- There is a debate about AI being the most transformational technology seen in 20 years versus it being a bubble with crazy valuations and cash burn.
- Holding two truths: AI is transformational but also creating a financial gold rush leading to a bubble.
- Historical parallels: The internet boom of the 1990s and the fiber optic craze, both of which created lasting infrastructure despite initial bubbles.
"This is the most transformational technology I think I will ever see in my lifetime, and at the same time, there is like happens with many transformational technologies, it's an incredible gold rush that brings in a lot of people."
- AI is both transformational and creates financial bubbles.
"The internet eBay Amazon Etc turned out to be incredible companies and I think the same will be true about AI."
- Historical successes in transformative technologies suggest AI will also produce foundational companies.
Financial Gold Rush and Bubble Dynamics
- Many people will lose money due to the bubble, but foundational technologies will be built.
- Exposure risk: Many LPS have exposure to the same companies through multiple funds, leading to a false sense of diversification.
- Logo chasing: Investors want to be associated with hot companies, leading to inflated valuations.
"A lot of LPS with a lot of exposure to a lot of the same kind of companies through multiple different funds."
- Overexposure to the same companies increases risk despite perceived diversification.
"There's a second kind of category which I call logo chasing... I need to be in the hot one."
- Investors chase popular companies for prestige, inflating valuations.
Foundation Models and Talent
- Foundation models are the fastest appreciating asset in history.
- The value lies in the teams that can bring these models together, not just the models themselves.
- Talent retention is crucial as the real asset is the people.
"Foundation models are the fastest appreciating asset in history."
- Foundation models have rapidly increased in value.
"The price is actually aligned to the teams that are able to bring these models together... that is where the value in the companies are."
- The true value is in the skilled teams, not just the models.
Large Cloud Providers and AI Market Dynamics
- Large cloud providers will likely acquire smaller AI providers.
- A battle for dominance will ensue between major players like Anthropic and OpenAI.
- The starting point for AI usage will be crucial, similar to how Google became a starting point for internet searches.
"You're going to see a battle for the crown between Anthropic and OpenAI."
- Major players will compete for dominance in the AI space.
"Where do people who use AI start their day? It's a little bit like the Google question."
- The starting point for AI usage will be pivotal in determining market leaders.
Venture Capital in AI
- Foundation models are not an asset class; only a few companies will make significant returns.
- The venture business is unique and not comparable to other asset classes like commercial real estate.
- Focus should be on identifying exceptional companies rather than treating all AI ventures as a homogeneous asset class.
"The Venture business is completely sui generis; it's not a class."
- Venture capital in AI is unique and cannot be treated as a standard asset class.
"There are one or two companies in there that will make their Venture investors a lot of money, and the rest of them will cost their LPS and GPS a lot of money."
- Only a few AI companies will be highly profitable; most will not.
AI Investment Strategy and Geographic Focus
- Investing in AI needs a strategic focus; not all regions or companies are suitable for foundation models.
- Israel, for instance, is better suited for applied AI rather than foundation models due to its military rather than academic focus.
- Applied AI offers opportunities in improving efficiency in various industries.
"We invest only in Israel, and we've had a theory... can Israel do Foundation models? We said no."
- Geographic focus matters; Israel is better for applied AI.
"What we want to do is applied AI and what we want to do is kind of full stack stringing through the system of AI."
- The focus is on applied AI and integrating AI systems fully.
AI's Impact on Legacy Companies
- AI will create a significant divide between AI-enabled companies and those that are not.
- Legacy companies will struggle to catch up if their data systems are not set up correctly.
- The transition to AI is more challenging than the transition to the internet.
"There used to be nuclear countries and non-nuclear countries; now they're going to be AI countries and non-AI countries."
- AI will create a significant divide between adopters and non-adopters.
"It's going to be harder for legacy companies to catch up to AI companies."
- Legacy companies will find it challenging to transition to AI.
Market Competition and Investment Preferences
- Competitive markets like customer service AI and sales team AI are less appealing due to high competition and low differentiation.
- Preference for investing in unique, less competitive markets with specific domain knowledge.
- Example: Investing in a company that provides synthetically engineered rocket fuel, which is a unique market.
"I really don't like competitive markets when I invest."
- Preference for unique markets with less competition.
"We just backed an AI to synthetic biology and chemistry rocket fuel company."
- Example of investing in a unique and innovative market.
Risk and Portfolio Management
- Investing in unique markets is not inherently riskier than investing in SAS or FinTech.
- SAS is considered riskier due to competition and price erosion.
- False sense of security in SAS models; pulling the model forward does not guarantee success.
"SAS is way more risky... because of the competition and price erosion."
- SAS is riskier due to high competition and price erosion.
"Anytime you can kind of stamp out MBAs from universities, you can pull the model forward."
- Critique of the perceived security in SAS models.
Premium Multiples and Market Trends
- Companies receive premium multiples when they are the only way to play a future trend in public markets.
- High growth is a factor but not the only reason for premium multiples.
- Being unique in a market trend can lead to higher multiples.
"Companies get premium multiples when it's the only way to play a future trend in the public markets."
- Companies that are the sole representatives of a market trend attract higher valuations.
"If I have multiple ways to play a market, you'll get a lower multiple. If I have a single way to play a market evolution, I'll get a premium multiple."
- Single-point market plays receive higher multiples compared to markets with multiple entry points.
Evaluation of Software Companies
- Comparison between Clavio and Atlassian regarding their multiples.
- Discussion on why some companies get higher multiples despite similar business models and growth rates.
"I've got the founder of Clavio on the show tonight which is a $7 billion company, doing $750 million a year in revenue growing 60% a year on a year. It's quite remarkable."
- Clavio is noted for its impressive growth yet has a lower multiple compared to Atlassian.
"The multiple on it is not great. I think the multiple is like a 6X or a 7X, and then I look at an Atlassian which is trading at 12X and it's not an inherently better business."
- Atlassian trades at a higher multiple, indicating investor preference for specific market trends.
Impact of AI on Software Markets
- Horizontal SaaS companies may be disrupted by AI.
- AI could reduce the need for traditional software by enabling custom solutions.
"Horizontal SaaS processes are going to be disrupted by AI."
- AI is expected to change how horizontal SaaS companies operate, potentially reducing their market.
"Amazon has said don't buy any more software; AI can take care of all the kind of business process needs we need in software."
- Amazon's stance on AI replacing traditional software solutions signifies a broader market trend.
Consulting Firms and AI Integration
- Companies like Accenture and McKenzie are leading in integrating AI into business processes.
- Consulting firms are increasingly using AI to improve business efficiencies.
"Accenture just posted $2.4 billion in generative AI revenue."
- Accenture’s revenue from AI highlights the growing importance of AI in consulting.
"McKenzie is also doing extremely well today in these at-risk fee businesses."
- McKenzie’s success in AI-driven consulting underscores the trend towards AI integration.
Software Market Saturation and Efficiency
- The market for purchasing software is slowing down.
- Companies have extracted significant efficiencies from basic software.
"I think the market for purchasing software is slowing down 100%."
- There is a noticeable decrease in the software purchasing market.
"We've squeezed a lot of efficiency out of businesses using kind of basic software already."
- Basic software has reached its efficiency limits, necessitating new solutions for further improvements.
Value-Based Pricing Models
- Buyers today are willing to pay for value rather than traditional pricing models.
- There is a shift towards value-based pricing in software and consulting services.
"People pay for work. I think that's a real thing."
- The trend towards paying for tangible improvements rather than per-seat models is gaining traction.
"Consultants like Accenture and McKenzie are the leading edge of this, but I think it's going to come into software very quickly."
- Consulting firms are pioneering value-based pricing, which is expected to influence the software industry.
Adoption Cycles and Technological Breakthroughs
- Adoption cycles are often overestimated in the short term and underestimated in the long term.
- The pace of technological advancements, especially in AI, is unprecedented.
"We always overestimate in a year and underestimate in ten."
- Adoption cycles are more gradual than initially perceived but have significant long-term impacts.
"The pace that these things are learning at and adapting at is incredible."
- The rapid development of AI technologies is highlighted as a major trend.
Regulatory Challenges and AI Development
- Regulatory challenges could slow down AI development.
- Europe is more likely to impose stringent regulations compared to the US and other markets.
"You have regulators who fear that it's getting away from them place these very punitive policies or regulations on data access."
- Regulatory fears could lead to restrictive policies, hindering AI development.
"I think that is going to set Europe back in competitiveness more than it's already been set back in competitiveness over the last 20 years."
- Stringent regulations in Europe could further reduce its global competitiveness.
Geopolitical Implications of AI
- AI is seen as a strategic advantage in global conflicts.
- There is a debate on whether AI systems should be closed to prevent adversaries from accessing the technology.
"AI is the most demonstrable power that any country or nation can hold and leverage in a case of war."
- AI’s strategic importance in warfare is emphasized.
"The 21st century is AI countries versus non-AI countries."
- The competitive edge in the 21st century will be defined by AI capabilities.
Defense Industry and Technological Integration
- The defense industry is becoming a focus area for technological advancements.
- There is a growing interest in defense technology investments, but it requires specialized knowledge.
"There was always an alliance between Silicon Valley and the defense industry."
- Historical ties between tech and defense sectors are being revitalized.
"People will lose a lot of money chasing the new new thing which today happens to be defense in addition to AI."
- Investing in defense technology is complex and requires expertise, cautioning against uninformed investments.
Shift to Hard Tech and Investment Challenges
- There is a shift from software to hard tech, including climate technology.
- Software investors may face challenges adapting to the different dynamics of hard tech investments.
"We need to move to hard tech, we need to move to whether that's climate but much more physical challenging."
- The investment focus is shifting towards hard tech sectors.
"A load of software investors are going to lose their shirts investing in a completely different type of company."
- Software investors may struggle with the transition to hard tech due to differing investment requirements.
Key Themes
Transition from SaaS to Harder Technologies
- Founders are increasingly avoiding SaaS investors as the SaaS playbook doesn't apply to harder technologies.
- Emergence of new fields like semiconductors, synthetic biology, and synthetic chemistry.
- Concept of "labless" model where synthetic biology can be outsourced, reducing infrastructure costs.
"Some Founders or the great Founders are likely not taking SaaS investors' money because the SaaS Playbook as it's become called doesn't apply to any of these harder Technologies."
- The traditional SaaS investment model is not suitable for emerging and complex technologies.
"I think we've now gotten a labless so you can do synthetic biology, you don't have to build a lab; you can outsource."
- The "labless" model allows for outsourcing lab work, making it more cost-effective for startups.
Learning and Building Expertise
- Using tools like ChatGPT to relearn and understand complex subjects such as chemistry.
- Importance of learning through collaboration and osmosis by working closely with experts.
"I've used actually ChatGPT now to teach me chemistry, and I've been doing kind of high school chemistry again."
- ChatGPT is being used as a learning tool for complex subjects.
"I brought this guy back from America, an Israeli guy with a PhD from The Weizmann Institute, who had built a synthetic biology lab at Harvard medical school."
- Collaborating with experts to build companies and gain knowledge through close interaction.
Market Liquidity Concerns
- Concerns about where liquidity will come from in the current market environment.
- IPOs, M&A, and PE as potential sources of liquidity, but each has its challenges.
"I'm wondering where is liquidity going to come from like I'm looking at the different Avenues which is IPO, it's M&A and then it's like PE."
- The current market environment poses challenges for liquidity through traditional means.
"Lena Khan seems like the ultimate challenge socialist to M&A."
- Regulatory challenges, particularly from figures like Lena Khan, are affecting M&A activities.
IPO Market and Public Listings
- The IPO market is open but at lower valuations; companies should consider going public early.
- Historical examples of successful companies that went public early with modest revenues.
"The IPO window is wide open; the question is what's the price you're willing to take."
- Companies can still go public, but they need to be willing to accept lower valuations.
"Shopify went public at 700 million. Amazon, the best business in the world, went public early."
- Successful companies like Shopify and Amazon went public early and grew in the public markets.
Private Equity and Secondary Markets
- Private equity (PE) is not a reliable savior for liquidity due to high-interest rates and price sensitivity.
- Secondary markets often lack genuine buyers and are mainly data fishing expeditions.
"Interest rates are way up; they can't borrow anymore. They're incredibly price sensitive."
- High-interest rates and price sensitivity limit PE's ability to provide liquidity.
"We decided to do a little experiment; we reach out to them. These are just people looking for data."
- Many secondary market buyers are not genuine; they are often looking for data rather than making actual purchases.
Investment Strategies and Decision-Making
- The importance of taking full positions in investments if there is conviction.
- The binary nature of venture capital investments; it's about taking whole positions rather than averaging in or out.
"If I have conviction, I'm going to take a whole position. This business is an outlier business."
- Conviction in an investment should lead to taking a full position rather than a partial one.
"This is a binary industry, very, very binary investments, and I'm in that binary camp."
- Venture capital investments are highly binary, requiring decisive actions.
Pro-Rata Investments and Portfolio Management
- Pro-rata investments are often made in middling companies rather than runaway successes.
- The need to buy ownership in the first round rather than relying on future rounds.
"We try to kind of peel back on it; we think we have to buy our ownership in the first round."
- Ownership should be secured in the initial investment round.
"The good ones just kind of get you know they become runaways and you kind of can't get more capital."
- Runaway successes often don't allow for additional capital investments later on.
Consumer vs. Enterprise Investments
- Differences in investment strategies between consumer and enterprise companies.
- Consumer companies are more transient and less predictable compared to enterprise companies.
"Consumer is ephemeral. Sometimes works, sometimes doesn't, sometimes goes out of style."
- Consumer investments are more unpredictable and can be transient.
"Enterprise, you've got a lot more predictability."
- Enterprise investments offer more predictability compared to consumer investments.
Building Moats in AI and Technology
- Challenges in building moats in AI and technology businesses due to the lack of visible differentiation.
- The importance of data as a moat in AI businesses.
"It's really hard to tell the difference visibly between OpenAI and Anthropic and any one of a number of models."
- Differentiation in AI models is challenging, making it hard to build a moat.
"The moat is the data, and over time some people will note that it's significantly better."
- Data serves as a crucial moat in AI businesses over time.
Exit Strategies and Fund Longevity
- Lack of focus on exit scenarios during initial investments; companies pivot and outcomes are unpredictable.
- The potential for a generation of funds to die due to market conditions and investment strategies.
"We don't outcome scenario plan... it never works out like that, so why bother."
- Exit scenarios are not planned as companies often pivot, making predictions unreliable.
"Do you think we're going to see a generation of funds die? Michael, of course."
- Market conditions and investment strategies may lead to the demise of some funds.
Venture Capital: High Barrier to Exit
- Venture Capital (VC) has a high barrier to exit due to continuous management fees.
- The industry sees slow exits, often due to a generational shift and market realities.
- Talent from failed startups is often recycled into new ventures.
"Venture Capital has the highest barrier to exit of any business out there. No one wants to leave; the management fees keep coming."
- Explanation: The consistent influx of management fees makes it difficult for venture capitalists to exit the industry.
Types of Funds and Their Longevity
- Funds with multiple partners but only one successful partner are likely to dissolve.
- Some funds fail to deliver capital back to Limited Partners (LPs) and will eventually disappear.
- Both large and small funds can face these issues.
"The first style of funds that go out of business is funds where there are three, four, or five partners, and only one of them is good."
- Explanation: Funds with a single successful partner are unsustainable long-term, leading to their dissolution.
Importance of TVPI and DPI
- Total Value to Paid-In (TVPI) is still highly valued by LPs despite market changes.
- Distribution to Paid-In (DPI) is crucial for assessing actual returns.
- The sustainability of TVPI is questioned based on competitive advantages and future cash flows.
"TVPI actually matters because if the thing is compounding at a high rate and keeps going, that's not a bad thing."
- Explanation: High TVPI indicates potential future growth, making it an important metric for LPs.
Competitive Advantage and Sustainable Growth
- Assessing the depth and sustainability of competitive advantages in portfolio companies is essential.
- The transition from hyper-growth to sustainable, slower growth is becoming more common.
- Companies with moderate growth face challenges in exiting and may need to grind it out or buy back stock.
"The question that needs to be asked in TVPI land is these underlying portfolio companies, how deep is their competitive advantage?"
- Explanation: The sustainability of a company's growth is heavily dependent on its competitive edge.
Directness and Communication in Venture Capital
- Being direct can be both a strength and a weakness in investor-entrepreneur relationships.
- Effective board meetings should be concise, with good preparation and focused discussions.
- In-person interactions are preferred over Zoom for their effectiveness and personal touch.
"It has been said about me multiple times that I am very, very direct and therefore an acquired taste."
- Explanation: The direct approach can be off-putting initially but is appreciated for its clarity and urgency.
Balancing Involvement and High-Level Perspective
- Investors need to balance deep involvement in companies with maintaining a high-level perspective.
- Over-involvement can rattle first-time entrepreneurs, while seasoned entrepreneurs handle it better.
- The importance of face-to-face interactions in building and guiding companies.
"You can get really absorbed into these companies, and sometimes I need to pull myself out at a high level."
- Explanation: Maintaining a high-level view is crucial for investors to avoid over-involvement.
Founder Experience: Naive vs. Experienced
- Founders with no prior experience in a market can bring fresh perspectives and innovative approaches.
- Lack of industry knowledge can lead to breaking traditional rules and achieving better outcomes.
"The fact that Shai and Daniel of Lemonade didn't know anything about insurance helped a ton."
- Explanation: Naive founders can disrupt industries by not being constrained by traditional knowledge.
Changing Perspectives on Younger Generations
- Younger generations are showing resilience and activism, contrary to initial concerns about their engagement.
- The recent events in Israel highlight the younger generation's potential to stand up for important causes.
"I was concerned about younger people being too absorbed in TikTok and Instagram, but they went out to fight for what mattered."
- Explanation: Younger generations are proving to be more engaged and resilient than initially thought.
Misconceptions about the Israeli Startup Ecosystem
- The Israeli startup ecosystem is vibrant and attracting significant foreign investment.
- There is a misconception that Israelis naturally know how to scale businesses, but they often need help thinking big.
"People think Israelis know how to scale things, but growing up in a small country, it's harder to think of scale."
- Explanation: Israeli startups may require external support to scale effectively due to their small domestic market.
Respect for Competitors and Hard Work
- Respect for competitors is essential, and hard work is necessary to stay competitive.
- The zero-interest rate environment led to complacency and missed opportunities to sell.
"If I'm not the hardest working venture capitalist out there, shame on me."
- Explanation: Hard work is crucial in the competitive venture capital industry.
Future Aspirations and Self-Reflection
- Continuous improvement and staying relevant in the venture capital industry are important goals.
- Balancing time and responsibilities is a constant challenge, with a need for better time management.
"I hope they'll keep me around; I'm ultra-committed to this business at 53."
- Explanation: The speaker hopes to remain relevant and valuable in the venture capital industry despite age-related challenges.
Key Areas of Strength and Weakness
- Networking is identified as a key strength, while management assistance is seen as a weakness.
- Sourcing deals is no longer a focus, relying instead on a strong network built over years.
"I get all my deals right now through referrals of 30 years of being in this business."
- Explanation: The speaker leverages a vast network for deal flow, reducing the need for proactive sourcing.
Final Reflections
- The importance of hard work and continuous effort in achieving success.
- The need for self-reflection and improvement in balancing time and responsibilities.
"Life is not supposed to be necessarily easy, and you got to keep working at it."
- Explanation: Hard work and perseverance are essential for success and fulfillment in life and business.