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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 on The Learning Corner, Mia and Charles dig into Gil Dibner's argument that venture has barbelled into two extremes, a tiny set of consensus darlings that can raise at any price and everyone else, who are increasingly paying pure gold prices for fool's gold. Then they turn to Dario Amodei's essay "We Must Pace the Frontier," the rare moment where Amodei, Sam Altman, and Elon Musk all agreed the AI industry needs to slow down. They unpack what "pacing" actually means, and whether it is good or bad news for the thousands of startups building on top of these models.
This week Mia and Charles dig into a market that only seems to have two speeds. Ethan Kurzweil of Chemistry argues the trillion dollar startup is a pink elephant nobody can unsee, and that the pedestrian double or triple has become a relic of a bygone era. David Cahn looks at what happens after the money lands: a generation of well funded teams with big visions and no clear steps to get there. Nikunj Kothari of FPV Ventures closes it out with a tactical playbook for founders raising this fall, from the number you say out loud to why VCs don't actually want a "deal."
This week we sit down with Nic Poulos, Co-Founder and General Partner at Euclid Ventures and one of the sharper voices on vertical AI, to pressure test the thesis as we head into the end of Q3. We dig into what defensibility actually looks like when any founder can spin up a vertical AI product in a weekend, why a $500M median exit is great math for some funds and tough math for others, and where "death of SaaS" narrative currently sits. Nic also revisits his 2026 predictions on deep tech fragmenting and religion as a vertical AI opportunity.
This week on The Learning Corner, Mia and Charles dig into how the rise of AI agents is paradoxically driving startup founders to work longer and harder than ever, with some monitoring their bots around the clock and describing the experience as nothing short of addictive. They then unpack a wave of CTOs and engineering leaders quietly walking away from their roles, driven by founder mode, preference stacks that have rendered equity nearly worthless, and the fact that AI labs like Anthropic are now paying individual contributors more than most executives make elsewhere. The episode closes with a sharp, timely read on what growth investors actually want right now: a credible path to a $20 billion company with you as the emerging winner, nothing more and nothing less.
This week on The Learning Corner, an observation from investor Matt Turck that startups today are either AI-native rocketships or left for dead opens up a real conversation about what that binary actually means for founders building outside the hype cycle. Michelle Volz's essay "To Be or To Do" uses military legend John Boyd's framework to argue that Silicon Valley has quietly shifted from rewarding builders to rewarding the performance of building, and why discipline is the actual path to the biggest outcomes. We finally close with Vinnie Lauria, Founding Partner at Golden Gate Ventures, who breaks down why a VC who already passed on your company is one of the worst people to introduce you to another investor and why credible signal matters far more than access in fundraising.
This week on The Learning Corner, Mia and Charles dig into Gil Dibner's argument that Series A investors have fundamentally abandoned their core function, opting instead to invest way too late, way too early, or simply accumulating options without conviction. They then unpack Sequoia's twenty-year hype analysis that shows the most valuable companies are almost never founded in the peak hype year of their category, and what today's signals might tell us about the next big wave. The episode closes with Maple VC's Talent Arbitrage framework and why the Builder, the nonlinear, hardest-to-categorize founder, is the most important and most overlooked signal in early stage investing.
This week on The Learning Corner, we dig into three pieces that all orbit the same uncomfortable question: who is actually accountable when things go wrong? Angela McNeal's "The Architecture of Blame" argues that AI does not invent accountability gaps, it industrializes them at machine speed across every workflow at once. New academic research reveals that VC-backed startups are statistically more likely to commit fraud, and that investors are not passive victims but active co-creators of the conditions that make it happen. We close with a Wall Street Journal investigation into how the AI talent war is turning founders into acquihire targets, with VCs now explicitly asking in diligence: will you quit on me?
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.
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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