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by Mia Farnham, Charles Hudson
Welcome to the Learning Corner, a weekly Precursor Ventures podcast, where members of the Precursor team walk through their favorite articles and news snippets across the venture ecosystem.
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This week Mia and Charles are joined by Precursor intern Aleena to dig into three good reads. First up, Ashley Smith's piece on the pressures young founders face today, including predatory incubators that trade small checks for outsized equity stakes. Then, YC's Fall 2026 Requests for Startups, featuring the first ever entry from a sitting US Secretary of the Army. They close with Frontier, a piece unpacking why AI labs stopped calling their models foundation models and started calling them frontier models, and what that shift reveals about how durable their moats really are.
This week on The Learning Corner, Mia and Charles dig into Nick Chirls' case for patience as an underrated venture strategy, using the owners versus tenants framing to explain why short term thinking is eating the industry. They then explore David Deming's argument that humans still hold a real edge over AI in social learning, especially in reading people and building trust from just a handful of interactions. The episode closes with George Sivulka's provocative piece comparing AI agents to a workforce, drawing parallels between tokenmaxxing and headcount bloat, and looping and meetings about meetings. Tune in for a conversation on long term thinking, the future of human judgment, and how to actually manage an AI agent workforce well.
This week Mia and Charles dig into whether using AI tools means quietly giving away your most valuable knowledge, what Sierra learned building a single company wide AI agent instead of one per department, and why data, not tokens, might be the next trillion dollar category in AI. They also touch on New York's new one year moratorium on large data center construction. Tune in for a debate filled conversation about what it really means to adopt AI at work today.
Is AI venture living through its biggest bubble yet, or its biggest winner-take-all cycle ever? Charles and Mia break down Samir Kaji's read on the duality driving valuations to record highs. They also dig into a Stanford field experiment proving cold pitches to investors work far more often than founders think, and challenge Tomasz Tunguz's take on why most startups don't actually have a real moat at founding. A fast, sharp look at three ideas shaping venture right now.
This week we dig into a piece from Halle Tecco exploring how healthcare VCs are splitting into two camps on ownership discipline as AI drives valuations to decade highs. We also break down Sam Lessin's argument that the SpaceX IPO signals the end of the DCF as the only globally scalable story of value, and what it means that minority belief systems can now pool conviction at trillion-dollar scale. We close with Sarah Guo's "The Untrainable," a sharp framework for understanding where real moats exist in the AI era and why the defensible work is exactly the stuff that can't be benchmarked. Tune in for a packed episode touching on venture math, narrative-driven markets, and what it actually takes to build something durable when the models keep getting smarter.
This week we featured Tony Fadell's interview with Lenny Rachitsky, covering how great products are built with pain at the center and why fast software is the new fast fashion. We also dig into Hunter Walk's practical framework for how early-stage VCs should communicate SAFE note markups to their LPs. And we close out with Reuters' reporting on Kirkland and Ellis committing $500 million to build a fully proprietary AI platform, and what that signals about where the legal industry is heading.
This week on The Learning Corner, economist Alex Imas makes a counterintuitive case that AI will not eliminate human labor but instead relocate scarcity toward a "relational sector" of nurses, teachers, craftspeople, and care workers where human presence is the product itself. Lisa Kostova shares one of the most honest accounts of vibe coding gone wrong, arriving at a major conference with 40 ready buyers and a product too broken to sell. We close with Boris Cherny, creator of Claude Code at Anthropic, who argues the title of software engineer is dissolving but predicts 100 times more people will be writing code in the near future. Three reads, one big question: what does human work actually look like in an AI economy?
This week on The Learning Corner, we dig into Rachel Karten's viral piece on AI-obsessed leadership and what happens when organizations adopt AI without any real strategy. We then discuss Karan Dhir's framework for career bets that actually compound versus the ones that just look like progress, including a debate on whether the AI era has quietly rehabilitated the generalist. We close with Charlie Warzel's Atlantic piece on AI malaise and whether the anxiety around AI is actually a geography problem more than a technology one.
Welcome to the Learning Corner, a weekly Precursor Ventures podcast, where members of the Precursor team walk through their favorite articles and news snippets across the venture ecosystem.
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