unforeseen tail event, with an unforeseen claim payout window. the human brain is designed to defer this.

something that most insurance marketers get wrong: People aren't bad at risk. They're bad at abstract, delayed, probabilistic risk. We evolved for tigers, not tail events.

Markdown+LLM is code and for creating high value complex contextual and intelligence-required tasks it is much much better than any deterministic language