Investing in Founder Strengths Amidst AI-Driven Market Shifts - Episode Hero Image

Investing in Founder Strengths Amidst AI-Driven Market Shifts

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TL;DR

  • Overweighting the fear of future theoretical competition can lead to missed investments, as demonstrated by the success of companies like 11 Labs and Deal, where backing exceptional founders with spiking strengths is paramount.
  • The venture capital asset class has fundamentally shifted, with significant value creation now occurring in later stages (Series C+), necessitating larger fund sizes and a focus on capturing winners in massive tech waves.
  • The proliferation of AI is driving a transition of spend from human labor to technology, evidenced by companies like C.H. Robinson achieving a 40% productivity increase and a 680 basis point margin expansion.
  • Rapid revenue scaling in AI companies requires a higher bar for assessment, focusing on engagement and retention as leading indicators of value rather than solely relying on historical growth metrics.
  • The diminishing number of public small-cap companies and deteriorating Return on Invested Capital (ROIC) in the public markets underscore the increasing importance of private markets for accessing high-quality growth opportunities.
  • Investing in strength of strengths, rather than solely addressing weaknesses, is a crucial philosophy, as demonstrated by the success of companies like Stripe and SpaceX, which leverage their leadership to attract further resources.
  • The market is evolving beyond models subsuming all software, with significant opportunities arising in building application software and services around AI capabilities, as seen in the radiology AI example.

Deep Dive

The a16z growth investing practice prioritizes backing companies with exceptional foundational strengths, even at high valuations, believing that market dynamics and AI advancements will create unprecedented company sizes. This approach challenges traditional venture capital metrics by focusing on durable market leadership and founder capabilities over immediate profitability, as evidenced by the firm's significant investments in AI and other transformative technologies. The implications are that investors must adapt to a landscape where private market opportunities dwarf public markets, and where identifying and supporting "strength of strengths" in founders is paramount for capturing future value.

The core of a16z's growth investing philosophy hinges on identifying companies with exceptional founders and market potential, often before the broader market recognizes it. This means embracing "strength of strengths" -- investing in founders who exhibit exceptional capabilities in critical areas like product, technology, and brand building, even if other weaknesses exist. This philosophy underpins their willingness to invest at high entry prices, particularly in the AI sector, where they anticipate the creation of some of the largest companies ever built. The rationale is that AI will fundamentally reshape industries, creating massive market opportunities that can sustain substantial valuations. This contrasts with a traditional fear-based approach that might shy away from investments due to perceived future competition, a pitfall the firm actively seeks to avoid.

The evolving private market landscape necessitates a shift in how investors assess opportunities. The private market's growth and the increasing trend of companies staying private longer mean that significant value creation now occurs before IPOs. This has led a16z to adapt its own business, requiring portfolio companies to be multi-product, multi-channel, and international, with AI accelerating these demands. For institutional investors, this blurring of lines between private and public markets suggests a re-evaluation of asset allocation, favoring venture capital's exposure to next-generation dominant companies that previously would have been public. The firm's data indicates that top-tier venture funds have historically outperformed private equity, a trend they expect to continue with AI driving even greater differentiation.

Furthermore, the rapid scaling of AI companies is forcing a re-evaluation of traditional metrics like revenue growth. While rapid revenue scaling is a positive indicator, a16z emphasizes high retention and engagement as crucial leading indicators for AI startups, given the difficulty in assessing long-term renewal behavior. This means a higher bar for evaluating these companies, focusing on organic customer acquisition and deep product engagement. The firm believes that market "pull" -- genuine customer demand -- is a more reliable driver of sustainable growth than a top-down sales approach. This focus on market pull, combined with a founder's ability to build a moat, is seen as critical for long-term success.

Finally, the firm views "king making" -- using capital and brand to anoint a winner -- as a supportive tool rather than a primary investment thesis. They invest in companies already demonstrating strength and market traction, believing their capital and endorsement can amplify existing advantages, such as preferential attachment and increasing returns to scale. This approach, while distinct from simply deploying capital as a weapon, aims to fortify market leaders. The firm's personal excitement for areas like proactive personal health management and robotics underscores their belief in future investable categories that, while early today, possess immense potential for societal and economic impact.

Action Items

  • Audit AI company retention: For 3-5 recent AI investments, analyze 6-12 month renewal behavior and engagement metrics to validate rapid growth.
  • Create founder strength assessment rubric: Define criteria for evaluating "strength of strengths" in founders, focusing on market insight, product knowledge, and execution aggression.
  • Measure AI productivity impact: For 2-3 companies implementing AI, quantify shipment or task completion increases per employee and corresponding operating margin changes.
  • Analyze market pull for AI startups: For 3-5 AI companies, assess organic customer acquisition or low-cost sales acquisition to validate market starvation for their products.
  • Evaluate AI model cost vs. usage: Track input costs per token and token usage for 2-3 AI applications to project future gross margin rationalization.

Related Episodes

Key Quotes

"if you overweight the fear of future theoretical competition you can always talk yourself out of making an investment the number one way to measure a company is ultimately return on invested capital on the the gross margin point today i'll say this we give a little bit more of a pass than we used to"

David George argues that an overemphasis on potential future competition can paralyze investment decisions. He highlights return on invested capital and gross margin as key metrics, though he notes a willingness to be more flexible on the latter for certain companies. This suggests a pragmatic approach to valuation, balancing traditional financial health with the unique dynamics of emerging sectors.

"private markets have grown 10x over 10 years right so it's over 5 trillion in market cap now in our market we actually just looked at the 50 top ipos from 2017 to 2025 and if you disaggregate where the dollars of return come from 47 of the dollars of gain happens between the seed and series b and 53 of the dollars of gain happen from series c plus"

David George points out the significant growth and scale of private markets, indicating a substantial shift in where value creation occurs. He presents data suggesting that a majority of investment gains now happen in later stages (Series C and beyond), challenging the traditional view that most value is created in early-stage investing. This highlights the increasing importance of growth-stage investing.

"tech waves tend to create massively different value i mean this is very well covered but the big story of mobile social sas cloud e commerce all at once was 20 25 trillion of market cap creation and if that started from scratch today given the public private market dynamic that i just described so much of that value creation would take place in the private markets"

David George emphasizes that technological shifts create immense market opportunities, referencing the previous wave of mobile, social, and cloud technologies that generated trillions in market cap. He posits that with the current private market dynamics, a similar or even larger wave of value creation would now largely occur within the private markets, underscoring the significance of private investing in today's landscape.

"the number of public companies has been cut in half over the last 20 years you know the companies that we're talking about many of them would already be in the public markets and they're not and so if you look at where the returns are getting generated the returns are actually getting generated in the private markets before they go to the public markets"

David George explains that the decreasing number of public companies means many high-growth businesses that might have gone public in the past now remain private for longer. He argues that this shift concentrates significant return generation within the private markets, making them a crucial area for investors seeking to capture this value before it potentially moves to public markets.

"we try really really hard not to do that other other mistakes if we if we passed on great companies you know it's not because they're you know the market leader it's not because they have a good business model it's because we think the market might be too small those are mistakes too like we always underestimate the size of a market and we have fun stories about that all over the place we do"

David George shares a common investing mistake: underestimating market size. He explains that even when passing on companies that appear strong in leadership or business model, the real error can be misjudging the total addressable market. This indicates a tendency for successful companies to expand markets beyond initial expectations, a factor investors must carefully consider.

"the number one way to measure a company is ultimately return on invested capital the way you do that with an early stage company mostly is efficiency of customer acquisition not every company needs to go you know zero to 100 like it depends on what market they're in but i do think the companies with ai if there's very sort of starving and customers high momentum gives you a chance to build a moat and i think that's the most important thing about this sort of debate about how high of growth is good enough it depends on what market you're in"

David George asserts that return on invested capital is the primary measure of a company's success, particularly emphasizing efficient customer acquisition for early-stage businesses. He believes that in fast-moving AI markets with high customer demand, companies have a greater opportunity to build a competitive moat, making rapid growth a critical indicator of potential success within those specific markets.

Resources

External Resources

Books

  • "The Hard Thing About Hard Things" by Ben Horowitz - Mentioned as a source for the philosophy of investing in "strength of strengths."

Articles & Papers

  • "The TAM Trap" (Source not specified) - Discussed as an analysis that suggests market sizes might be smaller than initially perceived.
  • New York Times Op-Ed (Source: New York Times) - Mentioned for an op-ed by a medical professional comparing Waymo's safety data to clinical trial approvals.

People

  • David George - General Partner at a16z, discussing growth investing, AI startups, and investment decision-making.
  • Harry Stebbings - Host of the 20VC podcast, interviewing David George.
  • Averett Randall - Mentioned in relation to a discussion about fund sizes and LP returns.
  • Kevin Cole - Mentioned as a guest on a podcast discussing NFL analytics.
  • John Collison - Mentioned for a quote about not wanting to go public.
  • Alex (Deal) - Mentioned as a relentless founder and deal customer.
  • Adam (Flow) - Mentioned as the founder of Flow, with strengths in brand building, company building, and product.
  • Maddie (11 Labs) - Mentioned as a founder of 11 Labs, a company a16z invested in.
  • Nomi (Character AI) - Mentioned as a founder of Character AI, whom a16z invested in early.
  • Brian Kim - Mentioned as part of the a16z growth funds team.
  • Anish - Mentioned as having led a Series A round for Deal.
  • Ben - Co-founder of Andreessen Horowitz, mentioned for his management coaching and understanding of executive dynamics.
  • Mark - Co-founder of Andreessen Horowitz, mentioned for his ability to see the future and expertise in consumer internet.
  • Dickson - Mentioned as having the clearest articulation of a16z's early-stage strategy.
  • Nat - Mentioned as having partnered with a16z.
  • Daniel - Mentioned as having partnered with a16z.
  • Lee Fixel - Mentioned for his ability to predict and forecast markets with a 10-year vision.
  • Fent - Mentioned for his clarity of thought.
  • Winston - Mentioned as an example of a founder with authenticity to their core domain and aggression.
  • Santiago - Mentioned as a partner who had dinner with Shiv.
  • Shiv (Abridge) - Mentioned as a founder of Abridge, a doctor and cardiologist with strong market, product, and technology knowledge.

Organizations & Institutions

  • a16z (Andreessen Horowitz) - Venture capital firm discussed for its growth investing practice, culture, and investment strategies.
  • OpenAI - AI startup discussed in relation to investment, market position, and potential.
  • Databricks - Company mentioned as a successful investment by a16z.
  • Figma - Company mentioned as a successful investment by a16z.
  • Stripe - Company mentioned as a successful investment by a16z.
  • SpaceX - Company mentioned as a successful investment by a16z.
  • Anduril - Company mentioned as a successful investment by a16z.
  • Cursor - AI startup mentioned as an investment by a16z.
  • Harvey - AI startup mentioned as an investment by a16z.
  • Abridge - AI startup mentioned as an investment by a16z.
  • NFL (National Football League) - Professional American football league discussed in relation to data analysis.
  • Pro Football Focus (PFF) - Data source for player grading.
  • New England Patriots - Professional football team mentioned as an example.
  • Flock Safety - Company mentioned in the context of competition with Axon.
  • Axon - Company mentioned in the context of competition with Flock Safety.
  • YC (Y Combinator) - Accelerator mentioned as a significant buy in venture capital, particularly for European companies.
  • 11 Labs - Company mentioned as a successful investment by a16z, with a focus on AI.
  • Character AI - Company mentioned as an early-stage investment by a16z.
  • Deal - Company mentioned as a potential investment and a "deal customer."
  • ADP - Company mentioned in the context of payroll services.
  • Paychecks.com - Company mentioned in the context of payroll services.
  • Google - Technology company discussed in relation to AI and market competition.
  • Facebook - Technology company discussed in relation to AI and market competition.
  • Microsoft - Company mentioned for reducing headcount.
  • Monday.com - Company mentioned in the context of enterprise software.
  • Duolingo - Company mentioned in the context of enterprise software.
  • Amazon - Company mentioned as a scale player in retail.
  • Walmart - Company mentioned as a scale player in retail.
  • Chanel - Company mentioned as a high-end retail brand.
  • Zegna - Company mentioned as a high-end retail brand.
  • Laura Piana - Mentioned in relation to high-end retail.
  • Decagon - Company mentioned as a strong performer in customer service AI.
  • Sierra - Company mentioned in the context of customer support software.
  • Twilio - Company mentioned in the context of SaaS.
  • PagerDuty - Company mentioned in the context of SaaS.
  • Dropbox - Company mentioned in the context of SaaS.
  • Waymo - Autonomous driving company discussed as a significant investment and future market leader.
  • Nvidia - Company mentioned as an early investment by SoftBank Vision Fund.
  • Slack - Company mentioned as an investment by SoftBank Vision Fund.
  • Garden - Company mentioned as an investment by SoftBank Vision Fund.
  • Uber - Company mentioned in the context of consumer markets and competition.
  • TikTok - Company mentioned in the context of consumer markets.
  • Revolut - Company mentioned as an error of omission for the speaker.
  • Anthropic - AI company discussed as a competitor to OpenAI, particularly in B2B.
  • AWS (Amazon Web Services) - Cloud computing service.
  • Azure - Cloud computing service.
  • GCP (Google Cloud Platform) - Cloud computing service.
  • Hummingbird - Seed fund mentioned.
  • Benchmark - Venture capital firm.
  • Founders Fund - Venture capital firm.
  • Napoleon - Mentioned in relation to venture capital firms.

Tools & Software

  • ChatGPT - AI model discussed for its capabilities and market impact.
  • GPT - AI model discussed.

Websites & Online Resources

  • a16z.com - Mentioned as the source for the podcast.
  • a16z substack.com - Mentioned for subscribing to their substack.
  • youtube.com - Mentioned as a platform for the podcast.
  • podcasts.apple.com - Mentioned as a platform for the podcast.
  • spotify.com - Mentioned as a platform for the podcast.

Other Resources

  • AI (Artificial Intelligence) - Central theme of the discussion, covering its impact on business, investment, and future markets.
  • Growth Investing - Investment strategy discussed by David George.
  • Return on Invested Capital (ROIC) - Metric used to measure company performance.
  • Gross Margin - Financial metric discussed in relation to AI companies.
  • Market Cap - Metric used to measure company size.
  • Tech Waves - Concept referring to periods of significant technological advancement and value creation.
  • Winner-Take-All Markets - Market structure where one company dominates.
  • Capital as a Weapon - Investment strategy discussed in relation to SoftBank Vision Fund.
  • Preferential Attachment - Concept explaining increasing returns to scale.
  • King Making - Concept of a financier anointing a winner in a category.
  • Tam Trap - Concept related to market size estimations.
  • Business Model Shift - Change in how companies generate revenue.
  • UI (User Interface) - Component of software discussed in relation to disruption.
  • Workflow - Process of how tasks are completed, discussed in relation to disruption.
  • Data Access - Availability and use of data, discussed in relation to disruption.
  • ROI (Return on Investment) - Metric discussed in relation to AI implementation.
  • ARR (Annual Recurring Revenue) - Metric for scaling revenue.
  • Customer Acquisition Cost (CAC) - Metric for the cost of acquiring a new customer.
  • Liquidation Preference - Term in investment agreements.
  • LPs (Limited Partners) - Investors in venture capital funds.
  • VC (Venture Capital) - Investment strategy and industry.
  • PE (Private Equity) - Investment strategy and industry.
  • SAS (Software as a Service) - Business model.
  • Cloud - Computing infrastructure model.
  • Robotics - Field of technology discussed as a future investment opportunity.
  • Personal Health Management - Area of personal care discussed as a future investment opportunity.

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