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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.
61 Episodes
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This week we unpack the viral AI food delivery hoax that fooled thousands on Reddit and what it reveals about misinformation in 2026. We discuss the crisis of career fulfillment in tech as layoffs continue while startups struggle to find talent. Finally, Roger Ehrenberg shares an honest take on the insecurities every venture investor faces and why playing your own game matters more than ever.
This end‑of‑year episode of The Learning Corner by Precursor brings together our first podcast guests, Hunter Walk (Homebrew, Screendoor) and Peter Walker (Carta) for a wide‑ranging conversation on how venture capital has evolved in 2025. We unpack ballooning early‑stage valuations, the distortion created by media attention, and how few companies actually sit at the top of the market. We also discuss today’s exit landscape, growing pressure for liquidity, the rise of secondaries, and what recent IPOs and M&A activity mean for funds of different sizes. We close by examining what early‑stage venture really looks like today, from changing GP‑LP dynamics to faster paths to scale and the push to build more with smaller teams.
In this week’s episode, we break down Ben Casnocha’s shift in thinking on whether good ideas matter more than good founders, Aaron Harris’ challenge to the “missionary founder” trope, and Jonathon Ready’s exploration of why AI is getting eye rolls from engineers in Seattle. We discuss how these takes intersect with early-stage investing and what signals we should be looking for as the startup landscape keeps evolving.
In this episode of The Learning Corner by Precursor, Mia Farnham is joined by Charles Hudson and Missy Martin to unpack three timely reads. First, we explore Charles Schwab’s $660M acquisition of Forge Global and what it signals about the mainstreaming of alternative assets for retail investors. Next, we dig into TechCrunch’s coverage of “venture zombies” and the rise of “hold forever” investors acquiring stalled startups. Finally, we reflect on a powerful essay by Sinéad O’Sullivan that reframes burnout as an identity collapse—not a productivity issue—and what that means for founders, operators, and investors alike.
This week on The Learning Corner by Precursor, Mia Farnham and Charles Hudson dive into three thought-provoking reads shaking up the venture ecosystem:
First, we break down Ben Zises’ take on why consistent founder updates may signal future success — and why that doesn’t always align with our own portfolio data.
Next, we explore M.G. Siegler’s “Hey, There’s a Bubble” and what today’s AI funding frenzy reveals about hype cycles, economic dissonance, and the uneasy optimism baked into bubbles.
Finally, we unpack Kyle Harrison’s “Build What’s Fundable” and its take on YC’s shifting tone, consensus capital, and the rising prevalence of ‘slop startups’—and what it means for early-stage builders trying to think independently in a world that rewards conformity.
We kick things off with a short but sharp post from Ben Choi reminding us that “VC is hard”—not just because of performance pressure, but because navigating fund dynamics and relationships is a game in itself. Then we dive into a provocative piece by Stefano Bernardi questioning the obsession with concentrated funds, and unpack why diversification often outperforms even the best instincts. Finally, we revisit the Cluely hype cycle, with CEO Roy Lee reflecting on the downside of viral traction and what happens when the market stops being impressed.
This week on The Learning Corner, Mia and Charles break down four of the most thought-provoking reads shaping the tech and venture ecosystem right now:
• Unsafe SAFEs in the Age of AI: Jason Lemkin calls out a troubling new trend where founders in hyped AI deals walk away with investor cash—without building a thing.
• 15 Charts That Explain How Tech and Venture Are Changing in 2025: Ruben Dominguez drops a chart-heavy update covering everything from AI app churn to why so many junior VCs leave the industry.
• Oreo-maker Mondelez is using GenAI to slash marketing costs: Mondelez teams up with Publicis and Accenture to roll out a $40M AI tool, cutting costs—and possibly creativity—in CPG advertising.
• Sequoia Names New Co-Leads as Roelof Botha Steps Down: With Roelof Botha stepping down, Sequoia is signaling a new chapter
First up, we dive into “Beyond True or False: Teaching Students to Interrogate AI Unreliability”, a Substack by Nick Potkalitsky, which proposes a new framework—borrowed from literary theory—for teaching students to critically evaluate AI-generated content. We discuss how this lens can help people move beyond simple trust/distrust binaries and become better co-creators with AI.
Then, we explore “Is AI the New Shadow Bank? (Yes…)”, a piece that draws parallels between today’s AI economy and the pre-2008 shadow banking system. Instead of mortgage-backed securities, today’s collateral is GPU access, compute contracts, and foundation models—and we ask: is the real innovation the credit system AI is built on?
We’re digging into three thought-provoking topics shaping the current startup and investing landscape:
🧼 Coterie’s $650M Exit & the Return of DTC M&A – We break down Brian Sugar’s “One Brand is Luck, Two is Strategy,” and why pure-play DTC brands with strong economics and customer devotion are back on the radar for modern acquirers.
⚡️ Iteration Speed & the Path to Series A – Hadley Harris of Eniac Ventures shares why iteration speed is the best predictor of Series A readiness, and how founders can prioritize feedback loops and kill ideas quickly to increase their odds.
💸 Secondaries in Term Sheets – A recent Axios note suggests Menlo Ventures is now pre-negotiating secondary sale conditions into early-stage term sheets. We unpack what this means, why it matters, and whether this becomes a new norm.
This week on The Learning Corner, Mia and Charles discuss Goldman Sachs’ acquisition of Industry Ventures and what it signals for the venture ecosystem, Maria Gonzalez Blanch’s take on “brain obesity” in the age of AI, and a recent post from Erica Wenger about friends investing in friends. We break down what it means for community, trust, and evolving norms in tech.
In this week’s episode of The Learning Corner by Precursor, Mia and Charles explore three themes shaping today’s startup and VC landscape:
The Three Lanes of Modern Venture – What type of fund are you really building? John Vrionis lays out three distinct approaches VCs are taking today.
When Great People Leave – How do strong leaders navigate inevitable departures? Lessons from Taps Notes on leadership, transitions, and grace.
The Solo Founder Debate – If solo founders can succeed, why don’t more VCs back them? Itamar Novick shares thoughts on survivorship bias and what makes solo builders special.
Tune in for a thoughtful discussion on the shifting expectations of investors, how to support teams through change, and why the solo founder conversation is evolving fast.
We start with a Fortune article on how founders are using “creative accounting” to boost ARR, once the gold standard for SaaS success and now a much murkier metric in the AI era. What used to be a reliable sign of recurring revenue has drifted into “vibe revenue,” and we talk about what that means for investors and founders trying to benchmark growth.
Next, we dive into Jasmine Sun’s blog on Silicon Valley’s cultural lexicon, “high agency,” “NPCs,” “996,” “taste,” and “decel/doomer.” These memes reflect deeper anxieties about meaning, ambition, and the pressure to win in today’s AI-driven world. We share our reactions to which of these terms resonate most, and what they say about tech culture right now.
Finally, we turn to the Wall Street Journal’s coverage of how debt is fueling the AI boom. With Oracle, CoreWeave, and others leveraging massive loans to secure infrastructure and power, we discuss whether this strategy is a smart bet on future demand or a dangerous setup for a bubble if growth slows.
We explore Jerry Neumann's "AI Will Not Make You Rich," which argues that transformative technologies like AI may not deliver lasting competitive advantages, using economist Carlota Perez's tech wave framework to examine whether we're in the "frenzy" or "irruption" stage of AI development.
Next, we dive into the curious disconnect in consumer tech markets, where VC funding has dropped from 15% to 5% of venture dollars despite consumer companies significantly outperforming the Nasdaq-100. Charles discusses why Precursor remains bullish on out-of-favor sectors and whether AI-powered personalization could revive investor interest in consumer tech.
Finally, we examine Nvidia's $100 billion investment in OpenAI and what this reveals about the interconnected web between chip makers, data centers, and AI companies.
This week on The Learning Corner, Mia and Charles explore three compelling venture capital topics: (1) Micah Rosenbloom's comparison of VCs to "cockroaches" and why fund consolidation remains unlikely despite market pressures, (2) the emerging trend of software engineers being paid to fix AI-generated "vibe-coded" projects that need human expertise to become functional, and (3) new Pitchbook data revealing how serial founders maintain a significant 2-3x fundraising advantage over first-time entrepreneurs in today's cautious investment climate.
First, we dive into “We Have Met the Enemy and He Is Us” by Euclid Ventures, which explores how venture capital is drifting from its roots as a market for independent thinkers.
Next up is “The AI Productivity Paradox” from Sequoia’s Inference, which explores why widespread AI adoption hasn’t translated into real productivity gains.
Lastly, we break down the recent Reuters story about Anthropic’s $1.5 billion settlement in a landmark author copyright case. Soon after we recorded, the Judge stepped in and rejected the settlement.
This week on The Learning Corner by Precursor, Mia and Charles dive into three major topics shaping the future of AI, startups, and software economics:
Taco Bell’s Voice AI Troubles: A WSJ piece reveals just how glitchy the chain’s drive-thru AI rollout has been—and why they’re rethinking it entirely. Charles shares why these failures might actually be a good sign of progress and what’s at stake when AI misfires in higher-risk industries like healthcare and finance.
The Myth of “Non-Consensus” Investing: A provocative thread from Martin Casado questions whether early-stage investors are placing too much faith in being contrarian. Is alpha really found in non-consensus bets—or does follow-on capital always chase what’s hot?
The Software Margin Cliff: A brilliant Substack from Sam Schillace suggests that AI is driving software economics off a cliff. As inference costs grow and traditional SaaS margins shrink, the industry may look more like manufacturing than the creative playground it used to be.
We kick off the episode by discussing Rebecca Kaden’s essay, “Hire the Experimenters”, which argues that speed, adaptability, and creative risk-taking are more valuable than traditional credentials in today’s AI-driven startup world. We explore how this mindset shift is reshaping what “great hiring” looks like for early teams — and whether that flexibility can translate into long-term defensibility.
Then we break down the MIT report on generative AI deployment across enterprise — and the not-so-great news that 95% of pilots are failing. Charles shares his opinion that these "failures" are signs of future success.
Finally, we look at Peter Walker’s data-packed breakdown of bubble-era valuations reappearing at Seed and Series A. With median valuations at the 99th percentile soaring past $160M for Seed and $700M+ for Series A, we ask: what does this mean for startups trying to raise now, and how do you tell signal from noise?
This week on The Learning Corner, we dig into the changing dynamics of talent, regulation, and hiring in venture. We start with the San Francisco Standard’s piece on why founding engineers are suddenly the most coveted hire in Silicon Valley, and how the expectations for technical co-founders have shifted post-AI.
Next, we explore Platformer News’s report on the political crackdown on AI therapy bots. As states move to regulate AI mental health tools, we debate where the line should be drawn between helpful support and unlicensed therapy, and what it means for builders in this space.
Finally, we unpack Amplify Partners’ post on why most VC firms hire associates wrong. Charles shares what he’s learned from hiring across multiple funds at Precursor, and we discuss what it looks like to truly invest in future partners from the earliest stages of their careers.
This week on The Learning Corner, we explore three perspectives shaping how startups get built and funded in today’s environment.
We start with Aditya Agarwal’s LinkedIn post on the two competing startup modalities in Silicon Valley: those building in legible, fast-moving spaces where speed is the moat, versus those tackling illegible, contrarian ideas that take longer to crystallize. We discuss how investors say they want one, but often fund the other.
Next, we dive into Rosie Bradbury’s PitchBook piece on whether VCs are truly independent thinkers. We break down new data showing how frequently top firms co-invest, and what it means for the myth of proprietary deal flow.
Finally, we unpack the New York Times’ coverage of the wave of 20-something founders flooding San Francisco to build AI startups. From teen dropouts to meme marketing, we reflect on how this boom compares to past cycles and what might be different this time around.
This week on The Learning Corner, we dive into three sharp pieces exploring the evolving shape of venture. We kick off with Elad Gil’s take on why AI markets are finally gaining clarity, with key winners emerging across foundational models, code, legal, and customer experience. We ask: can new entrants still break through if they’re not one of the early, well-capitalized names?
Next, we unpack Auren Hoffman’s argument that data businesses, while solid, often aren’t built for venture scale. As more investors rethink their appetite for pure-play DaaS models, we explore where data companies can still attract VC interest, especially as AI blurs the line between tooling and infrastructure.
Lastly, we discuss Tomasz Tunguz’s piece on why seed rounds are getting larger even as startups shrink. From inflated pre-seed valuations to AI-powered team efficiency, we reflect on the new expectations being placed on early-stage companies and where those pressures might lead next.
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