Sanjeev Bikhchandani

Cute instagram.com/reel/DYJwQxFiE…

@ActusDei The Jainses not the Sharmas 😊

"Do you want to get richer than your neighbour? If yes, you need a wealth manager. If no, you have your index fund earning 12% a year." My first reaction: that's envy dressed up as advice. Surely we can do better than keeping up with the Sharmas.

Last week I was on a panel at IIM Mumbai. My fellow panellist, Nitin Rao, CEO of Incred Wealth, was asked why wealth managers are even needed in the age of AI.His answer was one line. It annoyed me. Then it didn't. 🧵

I put a prompt into ChatGPT “Can you write an ode to the bootstrapping Indian Startup Founder” Here is the response 👇 Not for him the glittering cheque Signed in haste in Sand Hill rooms, Nor armies fed on venture dreams And loss-making perfumed blooms. He builds where ceiling fans complain, Where diesel fumes and summer press Their thumb upon the fragile will Of every would-be business messiah. His office first: a borrowed desk, A cousin’s flat in Patel Nagar, Three plastic chairs, one second-hand Dell, A modem blinking like a distant star. His mother asks when he’ll “settle down.” His father coughs behind The Hindu. The neighbours say with pitying smiles, “Beta, MBA nahin kiya tu?” Yet every dawn he rises still, Ironing hope into a shirt, Riding autos through traffic jams Like some small soldier into hurt. He learns the tyranny of cash: That revenue is oxygen. That profit is not bourgeois vice But freedom’s oldest discipline. He courts no headlines breathlessly, No jargon forged on Twitter Space; He knows that Bharat does not care For valuation without grace. His users call him late at night. His vendors ask for dues delayed. His coders leave for funded firms. Still payroll somehow must be made. He worships not disruption’s cult But quieter gods: retention, trust, The miracle that customers Return because they feel they must. He knows the taste of postponed wants: The cancelled trip, the ageing car, The wedding gold not yet redeemed, The dream deferred but not too far. And when at last success arrives — Not trumpets, merely steadier breath — He wears it like the Indian sun: Without announcement, without myth. For he has built the hardest thing In this loud age of borrowed flame: A company that earns its keep, A livelihood, a trusted name. O bootstrap founder, lean and bruised, Historically underpraised, The nation’s commerce rests far more On hands like yours than PowerPoints glazed. For every unicorn that flies On capital’s abundant breeze, A thousand stubborn enterprises Are built on grit, receivables, and pleas. And India, ancient, hungry, vast, Will not be shaped by hype alone, But by the ones who quietly build With customer cash and backbone.

Uber Investor Bill Gurley on why young graduates anxious about AI taking their jobs are thinking about it the wrong way: When asked what advice he'd give to new graduates worried about AI eliminating entry-level roles, he reframed the entire problem with an advice: "In any role in any field, be the most AI enabled version of yourself you can possibly be." To illustrate why, Bill draws on an analogy from anthropology: "There's tons of anthropologists that have written about how we evolve with our tools. And you can just imagine a farming competition between a guy with a tractor and some drones and the other guy's got a plow and a donkey. Who's going to win?" The implication is clear: AI isn't the threat. Being the person who hasn't learned to use it is. @bgurley explains how this plays out inside organisations: "If there are 40 people in your org all doing the same thing and you understand how AI affects that role more than the rest of them, you're not getting laid off. Like, it's just not going to happen." But the upside goes beyond simply keeping your job. Becoming AI-enabled changes the nature of the work itself: "You'll also start to understand what parts of your job are a threat or not. And maybe you can elevate yourself to where you're a designer and not the worker bee because you now have this power." The takeaway for young professionals is that the anxiety is misplaced, since AI only replaces the version of you that refused to learn it.

The universe does crazy shit sometimes. Amid runfests on roads, the stars of tonight's LSG-KKR humdinger were two UP cricketers I'd profiled four seasons ago in the same week—Rinku Singh and Mohsin Khan. Here's the piece on Rinku, a time capsule now theprint.in/feature/slow-m…

I have changed my mind on how AI will impact jobs in America. Previously, I believed AI would replace many entry level roles typically filled by young employees. The technology would then work its way up the organization and eventually reduce the total number of jobs in a company. The data is saying something different, so when I get new information I am willing to change my mind. The number of software engineers being hired has been increasing. The number of open software engineer roles is growing. The number of new college grads who get hired has increased 5.6% over the last 12 months. The unemployment level for people aged 20-24 years old who have a college degree has fallen from nearly 9% to almost 5% as well. The Wall Street Journal recently wrote “AI created 640,000 jobs between 2023 and 2025 in the U.S., according to an analysis by LinkedIn of job posting data, including new white-collar positions such as Head of AI and AI engineer.” And I am starting to see companies throughout our portfolio aggressively hiring to keep up with the demand for their products and services. If AI can make employees more productive, which is widely accepted as fact, then companies are going to want as many productive units of labor as possible. This is a key reason why I am changing my mind. AI appears to be a magical technology that will make companies more productive and more profitable. The net result will be more corporations, more startups, and more jobs. All three are big, positive wins for the American economy.

An investor risks money. An entrepreneur risks his or her life. An investor has a portfolio of investments. If a few succeed the investor succeeds. An entrepreneur has only one life. If the company goes down the entrepreneur goes down with it. The risk that an entrepreneur takes and the risk that an investor takes are asymmetric. Which is why we as investors have huge respect for founders instagram.com/reel/DXdzdaUil…

My current mental model basis what I am seeing around me and at InfoEdge in all our verticals - Naukri, 99acres, Jeevansathi and Shiksha. 1) AI is fundamentally deflationary for businesses. 2) When the cost of intelligence drops toward zero, the cost of doing many things drops with it. 3) Everyone becomes more productive but no one stays differentiated for long. 4) The natural outcome? Price compression. Margin pressure, Commoditization. 5) We’ve seen this with the internet, cloud, SaaS. AI is doing it to cognition itself. But this is only half the story. 6) AI is deflationary for existing markets and expansionary for new ones The big mistake 7) Using AI just to do the same things cheaper. That’s a race to the bottom. 8) The real question is, What becomes possible now that was previously impossible? Three ways I see AI creating real advantage 1) Solving problems that were too expensive to solve or not solvable earlier 2) Serving customers who couldn’t be served before 3) Delivering experiences and quality that wasn’t possible to deliver before In other words Don’t just lower costs. Expand the market. Because when capabilities commoditise , value shifts to, – Distribution and Customer Relationships – Brand – Trust – Proprietary data – Ecosystems The winners in the AI era won’t be the most companies which are the most efficient. They’ll be companies with the best imagination

Paid trolls. Lucknow thought of it first - two hundred years ago instagram.com/reel/DXWwKawEp…

I have hired lawyers for the last 15 years. I have helped law firms hire good talent too. For most of those years, I knew exactly what I was looking for. Give me a candidate who can research a legal issue thoroughly. Who can draft a clean contract and understand the second order effects of changing a clause. Who knows the Companies Act cold. Who can write a memo that a partner does not have to rewrite from scratch but just fine-tune. That is what I screened for. That is what I trained students for. That is what every law firm in India screened for. Day Zero interviews at NLUs test your knowledge of the Contract Act and try to understand what you did in your internships. Internship PPOs go to the intern who submits good research memos. Pre-interview screening rounds often include a drafting test. Research. Drafting. Legal knowledge. These three things decided who got hired at every good law firm in India for 30 years. AI made all three of them free. A 2nd year law student with ChatGPT can produce a research memo today that would have taken a strong 1st or 2nd year associate two full days in 2022. And AI would do it in better style. Law students using AI can draft a shareholders agreement that reads like it came from a 3rd year associate. They can answer a question on Section 230 of the Companies Act and related recent NCLAT judgments more accurately than a lot of lawyers with 5 years of experience, provided they have an AI agent open in the moment. I see this every day at Lawsikho. We train thousands of lawyers. The output quality of an average student using AI is now hard to distinguish from a good student working without it. This breaks hiring. But not in the way people think. The common fear is that bad candidates will fake their way in. Use AI to look good. Get the job. Then fail. That is not what happens. They use AI on the job too. And for most junior work like research, drafting, due diligence and contract review, it works fine. A mediocre lawyer with ChatGPT produces acceptable output for most of what a first year associate does day to day. The real problem is bigger. When every candidate's output looks the same, you lose the ability to find the ones who are genuinely exceptional. The ones who can spot the mistakes AI makes. Those who can think further than what the AI already thought. The ones who can predict what kind of trouble a perfectly formatted contract or a seemingly polished petition will land the firm into. You find out you hired the wrong person 7 months down the line. That is 7 months wasted. Also, how do you hire the ones who will become your best senior associates in 5 years? The ones who will bring in clients in 10? The ones who will make partner? You are not hiring bad people. You are hiring randomly. Because the signals you relied on for 30 years no longer separate anyone. A owner of a boutique law firm told me recently. "I used to rank my interns within the first week. Now they all look the same to me. I give PPOs based on who seems like a good person." Who seems like a good person is not a hiring strategy. So what do you actually screen for now? We spent the last few months rethinking this. Not just for law firms we help hire talent, but for our own hiring at Lawsikho and Skill Arbitrage. Three changes made most of the difference. The first change. We stopped sending take-home tests. We started sending teardowns. Every take-home assignment you send a candidate today is an open-book exam where the book writes the answers for them. You cannot outrun this. So we flipped it. Instead of asking them to write a memo, we send them a memo that AI already wrote. A 4-page legal opinion on a real Companies Act issue. We tell them upfront. We wrote this with ChatGPT in 10 minutes. It may be brilliant. It may be garbage. We are not telling you which. You have 8 hours. Send back every single thing that is wrong, weak, missing, or dishonest in this opinion. Explain why. This test does what no other pre-screen does. Asking AI to critique its own output produces bland, hedging feedback. Real critique requires actually knowing Indian law well enough to see what the AI left out. A 2nd year student who catches 3 genuine errors is more valuable to us than a 5th year student who catches zero. Every AI memo has different flaws, so the test cannot be rehearsed. The second change. We stopped testing skills AI made free. We started testing skills AI made rare. Everyone is focused on the skills AI now does for you. Research. Drafting. Memo structure. Case law recall. These were the skills law firms hired for. They are now in infinite supply to any candidate with a laptop. Their value as a hiring signal is zero. The skills that became more valuable because AI commoditized everything else are the opposite. Problem formulation. Taste. Translation. Judgment under ambiguity. We test these three ways. We send candidates a 10-minute voice note of a real client speaking. Rambling. Emotional. Mixing personal and business context. Switching between Hindi and English mid-sentence. We do not ask them to draft a response. We ask them a single question. What are the 3 questions you would ask this client before doing anything legal, and why those three? We ask this live. ChatGPT can answer any legal question you ask it. It cannot tell you which question will bring our the reality of the client's situation. That skill is the new moat. We give them a 15-page M&A term sheet that was mostly AI-drafted, with three subtle errors hidden inside. A cross-reference to clause 7.3 when the indemnity cap is actually in 7.4. A representation that contradicts a warranty two pages later. An arbitration seat that does not match the governing law. These are exactly the mistakes AI produces and exactly the mistakes AI cannot catch. Spotting them requires taste built from reading real contracts. We want to see how they interview a client. We do a roleplay for this. That one roleplay tells us more than we could understand from any HR questions that one can easily rehearse. The third change. We stopped trying to detect AI. We started requiring it. The entire conversation about "how do we detect AI in applications" is a losing war. Detectors are unreliable. They flag real writing. They miss polished AI. Every hour a firm spends on this is wasted. The move that changed everything for us is the opposite. Require AI. Watch them use it. A 30-minute screen. A real legal problem. The candidate has choice of their AI open. We are watching their screen over Zoom. Solve it live. The answer is not what we evaluate. We evaluate how they use AI. Do they accept the first output? Junior. Do they cross-check a citation? Competent. Do they notice when the model has gone off track and re-prompt? Good lawyer. Do they ignore AI entirely for a specific step because they know it will get that part wrong? That is the professional instinct we want. The way someone uses AI in 2026 is now the most honest signal we have of how they think. Not whether they use it. Everyone will use it. Whether they know when to trust it and when not to. The old hiring tested: can you produce good legal work? The new hiring needs to test: can you think, verify, translate, and judge? Every law firm in India is still hiring the old way. Day Zero interviews still ask what Section 34 of the Arbitration Act says. Internship evaluations still grade the quality of research memos that the intern may or may not have written. Screening still includes a drafting test on a hypothetical M&A deal that ChatGPT could pass in its sleep. These are all now testing one skill. How well can this person use AI. That is a useful skill. But it is not what separates a good lawyer from a great one. It never was. The firms that figure this out will quietly build the best teams in the industry. Not because they found a way to ban AI from hiring. Because they stopped screening for the things AI gives everyone for free and started screening for the things it cannot touch.

Well done Peyush

In which I chat with my old friend Safi Rizvi who has embarked on a new career as a podcaster after a long stint in the IPS. We discuss a range of topics Ep 3 | The Business of a Founder | In conversation with Mr. Sanjeev Bhik... youtu.be/G4ovrySSFAQ?si… via @YouTube

Desh ki GDP ka kya hoga. My colleague Chinmaya Sharma is worried about Samay Raina @sharmachinmaya @kitty_agar

@albinder Congratulations on this book. Just ordered ten copies on Blinkit. For the Info Edge Ventures office and for the Info Edge board. Essential reading in the car during my Delhi Gurgaon commute @deepigoyal @letsblinkit @zomato @InfoEdgeVC @kitty_agar

A glimpse of how naukri and Info Edge are using AI and what we are witnessing around the impact of AI on jobs fortuneindia.com/business-news/…

Over 300+ IPOs, M&A deals, and financial due diligence mandates now run on #LIBIL by @Legitquest — enabling disclosure-ready litigation schedules and proactive risk identification before filing

Alok Sama just faced another rejection. The manuscript for his next book got rejected by a publisher. Somewhat unusual for someone whose first book made waves and is a best seller @alok_sama has a longish history of facing rejection. In Kindergarten he was rejected for admission to Modern School in Delhi. Modern School’s loss became a gain for St. Columba’s. We are very happy to count him as one of us. The Principal of Modern School told his mother that the child seems a bit retarded. Alok went on to top in BA Mathematics in Delhi University and set a new record. I would not be surprised if forty two years later he still holds the record in some subjects. In college he was rejected for admission to BA Economics (the Principal did not approve of his hair style or his choice of hair dresser in the interview). He joined Mathematics on the rebound and excelled far more than he would ever have done at Economics. At Business School he got rejected by Goldman Sachs and settled for Morgan Stanley. He did very well there. So one more rejection is par for the course. I am sure his next book (a work of fiction unlike the first one) will also be a best seller aloksama.substack.com/p/its-hard?r=9…