Invest Like the Best, EP.450: David George – Building a16z Growth, Investing Across the AI Stack, and Why Markets Misprice Growth

Podcast: Invest Like the Best with Patrick O'Shaughnessy
Host: Patrick O'Shaughnessy
Guest: David George, General Partner at Andreessen Horowitz (a16z)
Date: December 2, 2025

Episode Overview

In this episode, Patrick O’Shaughnessy sits down with David George, a16z’s Growth General Partner. The discussion is a deep dive into how a16z's growth investing team operates, their unique approach to identifying and backing world-changing companies across the AI stack, lessons from historic platform shifts, the anatomy of a Yankees-level culture, and why high consistent growth is so often mispriced in the market. The conversation covers investment philosophy, team-building, the future of AI, the specifics of competition in venture capital, and concrete attributes that separate "pull" businesses from merely good ones. Listeners will discover how a16z makes decisions, approaches founders, and decides when to sell positions.

Key Discussion Points and Insights

1. The Near to Medium-Term Future: AI’s Expanding Impact

[05:40]

• AI Across the Stack: David breaks down a16z’s strategy—investing from the model, through infrastructure, to applications.
  • Quote: “We've backed a ton of really exciting companies at every layer of the stack and we can talk about that and that's been part of our strategy.” – David George (05:45)
• Consumer AI has huge untapped potential, but it’s early. ChatGPT is the dominant brand, yet the future won’t be chatbot-centric—expect proactive, multimodal, and long-memory systems.
  • Quote: “I don't think that the future of how we interact with AI is going to be a chatbot... The big shift will be what is reactive today to something that's proactive in the future.” – David George (06:28)
• Monetization is wide open: Billions use ChatGPT, but only a fraction pay. Figuring out native monetization is an open challenge—ads may not be the answer.
• Historical analogies: Companies like Google and Facebook blew past their early perceived user monetization ceilings.

2. The Real Monetization Opportunities in Enterprise AI

[10:20]

• Skepticism about enterprise AI business models: Most surplus will accrue to users, not vendors, echoing lessons from past platform shifts—think of the steam engine.
• Easiest verticals: Customer support and coding, where clear metrics allow for consumption- or success-based pricing.
  • Quote: “90% of the technological surplus is going to go to the end users. Just start with that as the assumption whether it's consumer, whether it's enterprise.” – David George (11:43)

3. Investing in Hard Tech: Robotics and "American Dynamism"

[14:06]

• Robotics > Autonomous Vehicles in complexity: Home robots have many more "degrees of freedom" and will take longer to materialize than autonomous cars.
• Waymo as a case study: a16z’s first investment in 2020 was based on “seeing the future”—but it took years for market and technology to catch up.
  • Quote: “Stop overthinking it... This is autonomous driving. Are you kidding me? This is the mother of all markets.” – Mark/Ben to David George (16:52)

4. Investment Philosophy and the "Technical Terminator"

[18:19]

• Philosophy: Pay fair prices for great companies—recognize greatness early where the market is "underpricing" it.
• Edge is in people, products, and markets—especially founder archetypes:
  • Loves the "Technical Terminator": deeply technical founders who learn to become outstanding business leaders (e.g., Ali from Databricks, Mark Zuckerberg, Elon Musk, Dylan from Figma).
• Exception to the rule: Markets with pure competition (e.g., Travis at Uber), where a different founder archetype is more suited.

5. The Power of Market Leadership and the "Glengarry Glen Ross" Analogy

[22:37]

• Market leadership is critical: Most value accrues to the leader—number 2 wins rarely pay off, especially in tech and networked markets. This even holds true in many enterprise SaaS niches.

6. Competitive Dynamics and the Barbell of Venture Capital

[27:13]

• Venture capital is now a "grown up" asset class: Tech dominates public markets; private market cap is ~25% of S&P 500.
• Competition: a16z faces fierce battles with both multi-stage "superstores" and highly specialized "Gucci stores."
• How a16z wins deals: Years of relationship-building, intense founder support before investing ("helping them as if we were already investors"). Relentless value-add is the core differentiator.
  • Quote: “The reality of the growth stage business is we win deals based on years of relationship building.” – David George (30:33)
• Figma example: Demonstrates integrating product/market/deep industry insights to win deals where traditional financial analysis might miss the big opportunity.

7. Day-to-Day as a Growth Partner: Leverage, Learning, and “Game Film”

[35:38]

• Calendar discipline: Learning from Bob Swan, David aims to cut 30% of standing commitments yearly to focus on high-leverage activity.
• Time allocation: Majority is spent on emerging companies/AI founders, minority on established investments.
• Meeting style: Short intros; focus on founder vision, then deep questioning.
• Team size/culture: a16z’s growth team is intentionally small (~10 investors), thrives on collaboration and collective investment judgment from all levels.

8. Investment Committee and Decision Process

[41:35]

• No traditional committee: Single-trigger-puller model, encourages candor, speed, responsibility, and rigor; decisions can happen anywhere, not just on Mondays.
• Culture: Draws from the Yankees—high performance, high expectations, but collaborative.
  • Quote: “We are the Yankees and we're going to act like it... if you're on the Yankees, you better be performing. This is the big stage.” – David George (39:30)

9. Conditions for Optimal Growth Investing

[45:04]

• Best environment: Early product cycle, even amid poor capital cycles; new technology waves are the "golden time" (e.g., mobile, cloud, SaaS circa ~2010).
• Pitfall: Biggest missteps come from investing late in the cycle (as in 2021).

10. Why Markets Misprice High Growth

[47:42]

• Persistent high growth is under-modeled: Investors underestimate the duration/magnitude of sustained growth (the “model busters”).
  • Quote: “It's just so hard for any investor to build a five or ten year model where high growth persists... It's just not natural.” – David George (47:49)
• Case: Consensus in 2009 underestimated Apple’s 2013 numbers by 3x.

11. "Pull" Businesses vs. "Push" Businesses

[49:11]

• “Is the market demanding more of your product?” is the central question (post-it note on David’s monitor).
• Examples: Roblox, Anduril, and Cursor illustrate the viral, organic demand that creates category-defining winners.
• For enterprise AI, customer acquisition and engagement must be easy and durable; gross margins are currently less relevant but will matter more over time as costs (especially inference) decline.
• Quote: “Ease of customer acquisition is sort of a must for us in this AI wave...” – David George (51:20)

12. Product vs. Distribution Uniqueness

[54:32]

• Greatest companies have both: Unique products lead to unique distribution as in Cursor and GitHub (where deals happened with zero sales calls).

13. a16z’s Structure: Trade-Offs of Scale and Specialization

[57:20]

• Decentralized, specialized funds have improved investing expertise, though some cross-fund information flow is lost.

14. Investment Sourcing, Reservations, and Selectivity

[59:20]

• 70% of investments tie into prior company or fund knowledge ("game film").
• Reserving: Minimal for growth fund; every major follow-on treated as a new investment.

15. The Art and Challenge of Selling

[61:10]

• No rigid rules: Sale decisions weigh founder involvement, market leadership, relative valuation, and qualitative factors.
• Cultural fit: a16z prefers backing upstarts; buyout funds or buying incumbents clash with their ethos.

16. How Upstarts Beat Incumbents

[63:08]

• Business model shifts (especially tied to new UIs or data) are the hardest for incumbents to counter.
• Example: The future Salesforce challenger will win with a proactive, AI-driven, reimagined UI and new data sources.

Notable Quotes & Memorable Moments

• On AI’s consumer future:
  “I think the way that we interact with all this stuff is going to change dramatically. It’s going to have long form memory, it’s going to be multimodal and it’s going to be proactive.” – David George (06:32)

• On surplus distribution:
  “90% of the technological surplus is going to go to the end users. Just start with that as the assumption whether it's consumer, whether it's enterprise.” – David George (11:43)

• On investment edge:
  “You can get edge from product insights, market insights, and people insights.” – David George (18:39)

• On founder archetypes:
  “I call him the Technical Terminator... those are the people that are likely to figure out the next product area because they're technical.” – David George (19:31)

• On market leadership:
  “We've adopted that [Glengarry Glen Ross] as a way of describing most of the technology markets that we live in...most of the market cap creation is going to go to the market leader.” – David George (23:20)

• On private market evolution:
  “The industry is real. It shouldn’t be a surprise that the competition has intensified.” – David George (28:48)

• On relationship building:
  “We win deals based on years of relationship building.” – David George (30:33)

• On what makes a great pull business:
  “Is the market demanding more of your product? It's the most special thing when it happens.” – David George (49:18)

• On unique product/distribution:
  “Every great company either has unique product or unique distribution. The best companies in the world have both.” – David George (54:37)

Timestamps for Key Segments

• 05:40 – David on AI's future, consumer/enterprise split, ChatGPT's opportunity
• 10:20 – Where David’s views diverge, enterprise AI business models
• 14:06 – Investing in robotics, the Waymo case
• 18:19 – David’s investment philosophy and the "Technical Terminator"
• 22:37 – Lessons from missed investments, market leadership, Glengarry Glen Ross analogy
• 27:13 – How competition in VC has changed, "grown up" asset class
• 30:33 – How a16z actually wins deals: extreme relationship investment
• 35:38 – What David’s daily life looks like, time allocation, meeting style
• 39:30 – a16z as the Yankees: culture and expectation
• 41:35 – Investment process at a16z: no committees, fast, transparent decisions
• 45:04 – Market cycles, optimal growth investing conditions
• 47:42 – Why consistent high growth is mispriced
• 49:11 – Push vs pull businesses, AI company evaluation in 2025
• 54:32 – Product vs. distribution uniqueness with examples
• 57:20 – Structure of a16z, trade-offs of decentralization
• 59:20 – Prior investments (“game film”), reserving philosophy
• 61:10 – Selling positions: how, when, and why
• 63:08 – How upstarts beat incumbents: UI, business model, data shifts

Tone and Style

The conversation is candid, intellectual, and direct—blending strategic macro lens with inside-baseball anecdotes and actionable wisdom for investors, founders, and operator-listeners alike. Each point is reinforced with real examples, stories from the trenches, and David's self-professed "obsession" with finding and backing transformational people and companies.

Closing Anecdote

[66:01] – David reflects on the kindness of his parents supporting his childhood, underscoring the role of parental support and sacrifice in shaping his character and career.

This summary is designed for professionals and enthusiasts who may not have time to listen to the full episode, but want a tight, insightful overview of David George’s investment philosophy, a16z’s approach, and what it takes to win in the competitive growth investing landscape of 2025.