20VC Who Wins in AI; Startup vs Incumbent, Infrastructure vs Application Layer, Bundled vs Unbundled Providers From 150 LP Meetings to Closing $230M for Fund I; The Fundraising Process, What Worked, What Didn't and Lessons Learned with Tomasz Tunguz

Summary Notes


In this episode of 20vc, host Harry Stebbings converses with Tom Tunguz, who recently announced his new $230 million fund, Theory Ventures. Tunguz, a former general partner at Redpoint for 14 years with investments in Looker and Expensify, shares insights on the venture landscape, discussing the advantages of application-layer startups over foundational models, the importance of thesis-driven investing, and the strategy behind his concentrated portfolio approach. He predicts that AI will significantly impact GDP growth, akin to the post-WWII era, and critiques Google's missed opportunity with generative AI, highlighting the potential for startups to disrupt even in the face of incumbent giants. Tunguz also delves into the fundraising process, revealing the challenges and tactics of securing LP commitments in a tough market.

Summary Notes

Foundational Model Layer vs. Application Layer

  • The foundational model layer is considered a game for the big players, with higher odds of success at the application layer due to diverse needs.
  • Post-WWII technology surplus could be replicated by current technology.
  • Google experienced a rude awakening by developing in-house but ignoring external innovations, exemplifying the classic innovator's dilemma.

"I think at the foundational model layer, that's a big boys game or big girls game. The odds of success are going to be significantly higher at the application layer because the diversity of needs there is greater."

This quote emphasizes the speaker's view that success is more likely at the application layer of technology due to the variety of needs it addresses, compared to the foundational model layer which is more competitive and less diverse.

"We're faced with a technology that could actually replicate the postwar surplus out of World War II."

The speaker suggests that current technology has the potential to create a surplus similar to the post-WWII era, indicating significant technological advancements and their economic impact.

"I think Google had a rude awakening where to some extent they developed inhouse but ignored. So it's a classic innovator's dilemma."

The speaker points out that Google, despite its in-house development, may have overlooked external innovations, leading to a situation described by the innovator's dilemma, where established companies can struggle to adopt new technologies due to their focus on current products.

Harry Stebbings and 20 VC

  • Harry Stebbings is the host of the 20 VC podcast.
  • The podcast features discussions with venture capitalists and entrepreneurs.

"This is 20 vc with me, Harry Stebbings."

Harry Stebbings introduces himself as the host of the 20 VC podcast, setting the stage for the conversation about venture capital and startups.

Tom Tunguz and Theory Ventures

  • Tom Tunguz is a former general partner at Redpoint and the founder of Theory Ventures, a new $230 million fund.
  • Prior to Theory, Tom spent 14 years at Redpoint, investing in companies like Looker, Expensify, Monte Carlo, and others.
  • Theory Ventures is a result of Tom's desire to start his own company and experiment with building a venture firm in a different way.

"Now the last time I had Tom Tunguz on the show was seven years ago, since he's become a dear friend."

The speaker, Harry Stebbings, notes the last appearance of Tom Tunguz on the show and their ensuing friendship.

"And last week he announced his new $230,000,000 fund, Theory Ventures. No one deserves this more than Tom."

Harry Stebbings expresses his happiness for Tom Tunguz's announcement of his new venture fund, Theory Ventures, and commends Tom's deservingness of success.

"Prior to founding Theory, Tom spent 14 years at Redpoint as a general partner."

Tom Tunguz's background is highlighted, showcasing his extensive experience as a general partner at Redpoint before starting Theory Ventures.

Coder and Angellist

  • Coder is a tool that helps teams collaborate efficiently by centralizing data and eliminating roadblocks to productivity.
  • Angellist is described as becoming central to the venture ecosystem, offering services for startups and venture funds, including captain able management, banking, fundraising, and compliance.

"Coder is the doc that brings it all together and how it can help your team run smoother and be more efficient."

This quote explains the utility of Coder in bringing team efforts together in one document for smoother operations and increased efficiency.

"Angellist is fast becoming the center of the venture ecosystem."

Angellist is portrayed as an increasingly central player in the venture capital ecosystem, providing a range of services to startups and funds.

Brex and Financial Stack for Startups

  • Brex is committed to helping startups at every stage by providing a comprehensive financial stack.
  • The financial stack includes a high-yield business account, corporate cards, expense tracking, and bill pay.

"Brex's all-in-one financial stack is used by one in four US startups and counting."

Brex's financial services are highlighted as widely used among US startups, indicating its importance in the startup ecosystem.

Tom's Journey from Redpoint to Theory Ventures

  • Tom left Redpoint after 15 years to start his own venture, driven by the desire to experience founding a company and to experiment with creating a venture firm in a unique way.
  • He believes in thesis-driven investing and concentration, which influenced the creation of Theory Ventures.

"Yeah, I had a great time at Redpoint. I was there for 15 years, learned from many wonderful people, and after that amount of time, I decided that after seeing so many founders start companies that I really wanted to start one of my own."

Tom reflects on his positive experience at Redpoint and explains his motivation for leaving to start his own venture, inspired by the founders he encountered.

"I really believe in thesis-driven investing, and what that means is going deep in a space and spending 6, 9, 12 months researching it and really understanding it."

Tom emphasizes his investment philosophy of thesis-driven investing, which involves in-depth research and understanding of a particular space before investing.

"I really believe in concentration. The industry is governed by a power law, and the more dollars you can have closer to the y-axis of the peak on the power law, the better your returns will be."

Tom discusses his belief in concentrated investments and the power law that governs the industry, suggesting that having more dollars invested near the peak of the power law curve can lead to better returns.

Fundraising for Theory Ventures

  • Tom conducted around 150 LP meetings to raise funds for Theory Ventures during a challenging market.
  • He approached fundraising like a software sales process, aiming for a 15% close rate.
  • Tom knew about 40-50 of the LPs before the raise, and approximately 50% of the capital came from new relationships.
  • He sought large institutional anchors first to set the process up well and to assuage concerns from newer LPs.
  • Tom set a limit on check size, with the largest LP contributing no more than 12% of the fund.
  • He provided a data room with a track record, pitch deck, bio, and blog posts for LPs, using doc send to track engagement.
  • The biggest reasons for LPs saying no were the solo GP risk and timing due to public market downturns and private market valuation uncertainties.
  • The LP base for Theory Ventures is predominantly US-based, with a mix of fund of funds, endowments, foundations, pension funds, and healthcare plans.

"My friend, it took about 150 LP meetings. The fundraising market was a very challenging one over the last couple of months, I'd say, but it took about a meeting, about 150 LPs."

Tom shares the extensive effort it took to meet with 150 LPs during a difficult fundraising market to secure the capital for Theory Ventures.

"I went for the large institutional anchors, had some relationships there."

Tom discusses his strategy of targeting large institutional anchors first to gain credibility and support for his fund.

"I did, yeah. I think the largest LP is no more than 12% of the fund."

Tom confirms that he set a limit on the maximum percentage an individual LP could invest in the fund to maintain diversification.

"Every time I had another verbal commit, I emailed the LP base and I gave them the update."

Tom describes his method of driving urgency among LPs by regularly updating them on new commitments to maintain momentum in the fundraising process.## Fundraising Strategy

  • Emphasizing the inevitability of success can be persuasive in fundraising.
  • Mentioning new commitments from investors can build momentum and credibility.
  • Long-term relationships with investors are crucial for successful capital raising.
  • Understanding the conservatism of investors in different geographies is important for efficient use of time.

"Is hugely helpful when you say, hey, this person just committed, or we just got another great institution."

The quote highlights how sharing news of new investor commitments can positively influence existing investors and attract further interest.

"I think one of the things that's really important is building long term relationships."

This quote emphasizes the importance of long-term relationships in the fundraising process, which proved to be beneficial for the speaker.

"There are different geographies where lps as a whole are more conservative, and it took me a while to appreciate that."

Here, the speaker reflects on the need to recognize and adapt to the varying levels of conservatism among investors in different regions.

Effectiveness of In-Person Meetings

  • There was no clear correlation between in-person meetings and successful investor conversions.
  • A significant portion of commitments came from investors who were only met after they committed, possibly due to the virtual fundraising environment during COVID-19.

"Actually, no, there's no correlation."

The speaker indicates that in their experience, in-person meetings did not necessarily correlate with higher conversion rates with limited partners (LPs).

Continuous Investor Engagement

  • Regularly meeting new LPs can create a self-perpetuating network for introductions and potential investments.
  • Actively seeking introductions to like-minded LPs can expand one's investor network.

"Actually, the thing that I do is every week I meet two new lps."

This quote discusses a proactive strategy of meeting new investors regularly to expand the network and potential fundraising opportunities.

"And the flywheel is self fulfilling."

The speaker describes the momentum gained from consistent networking, where one introduction leads to another, creating a continuous cycle of potential investor engagement.

Importance of a Business Model in Fundraising

  • LPs are increasingly interested in the business model and assumptions underlying a venture.
  • A detailed business model has become more important due to the increased cost of capital.
  • Historical focus on fundamentals has shifted, and now there is a renewed interest due to market conditions.

"I think in the last 1112 years, where we've had this incredible bull market, the portfolio construction hasn't mattered as much."

The speaker reflects on how, during a bull market, the focus on portfolio construction and business models was less critical, but the trend is changing.

"It's really important to have a business model in your deck."

Here, the speaker advises that including a business model in a fundraising deck is now crucial due to changing market conditions and investor scrutiny.

Portfolio Construction and Fund Size

  • The speaker chose a fund size of $230 million based on optimal portfolio construction derived from Monte Carlo simulations.
  • A concentrated portfolio approach with significant investment in a few companies aligns with being thesis-driven and deeply understanding a market.
  • The speaker believes in the ability to pick better investments with deep industry knowledge, reducing the need for diversification.

"It was all about portfolio construction."

The speaker explains that the decision on the fund size was based heavily on the concept of portfolio construction, using data and simulations to determine the optimal amount.

"It's about twelve to 15 portfolio companies, significant concentration."

This quote details the speaker's strategy for portfolio concentration, which involves a smaller number of companies with larger investments in each.

Investment Conviction and Diligence

  • Building conviction for investment requires extensive diligence and understanding of the market, benchmarking, and exit market analysis.
  • The speaker uses a method called "fermisation" to evaluate conditional probabilities and expected outcomes for investments.
  • Understanding the historical and realistic multiples at the time of exit is crucial for responsible investing.

"It's a lot of diligence. We'll spend 6912 months researching a space."

The speaker emphasizes the depth of research and diligence that goes into building conviction for an investment.

"The historical forward multiple is about five x."

This quote indicates the importance of understanding historical data and setting realistic expectations for investment returns based on current market conditions.

Price Sensitivity and Ownership

  • Knowledge of a market can justify higher investment prices due to increased certainty in outcomes.
  • Meaningful ownership in portfolio companies is important, especially when the investment strategy is highly concentrated.
  • The speaker's firm aims to build ownership positions over time rather than requiring large initial stakes.

"I think it's true, because if you know more about a market, the range of expected outcomes is far more narrow."

The speaker agrees that deeper market knowledge can lead to more confidence in investment decisions, potentially justifying higher prices.

"It's important for us to have meaningful ownership because we're so concentrated."

This quote explains the speaker's approach to ownership, highlighting the importance of significant stakes in a concentrated portfolio.

Reserves and Investment Discipline

  • The firm has a disciplined approach to reserves, only investing additional capital in companies after thorough diligence.
  • The speaker believes in supporting companies through various market conditions, as demonstrated by the Snowflake investment story.
  • Understanding when to invest further or step back is crucial for managing a concentrated portfolio.

"The idea behind concentrating in reserves is we will run diligence processes on those existing portfolio companies in order to understand where to concentrate."

The speaker outlines their strategy of conducting diligent reviews of portfolio companies to decide where to allocate reserve capital.

"If you have an accurate thesis and you can find the right company and you have the wherewithal to be able to support that business through good times and bad. You can be disproportionately rewarded for it."

The Snowflake anecdote illustrates the potential rewards of standing by a strong investment thesis and providing continued support to a company, even during tough times.

Thesis-Driven Investing and Confirmation Bias

  • The speaker acknowledges the risk of confirmation bias in thesis-driven investing.
  • To mitigate confirmation bias, one must engage in many conversations and be guided by actual customer demand.
  • The speaker uses pipeline and customer need as indicators of market timing and the validity of a thesis.

"You could become enamored with a particular view of the world."

This quote acknowledges the danger of becoming too attached to one's investment thesis and the need to remain objective.

"The greatest sort of foil to confirmation bias is a lack of customer demand."

The speaker suggests that actual market demand is the best check against confirmation bias, as it provides tangible evidence of a thesis's viability.## Market Timing and Customer Understanding

  • Understanding the customer buyer population is essential for developing investment theses.
  • The needs of one buyer can often be extrapolated to others, which gives confidence in market timing.
  • A strong pipeline is indicative of good market timing.

"As long as you have a strong pipeline, you can have a lot of confidence, as long as you can extrapolate the needs of one buyer to another."

This quote emphasizes the importance of a strong pipeline and the ability to generalize the needs of one buyer to others in order to have confidence in market timing.

Future of AI Models

  • There is a debate on whether the future of AI will be a single general model or a decentralized ecosystem.
  • Analogies with Apple and Linux/Windows suggest both integrated and open-source models will exist.
  • Dominant models will likely serve as an interface across various models for different purposes.
  • Large language models will be accessible to developers through platforms like Striped Twilios.
  • Full enterprise services will cater to large companies wanting complete solutions.
  • The infrastructure layer of AI is capital intensive and may be dominated by a few players.
  • The application layer of AI will likely have a higher diversity of businesses and therefore more opportunities for investors.

"I think you have both. I think the analogy of Apple and Linux is really useful here, Apple and Windows, where you'll have one system that is basically fully integrated and closed, and then you'll have another world where people are building little open source models."

This quote suggests that the future of AI will include both integrated systems and open-source models, similar to the ecosystems of Apple and Linux/Windows.

Enterprise Data Security and AI

  • Traditional software was run on enterprise machines, but Salesforce pioneered moving to the cloud.
  • There is a trend towards bifurcation, keeping data in the customer's account while running applications elsewhere.
  • A likely architecture involves the model going to the data, executing, and then leaving, keeping data secure.
  • Sectors like finance and healthcare may remain on-premises due to security and compliance requirements.
  • AI startups have opportunities in enterprise readiness, including compliance and legal shielding.
  • The architecture of AI deployment must accommodate the security and compliance needs of enterprises.

"I think we'll see a very similar architecture where the model actually goes to the data and then comes back out with the result."

This quote describes a future architecture for AI in enterprises where the model interacts with data securely within the customer's environment, addressing security and privacy concerns.

Market Dynamics and Bundling

  • In early markets, there is a preference for bundled solutions due to the lack of understanding and the fast pace of technology.
  • As market sophistication increases, customers may seek best-of-breed solutions for specific layers of technology.
  • The transition from bundled to unbundled solutions is driven by increased customer experience and needs.

"My learning has been that in early markets, people want bundling...So my sense is, in the beginning, people want an end to end solution."

This quote reflects the initial preference for bundled, end-to-end solutions in early markets due to the complexity and novelty of the technology.

Enterprise Readiness for AI

  • Enterprises may not need to understand AI technology fully to use it, similar to how most users do not fully understand databases.
  • End-to-end solutions that work most of the time and meet security and compliance needs are often sufficient for enterprise buyers.
  • The concept of the "illusion of explanatory depth" suggests familiarity with technology does not equate to understanding it.

"This is a technology that most buyers won't need to understand how it works."

This quote implies that the technical intricacies of AI are not a barrier to adoption for enterprises, as long as the solutions meet their practical needs.

AI's Impact on Code Generation and Economy

  • AI-driven code generation is expected to increase significantly in the future.
  • AI has the potential to significantly increase GDP growth, drawing parallels to the postwar economic boom.
  • There are concerns about AI's impact on wealth distribution and the potential concentration of wealth.

"I think it'll probably be 70% to 80%."

This quote predicts a substantial increase in AI's contribution to code generation, reflecting the growing influence of AI on software development.

Regulation and Market Dynamics

  • Regulation often benefits incumbents due to the cost of compliance.
  • Unintended second-order effects of regulation can have significant impacts.
  • The legal system's slow response to technological changes, such as in crypto, poses challenges.
  • Incremental regulation is seen as the best approach, allowing for adjustments as new issues arise.

"I think regulation, on the whole one, it benefits incumbents because the cost of adhering to regulations are significant."

This quote highlights the advantage that existing large companies have when it comes to regulation due to their resources to comply with new rules.

Startups vs. Incumbents in AI

  • There is a debate about whether startups or incumbents will dominate the next generation of AI.
  • Incumbents have the advantage of distribution and existing relationships, while startups have agility and flexibility.
  • Execution quality is the key moat for both startups and incumbents in the AI space.

"My thinking's evolved here. In the beginning, I thought the incumbents were going to win the whole thing."

This quote reflects a shift in perspective, acknowledging that despite the advantages of incumbents, startups can still succeed through superior execution.## Disruptive Technology and Market Dynamics

  • Disruptive technology can challenge established monopolies and open up markets.
  • Dominance by major companies such as Facebook and Google has stifled innovation in the ads and BTC ecosystems.
  • The emergence of new technology allows for the creation of new services and platforms, such as travel agencies, shopping experiences, and social experiences based on chat.
  • Market share in these areas is now "up for grabs" due to technological advancements and replatforming.

"And now all of a sudden there's a disruptive technology... And now all of a sudden you have a technology and a replatforming where all that market share is conceivably up for grabs."

This quote emphasizes the impact of disruptive technology on established markets and the opportunities it creates for new entrants to capture market share.

Innovator's Dilemma and Corporate Strategy

  • Companies with successful business models face the dilemma of self-disruption versus external disruption.
  • Leadership teams often struggle with the decision to disrupt their own stable business models.
  • The reluctance to self-disrupt can lead to missed opportunities and allow competitors to gain an advantage.

"I think it's a classic thing that when you have a golden goose... I think as a leadership team it is so difficult to have the discipline to say we are going to destabilize this ourselves."

This quote reflects the challenge companies face in deciding whether to risk destabilizing their own successful business models in order to stay ahead of disruptive technologies.

The Evolution and Impact of Large Language Models (LLMs)

  • LLMs were initially perceived as primarily memorization systems, but they also learn by doing, leading to emergent properties.
  • The cost to produce a query using advanced models like GPT-4 is significantly higher than a traditional Google query.
  • The sophistication and capabilities of LLMs have rapidly increased, often catching industry observers by surprise.
  • The pace of innovation in AI is accelerating, with new models and applications emerging regularly.

"I think the other thing that I didn't really appreciate until some of the later models came out was just how sophisticated the emergent behavior can."

This quote highlights the underestimation of the sophistication that LLMs can achieve through learning by doing and the emergent properties that arise from their use.

Data and Content Ownership in the Age of AI

  • The issue of content ownership and fair use is a concern with the rise of AI platforms like ChatGPT.
  • There is a debate over whether AI-generated content that mixes existing sources creates a new copyrightable product.
  • The future of data attribution and content ownership in AI is uncertain, and revenue-sharing models may be necessary.

"Who owns that content? The notion of fair use... And so basically the Internet becomes one huge walled garden."

This quote discusses the legal and ethical challenges surrounding content ownership as AI begins to aggregate and repurpose existing content from various sources.

Economic Outlook for 2023

  • There is a belief that the economic conditions may worsen by the end of 2023.
  • Factors contributing to this outlook include overcorrection on interest rates by the Fed and geopolitical risks, such as conflict in Taiwan.
  • There is a tendency for human psychology to overreact to situations, which can exacerbate economic downturns.

"I think we will probably be in a worse place by the end of 23... So the combination of those four risk factors I think puts the odds of a US recession meaningfully higher than I think a lot of people appreciate."

This quote provides an assessment of the potential economic challenges facing the United States by the end of 2023, highlighting several risk factors.

AI and the Competitive Landscape

  • Microsoft is seen as a leader in AI innovation, with Google slightly behind.
  • Adobe is recognized for its use of generative AI, particularly in products like Photoshop.
  • There is a significant market opportunity for AI to disrupt existing business-to-consumer (B2C) internet services.

"Adobe doesn't have the recognition it deserves when it comes to using generative."

This quote identifies Adobe as an undervalued player in the AI space, particularly regarding its generative AI capabilities in creative software.

Enterprise Readiness for AI

  • A major market opportunity lies in preparing enterprises to integrate AI into their existing systems.
  • There is a need to make AI technologies compatible with the ways large companies have traditionally purchased and used software.

"Time on enterprise readiness? I think if there's one big market opportunity that people haven't focused on, it's how do you bring this to the global 2000 in a way that they will accept and buy."

This quote points out the potential for growth in making AI technologies accessible and acceptable to large, established enterprises.

Venture Capital and Investment Strategies

  • Goodwater is identified as a promising investment due to its focus on identifying B2C opportunities worldwide.
  • The importance of startups in creating markets is emphasized, with a user base in an early market often leading to surprising success.
  • Venture capitalists and limited partners (LPs) should work towards better understanding each other's goals and portfolio construction.

"I'd invest in Goodwater because it's completely orthogonal to B to B... The opportunity for LLMs to destabilize the existing B to C Internet is really huge."

This quote explains the investment rationale for choosing Goodwater, highlighting the significant potential for disruption in the B2C space by LLMs.

Political Landscape and Business

  • The Republican Party is traditionally seen as the party of business and capitalism.
  • There is a need for entitlement reform in the United States to address the projected consumption of tax receipts.
  • The relationship between government and people is expected to undergo significant changes over the next decade.

"And so we need a leader who can guide us through all that."

This quote expresses the need for strong leadership to navigate the upcoming changes in the relationship between the government and the populace, particularly in the context of financial reforms.

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