“None of these social trends are monocausal: the cost of childcare has increased, it's hard to raise kids far away from your parents and intergenerational community more broadly, there are fewer walkable cities than ever, etc. Parenthood, birth, and pregnancy are mostly told of in stories of the negative extreme. Birth is treated like a medical event, a risk, a threat — rather than something wondrous, natural, and empowering. Children are to be kept in a glass case and all of society is to support the ultimate goal of lifelong risk mitigation for them and on behalf of the parents.”

Are Pre-Seed VCs Pattern Matching Their Way Out of the Best Deals? After 70+ conversations with pre-seed investors this month, I've noticed something that's been bugging me. Most pre-seed VCs are obsessed with pattern matching. They pride themselves on hunting in the "right" places and evaluating Founders to find the mythical 1%ers. But here's the thing: Since venture has more failures than successes, pattern recognition will almost always point you toward reasons NOT to invest. Think about it. Almost every exceptional company traveled a path that would have failed traditional pattern recognition. The patterns tell you what worked before, not what will work next. Rather than ask "does this fit the pattern", the better question is "how much can we learn, for how much, and how quickly?" Sure, pattern matching might help you find the super competitive hot deal that gets you a quick markup and makes you look good to fellow Investors and LPs. But the returns on these deals rarely match what you can find living in the non-consensus world with companies that turn over cards efficiently. History proves this over and over: The best company formed in any calendar year rarely exists in the hottest category of that year. If you've got a fantastically compelling long-term vision, and you can identify the 4-5 critical assumptions that determine whether an idea could become a great business, then ask yourself: Can you test those assumptions for $1 and 1 day? If yes, you should invest. Of course, it never actually costs $1 and never takes 1 day, but that's where skill and experience comes in. You should lean into Startups that are efficient from a learning perspective. Velocity of learning matters. Cost of learning matters. Running experiments that generate definitive proof or anti-proof matters. The best investments are high potential non-consensus ideas that you can buy at non-consensus prices. The best investments flip from non-consensus to consensus on a single check if the key assumptions prove correct. The art of true early stage Venture Capital is about turning over cards efficiently, not about recognizing old patterns. My suggestion: Care about learning velocity, not pattern matching. Care about the long-term vision and the capital efficiency of de-risking core assumptions. The truth is that the 1%ers aren't hiding in plain sight waiting to be pattern-matched. They're building something the patterns would tell you to avoid. Onwards and Upwards, Fintechjunkie

.@jacobkimmel thinks that the functionality to reverse aging already exists in our epigenome. But then why didn't evolution already optimize for longevity? Jacob explains that if you consider evolution as an optimizer, the gradients flow in a really surprising way. Naively, it seems like evolution should want you to live longer (more time to have babies and care for your kin). Jacob explains 3 complications on the naive picture: 1. Baseline mortality was brutal throughout most of history. Even without aging, you'd likely die from infection, predation, or accident before reaching 50. So there's no signal flowing back from 100 to the genome which incentivizes some selective process to make you live longer, even if it was easy to do. 2. There's selection against fixing just one (but not at all) causes of aging). Because then you have some grandpa who's slightly healthier but still a worse use of resources than the next generation from the gene's eye point of view. 3. Evolution is very limited as an optimizer. The step size (number of variants you can test in parallel) is limited by your step size. And through the most of history, this bandwidth was dominated by selective pressures much more urgent than de-aging (for example, building a better immune system to fight infectious diseases). Full episode with @jacobkimmel out Thursday. So excited about this one. Jacob's simple 3-point list led to more than half an hour of random digressions, from how many antibiotics were naturally evolved, to how hard evolution actually optimized for intelligence, to how we can actually detect the evidence for some deadly ancestor of HIV in our genome.

Former Founders Fund colleagues turned bitter venture rivals. @zebulgar and @everettrandle have bet their careers on wildly different industries. Today they will join TBPN together at 11am pacific to debate gross margins, AI, hard tech, accounting rules and more.

on global cultural shift, from an indian friend: ‘India was colonized for 200-300 years, yet successfully preserved much of its culture. But in just 15 years of the Internet, I’ve seen significant, if not greater, change in India’s dress, food habits, values, and culture.’