Good Capital

Good Capital is hiring an Executive Assistant! You'll own @BadCapitalVC's calendar, communications, travel, team coordination, and complex projects. What makes someone great at this: - You've built spreadsheets and workflows you're genuinely proud of - You pick up new tools ridiculously fast (we use everything from Asana to Claude) - You have impeccable judgment under ambiguity - Your written communication is clear, warm, and concise Application deadline: January 5th midnight. Full details: docs.google.com/document/d/1Mt…

Orange Health has always been committed to six-hour reporting. Not "as fast as possible" but specifically six hours, no exceptions. This one constraint made them build everything differently. They couldn't use standard labs designed for average daily volume - they had to build for peak hourly capacity. They couldn't have doctors at each location, so they built remote pathology, where one doctor reviews slides from multiple cities. They couldn't rely on traditional logistics - so they created dedicated networks covering four times the area of competitors. Now incumbents can't copy it without scrapping their existing infrastructure. They have hundreds of labs built the old way, doctors hired locally, and established logistics. Retrofitting would cost more than starting from scratch, and starting from scratch means abandoning their existing business. I like how Orange Health's edge is that matching their model means incumbents must treat their current infrastructure as sunk cost. This is the kind of advantage that compounds.

Wild week for Indian startup acquisitions! The pattern that is showing up is that every health/wellness company is racing to go full-stack. GABIT: Ring → coaching → skincare → supplements (Näck) Honasa: Women → baby → men's care (Reginald) Marico: FMCG → wellness (Cosmix)

The words "contrarian" and "unconventional" have been said so many times in pitches that they've lost all meaning. Instead, what actually matters when pitching to us: 1. Spend time living the problem. Bottom-up insights mean real anecdotes from the field - watching how customers actually behave, what workarounds they've created, the friction they've normalised. 2. Be willing to hold non-consensus views when your insights lead you there. We've backed companies that seemed odd at the time but made perfect sense given what the founder understood about their market. 3. Be networked enough to get a warm intro. If you can hustle your way in, you can hustle your way up. 4. Make the "why" feel inevitable. When you explain it, it should feel almost obvious in hindsight - but only because you've thought about it so deeply/spent considerable time with the consumers. Show us you've found something others missed. Everything else is secondary.

As a founder, you need to be deeply optimistic about the problem space but ruthlessly honest about your current approach. This is the fundamental difference between conviction and certainty, and I usually see these being mixed up way too often.

For years, Indian VCs worked within a limitation: we could deploy capital easily, but getting returns took much longer. Liquidity was slow, often stretching over a decade. Between 2022-24, a new gen of companies changed that - focusing on strong unit economics, lower burn, and sustainable growth. The result is a materially different IPO pipeline entering 2025. We’re seeing companies listed in 8–10 years instead of 12–15. This year has seen a fundamental reset of how Indian startups mature. @_groww is one of the best examples for this. Founded in 2017, profitable by FY25, IPO in late 2025. The ₹6,632 crore offering was oversubscribed 18x, but more telling was how it got there: it's one of those rare products that your parents, your younger cousin, and your neighborhood uncle all use. It's single-handedly responsible for pushing millions of Indians into investing. Groww's IPO is a milestone worth celebrating - and it signals that the entire ecosystem has matured with them. Founders now know what good unit economics look like. They’re thinking IPO-readiness from day 1. Institutional learnings from past cycles are finally compounding, and it’s showing.

Some of our best wins have come from simply introducing portfolio founders to each other - especially those tackling adjacent problems. These connections work well because trust already exists, and the incentive to help is real and not performative.

Everyone talks about India's digital infrastructure - UPI, Aadhaar, ONDC, but Meta owns the communication layer. Most Indians run businesses where WA downtime = business downtime. Why did China build sovereign communication infrastructure and India didn't? WeChat is killing it.

There’s been a lot of chatter about Meesho lately for all the right reasons. But everyone keeps counting Meesho's "pivots." I think there was just one - moving from hyperlocal fashion to reseller enablement. Everything else is their exceptional execution on vertical integration. And what makes that execution stand out is that they have consistently been early on every major move. Early on zero commission when marketplaces needed take rates to work. Early on discovery-led commerce when the playbook was search-first. Early on building Valmo when conventional wisdom said to outsource logistics. They integrated backward, forward, and into infrastructure - all while staying ahead of consensus. Backward into supply (attracting thousands of sellers of unbranded goods nobody else wanted), forward into demand (discovery feeds that work for smaller AOV baskets), and then into infrastructure with Valmo. While it's impressive they're processing 4.5M+ daily orders and heading to IPO with positive cash flow, what stands out most for me is this: most companies pick one integration path & execute. Meesho's been threading all three - consistently 1-2 years ahead of market consensus on each.

I read somewhere that we’re moving from a knowledge economy to an allocation economy. The shift is mainly because we’re no longer compensated for what we know, but for how well we orchestrate intelligence. I agree because no matter the role, we should now be able to answer: - Which problems deserve AI applied to them? - How do you combine multiple AI insights into a strategy? - What gaps is AI leaving that need human attention? Call it the judgment economy, the orchestration economy, the taste economy - the label doesn’t really matter. All we should know (and hopefully act upon) is that knowledge has become abundant, but curation is still scarce.

AI products have this weird catch 22: they need your data to improve, but most won't stick around long enough to give them that data in the first place. People won't sit through 10 bad recommendations waiting for #11 to be good - because masses don't think "oh, it's learning," they think "this doesn't work for me." This hits vertical apps especially hard because they need domain-specific patterns that are more gradual in nature

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Drivers, cooks, hotel owners - they already run everything on WhatsApp. They don’t need more complicated tools. They need tech that speaks their language, literally and culturally.

every business deals with at least one necessary evil for fashion brands, it’s RTO - 70% of customers feel uncomfortable purchasing from stores without a limited policy - reverse logistics can cost can be upto 20-40% and take anywhere from 12-25 days to

The Air India x Zomato partnership is so good! It taps into what you're already doing instead of forcing new behavior. I'm ordering food anyway - now I just need to do it on Zomato instead of Swiggy to stack flight points. I can already see people switching apps just for this.

There's this concept by @andrewchen that I really like - assessing the "nature vs nurture" of products, especially while evaluating retention. Some products will never be used daily, no matter how brilliant the execution. A hotel booking app can't become as habitual as Instagram, and a weather app won't match the engagement of gaming, despite having loyal users. Better to accept it early and design accordingly - optimise monetisation, find adjacent frequent use cases - than burn cash trying to make a quarterly-use product feel like Instagram.

Super excited for this. But the hardest part here will be getting users to trust it after a decade of OTP conditioning. We have been trained that "OTP = secure" - you receive a code, you enter it, the transaction goes through - there's a tangible sense of control. Even UPI penetration wasn't easy (if you avoid hindsight bias) - banks deployed armies of representatives to markets with QR codes. Over 100mn customer engagements. Government campaigns reached 400M+ Indians. While tech was great, it still took a comprehensive trust-building exercise. Our thesis has always stated that India runs on trust networks, not just tech. Face ID for payments is asking people to trust that their face is more secure than a 6-digit code they can see and control. Will be interesting to see whether convenience can overcome conditioning - but I'm hopeful.

Carrying on Rohan's legacy, one big hug at a time 💙

Every conversation about agent-led use cases eventually arrives at the same concern: "But will users trust AI to make decisions for them?” We’re past that stage; they already do. ChatGPT hit 100 million users faster than any product in history. People are paying for AI companions, using AI for therapy, letting AI manage their calendars, asking AI questions about their health - something you do only if you trust it. So clearly, the trust is already there - we've just been too focused on the technology to notice the behavior shift. Agentic AI will face other challenges - data quality, speed of learning, whether the tech can actually deliver on the promise - but trust won't be one of them.