The Learning Corner by Precursor

The Learning Corner by Precursor

By Mia Farnham, Charles HudsonBusinessTechnologyInvesting
Download on the App Store

The Learning Corner by Precursor episodes

  • Episode #50: What Does ARR Mean?, High Agency in Silicon Valley, Debt Fueling The Next AI Wave
    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.

    ​​[Founders are using creative accounting to boost lofty ‘ARR’—the hottest startup metric in Silicon Valley | Fortune] (https://fortune.com/2025/09/28/how-is-arr-calculated-startups-venture/)

    [Are you high-agency or an NPC? | Jasmine Sun] (https://jasmi.news/p/dictionary?utm_campaign=post&utm_medium=web)
    [Debt Is Fueling the Next Wave of the AI Boom | Wall Street Journal] (https://www.wsj.com/tech/ai/debt-is-fueling-the-next-wave-of-the-ai-boom-278d0e04?st=KWeTHZ&reflink=desktopwebshare_permalink)

    (0:00) Introduction and founder work habits
    (0:46) ARR murkiness and AI gold rush
    (2:20) Inflated ARR and valuation impacts
    (5:19) Due diligence challenges and competitive deals
    (7:09) AI churn rates and gross margins comparison
    (8:36) Investor strategies and fraud speculation
    (9:30) Key cultural terms and tech landscape seriousness
    (12:09) Nine nine six work culture and San Francisco living
    (16:21) Intense work periods and fear of underclass
    (18:48) Debt's role in AI growth and tech bubble concerns
    (22:04) Credit dynamics, data center risks, and venture disconnect
    24 min
  • Episode #49: Making Money on AI, Consumer Deserves Attention from Investors, Nvidia Invests in OpenAI
    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.

    AI Will Not Make You Rich

    Consumer Businesses Are Stronger than Ever… Where Are the Investors?
    Nvidia to Invest $100 Billion in OpenAI

    (0:00) Introduction and frenzy stage in tech investment
    (0:48) AI and tech waves
    (2:02) AI's potential value capture and software pricing impact
    (5:21) Consumer tech investments and why VCs stay away
    (10:09) AI-driven personalization in consumer tech and NVIDIA's investment in OpenAI
    (15:22) Tech giants' relationships and AI infrastructure's future
    19 min
  • Episode #48: VCs are Cockroaches, Engineers Fixing Vibe-Coded Projects, Serial Entrepreneurs Continue to be Favored
    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.
    1. VCs Are Cockroaches

    By Micah Rosenbloom at Founder Collective

    2. The Software Engineers Paid to Fix Vibe Coded Messes

    By Emanuel Maiberg at 404 Media

    3. Why Serial Founders Still Have a Fundraising Edge Over First-Timers

    By Jacob Robbins at Pitchbook

    (0:00) Introduction and Venture industry feedback loop
    (0:43) LinkedIn post and VC resilience discussion
    (4:08) Merging and acquiring venture firms and first fund performance
    (8:02) Article on vibe coding, software engineers, and AI impact
    (14:09) PitchBook piece on serial founders and competitive dynamics in venture
    (18:02) Portfolio success and evaluating second time founders
    (19:43) Strengths and weaknesses of different founder profiles
    (20:10) Closing remarks and farewell
    21 min
  • Episode #47: We Are The Enemy, The AI Productivity Paradox, Anthropic's Author Class Action
    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.
    Articles Discussed

    1. We Have Met the Enemy and He Is Us
      Euclid Ventures explores the rise of consensus-driven investing in venture capital and its impact on innovation.

    2. The AI Productivity Paradox: High Adoption, Low Transformation
      Sequoia’s Inference dives into why AI tools are widely adopted but haven’t yet translated into meaningful productivity gains.

    3. Anthropic Agrees to Pay $1.5 Billion to Settle Author Class Action
      Reuters reports on a landmark copyright settlement in the AI space, raising big questions around fair use and model training.

      4. (0:00) Introduction and episode overview
      (0:43) Big funds' impact on seed stage and venture capital concentration
      (3:38) Advice for emerging fund managers
      (5:20) Sequoia's AI productivity paradox and enterprise AI transformation challenges
      (10:58) Anthropic's author class action and fair use debate in AI
      (16:13) Prioritizing for founders in creative spaces
      (17:34) Closing remarks and thank yous
      18 min
    4. Episode #46: AI Troubles for Taco Bell, Is Non-Consensus Dangerous, Are Software Economics Going Off a Cliff with AI
      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.
      • Taco Bell Rethinks Future of Voice AI at the Drive-Through (WSJ)
      • Martin Casado on Non-Consensus Investing (X)
      • Sam Schillace: Has the economics of software run off a cliff with AI? (Substack)
        • (0:18) Introduction to the Learning Corner podcast
        (0:48) Taco Bell's bumpy rollout of voice AI and its broader implications
        (3:19) AI in healthcare, fintech, and the future of engineering
        (6:09) The nuances of contrarian and nonconsensus investing
        (10:09) Consensus in later-stage investing
        (12:46) Sam Schillis on AI's impact on software economics and changing business models
        (18:36) Closing remarks and thank yous
        19 min
      • Episode #45: Hire the experimenters, Lessons from "failed" enterprise AI pilots, Valuations soar past the 2021 bubble
        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?
        • Hire the Experimenters
        • MIT report: 95% of generative AI pilots at companies are failing
        • Startup valuations: A 2021 bubble revival? | Peter Walker on LinkedIn
          • (0:00) Industry trends and technology adoption overview
          (0:11) Introduction and hosts
          (0:41) Hiring experimenters and new moats in business
          (1:40) AI investing insights with Charles Hudson
          (4:18) Navigating high-capital environments and startup paths
          (8:00) Startup creation strategies and generative AI deployments
          (10:31) AI resource allocation and vendor solutions
          (15:28) Startup valuations and investment trends
          (19:13) Entry prices, VC competition, and closing remarks
          21 min
        • Episode #44: Founding Engineers Are Impossible To Hire, Regulators Come For AI Therapy Chatbots, What VCs Get Wrong About Hiring
          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.

          • ‘The hot girl at the club’: How founding engineers became Silicon Valley’s biggest catch (Rya Jetha, The San Francisco Standard)

          • The states are coming for AI therapy bots (Casey Newton, Platformer News)

          • Why most VC firms hire associates wrong (and what we do instead) (Mike Dauber, Amplify Partners)

            • (0:19) Introduction and welcome
            (0:57) Founding engineers in the AI era & Equity packages
            (7:45) Changing expectations for founding engineers
            (10:05) The states are coming for AI therapy bots & The responsibility for AI therapy tools
            (18:13) Strategy for hiring in venture capital & The challenge of getting into VC
            (25:13) Differences between big consulting and boutique funds & Flexibility in hiring
            (25:53) Closing remarks and thank yous
            27 min
          • Episode #43: Two Silicon Valley Modalities, Are VCs Independent Thinkers?, 20 Somethings Swarming SF
            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.

            • Two Modalities of Competition in Silicon Valley (Aditya Agarwal, LinkedIn)

            • VCs Love to Claim They're Independent Thinkers. The Data is More Complicated (Rosie Bradbury, PitchBook)

            • Swarming to San Francisco’s A.I. Boom: A New Crop of 20-Something CEOs (New York Times)

              • (0:00) Introduction and market winners unpredictability
              (0:47) Startup competition and AI company dimensions
              (6:00) Venture competition evolution and VC collaboration trends
              (12:39) LPs' expectations and co-investing dynamics
              (16:18) Consumer fintech resurgence and AI founders in SF
              (18:46) College admissions, entrepreneurship trade-offs, and young founders
              (21:12) Early-stage customer acquisition and founder visibility
              (23:22) Ethical considerations in entrepreneurship encouragement
              (24:18) Closing remarks
              25 min
            • Episode #42: The "Winners" in AI Today, DaaS Is Not Venture Backable, Seed Rounds Grow As Startups Shrink
              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.

              AI Market Clarity (Elad Gil)

              Data is Actually Not a Great VC-Backed Business (Auren Hoffman)
              Why Seed Rounds Are Growing as Startups Shrink (Tomasz Tunguz)

              (0:00) Introduction and welcome
              (0:41) AI markets ripe for disruption and impact of not being a big-name AI fund
              (1:30) Conviction in capital and customer markets
              (3:11) Portfolio company conflicts in venture capital
              (5:22) Emerging markets, challenges in AI, and data businesses in venture capital
              (10:05) Challenges and successes in data business scalability and market trust
              (13:18) Seed rounds: growth, driving forces, and expectations
              (17:18) Benefits and challenges of larger seed rounds
              (18:41) Closing remarks and gratitude
              19 min
            • Episode #41: Investor to Fund Manager, Picking the RIGHT Capital, Seed Is Experiencing A Crisis
              This week on The Learning Corner, we dive into the evolving reality of seed-stage venture capital.
              We kick things off with takeaways from the Superclusters podcast, where the team at Screendoor shares what LPs are really looking for in emerging fund managers today. Charles reflects on how the role of a fund manager shifts as firms scale, and what skills matter most beyond just investing.
              Next, we unpack a thoughtful post by Halfdays founder Ariana Ferwerda on how founders should approach choosing investors. We discuss the subtle red flags that surface post-term sheet and what questions can help founders protect their long-term vision.
              Finally, we break down Rob Go’s post on the existential moment facing seed VC, exploring whether this is just a temporary reset or a long-term shift in how early-stage investing works.
              Whether you’re a founder navigating early fundraising or a VC trying to adapt in a changing market, this episode offers timely insight from both sides of the table.
              • Should VCs Scale? | El Pack w/ Screendoor (Superclusters)
              • The People Behind the Capital (Ariana Ferwerda, Over and Out Substack)
              • A Crisis Moment for Seed VC (Rob Go, NextView)
                • (0:00) Introduction and Welcome by Charles Hudson and Mia Farnham
                (0:54) Evolution of venture capital role and the three-part job of running a venture fund
                (6:51) Evaluating fund managers, LP-GP relationships, and choosing the right investors
                (15:46) Handling disruptive investors and pitch meeting approaches
                (18:54) Rob Go's insights on the future of seed VC and venture capital concentration
                (23:16) Potential winners in venture capital and alpha ratios
                (24:56) Closing remarks and thank yous
                26 min

              About The Learning Corner by Precursor

              From the publisher's feed

              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.