"I think price does matter, but I think it matters least... when a company is growing exponentially, 10x year on year, 50x year on year... valuation is the last question we try to answer." - Lucas Swisher (On evaluating hyper-growth stage investments) []()
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"20 companies have generated 80% of the enterprise value of all the private companies that exist in the world. And four companies have generated 65% of the enterprise value." - Lucas Swisher (Explaining the extreme power law in venture capital) [00:19:55](https://www.youtube.com/watch?v=Hom5OMMzOQ0&t=0h19m55s)
"Margin matters at scale... early it can be a misleading indicator, especially when an architecture shift is happening." - Lucas Swisher (Discussing AI's impact on traditional SaaS margin metrics) [00:33:32](https://www.youtube.com/watch?v=Hom5OMMzOQ0&t=0h33m32s)
"Data is a prerequisite. It is not the answer... you can't miss the forest through the trees." - Lucas Swisher (On not letting spreadsheet metrics blind you to massive generational trends) [00:48:52](https://www.youtube.com/watch?v=Hom5OMMzOQ0&t=0h48m52s)
"The safe path is so much less safe than you think. The risky path is actually less risky than you think." - Harry Stebbings (Reflecting on career choices and leaving linear paths) [01:03:18](https://www.youtube.com/watch?v=Hom5OMMzOQ0&t=1h3m18s)
2. Executive Summary
In this discussion, Coatue's Lucas Swisher outlines the evolving landscape of growth investing during the current AI architecture shift. He argues that the traditional boundaries between public and private markets are dissolving, forcing investors to seek exposure to private "platform companies" to capture future technological upside.
Swisher dissects the new math behind mega-funds, emphasizing extreme concentration, massive Total Addressable Markets (TAMs), and the shifting dynamics of software margins, ultimately asserting that AI will drive unprecedented labor replacement and enterprise value creation.
Public Markets Lack the Future: The traditional public markets currently lack exposure to the most critical foundational AI and platform companies (e.g., SpaceX, OpenAI, Anthropic, Revolut). To capture exponential future growth, capital must flow into private markets.
Re-evaluating Software Margins: Do not blindly judge AI companies by SaaS gross margin standards. AI companies will likely have lower gross margins due to compute/inference costs, but their terminal operating margins may be higher because AI will shrink Opex (sales, legal, engineering).
TAM Trumps Entry Price: When a market is truly gigantic and a company is growing exponentially, entry valuation becomes the least important factor. The core question is whether the company can realistically become a $50B - $100B+ public entity.
The Power Law is Extreme: Just 4 private companies have generated 65% of the enterprise value in the private markets. Growth investors cannot afford to "spray and pray"; they must consolidate capital into these select platform winners.
Growth Rate Compression: What took cloud hyperscalers a certain time to achieve at scale is being dwarfed by AI. AI native companies are growing at 800% at scales where previous generational winners were growing at 60%.
The Downside of Pre-Revenue Investing: Coatue avoids high-valuation, pre-revenue investments because the risk-reward math breaks down. A fund targeting a top-quartile 3x net return cannot afford zeros, as compensating for a total loss requires an elusive 6x return elsewhere.
The conversation opens with an analysis of public SaaS companies facing significant market cap reductions. Swisher explains that for the first time, the "terminal value" of SaaS is being questioned. Previously, SaaS businesses were viewed as insurance-like annuities with perpetual profit pools. However, recent coding models from Anthropic and OpenAI are threatening these moats. When terminal value is questioned, accounting benefits (like stock-based compensation leniency) evaporate, causing investors to walk away from the sector until the dust settles.
Swisher notes a structural shift: 18 out of the top 20 private platform companies today would have been public a decade ago. If an investor wants to be "ultra-levered long" to the future (e.g., AI, space, next-gen fintech), they cannot do so in the public markets. Companies like OpenAI, Anthropic, SpaceX, and Revolut are choosing to stay private longer, which is a massive gift to growth venture funds but a penalty to retail public market investors.
When dealing with companies growing 10x or 50x year-over-year, Coatue looks at valuation last. The first filter is TAM. Coatue previously used a $10 billion public company test; now, due to AI expanding markets, the test is whether a company can reach $50 billion to $100 billion in market cap. Swisher leverages a framework learned from Insight's Jeff Horing: the best round is the double-down round. Entry price is elastic if the company's trajectory implies you will desperately want to invest more capital at a higher price in the next round.
Swisher shares staggering internal data: 20 private companies have generated 80% of total private enterprise value, and just 4 are responsible for 65%. Because value is so hyper-concentrated, growth funds cannot spray and pray. They must identify the exact right horse. Interestingly, Swisher notes that the statistical probability of a company achieving a 10x multiple actually increases as you move up the market cap bands (e.g., from $10B to $100B) compared to earlier stages.
Discussing the viability of multi-billion dollar funds, Swisher admits that vertical SaaS cannot return these vehicles—the outcomes are too small. However, AI expands TAMs by addressing labor, not just software budgets, enabling trillion-dollar outcomes. To achieve a top-quartile 3x net fund return (~25% net IRR), fund managers must obsess over loss ratios. If an investment returns 1x, the manager needs a 5x elsewhere to balance it. If an investment goes to 0, they need a 6x. Because 6x returns at the growth stage are incredibly rare, Coatue fundamentally avoids high-valuation, pre-revenue companies.
Stebbings questions whether early margins still matter. Swisher clarifies that "margin matters at scale." Historically, massive platform shifts (like AWS, Snowflake, Databricks) featured terrible early margins. AI companies currently suffer structurally lower gross margins due to LLM API and compute costs. However, Swisher argues that AI will drastically reduce Opex (sales, engineering, legal). Thus, a lower gross margin will be substituted by a lower Opex burden, potentially resulting in a higher terminal operating margin than traditional SaaS.
Despite ample private liquidity, Swisher believes platform companies (like Canva) will eventually go public. He cites three reasons:
True liquidity at scale without the opacity of layered SPVs.
The public market acts as an incredible, ruthless feedback mechanism (citing Netflix's successful pivot from DVDs to streaming, which was heavily scrutinized and guided by public analysts).
Public companies are harder to mess with because they become systemic components of indices and 401ks.
Swisher reflects on working with legendary investors. From Mary Meeker, he learned extreme analytical rigor and the ability to "tell stories with data" through complex Excel modeling. However, she taught him that data is a prerequisite, not the final answer. From Mamoon Hamid, he learned the art of spotting inflection points with minimal data, praising Hamid's ability to see massive customer usage stickiness at early stages to aggressively preempt rounds.
When asked where he would put his final dollar between OpenAI and Anthropic, Swisher breaks down the bull case for both:
OpenAI: Possesses an unbeatable consumer franchise, emerging enterprise strength via coding, and a massive "unknown unknown" upside (referencing Jony Ive's secretive hardware design project).
Anthropic: Dominated the coding beachhead early, which translates to all analytical enterprise tasks. Strategically, they built to be compatible with every cloud and every chip (TPUs, GPUs, Trainium), giving them a massive infrastructural and cost advantage in a compute-constrained world.
6. Data & Figures
Data Point
Value
Context
Timestamp
Enterprise Value Concentration
80%
The percentage of total private enterprise value generated by just 20 companies.
Mary Meeker's Excel Rigor [00:48:04](https://www.youtube.com/watch?v=Hom5OMMzOQ0&t=0h48m4s): During his second week at Kleiner Perkins, Swisher (who admitted he couldn't model well at the time) was destroyed in a modeling exercise by Meeker. She taught him that the ability to express a complex company in a few lines of Excel, and instantly spot a cell error from across the room, is a critical storytelling skill.
Mamoon Hamid Spotting Figma [00:51:02](https://www.youtube.com/watch?v=Hom5OMMzOQ0&t=0h51m2s): While an associate at Kleiner, Swisher cut the data for Figma when the company only had $500k in ARR. The market consensus favored InVision, but Hamid looked at the net retention and usage curves from just three early enterprise clients (Google, Square, Amazon) and made the decision to invest within 30 seconds.
The Biggest Miss - Anduril [01:04:31](https://www.youtube.com/watch?v=Hom5OMMzOQ0&t=1h4m31s): Swisher traveled to LA to look at Anduril's billion-dollar round. Because he was strictly a SaaS investor at the time, he applied a myopic, metrics-heavy lens to their P&L. He passed because the P&L was "ugly," missing the forest for the trees regarding the founders' generational talent and the massive defense tech trend.
First Founder Meeting Magic - Harvey [00:59:28](https://www.youtube.com/watch?v=Hom5OMMzOQ0&t=0h59m28s): Swisher's most memorable first founder meeting was with Winston from Harvey. The founder-market fit was immediately obvious: LLMs excel at text-in/text-out, and law is the most text-heavy profession in the world.
Concept: Valuation is a secondary metric if the growth rate is exponential. The true test of a growth stage entry price is asking: "If this company executes perfectly over the next 6-12 months, will I be eager to put more money in at a significantly higher price?"
Concept: In a growth fund targeting a 3x net return, loss ratios destroy fund math. A 1x return demands a 5x winner to balance the math; a 0x (total loss) demands a 6x winner. This model is why Coatue strictly avoids pre-revenue, high-valuation momentum deals.
Concept: Do not penalize AI companies for having low gross margins early on. High cloud and token costs drag gross margins down, but AI efficiencies drastically shrink Opex (sales, engineering, legal headcount). Investors should index for high terminal operating margins rather than standard SaaS gross margins.
9. References & Recommendations
People:
Jeff Horing (Insight Partners) - Mentioned for his philosophy on the "double down round."
Mary Meeker (Bond Capital / Ex-Kleiner Perkins) - Swisher's mentor; praised for her analytical storytelling.
Mamoon Hamid (Kleiner Perkins) - Praised as the best Series A investor of the SaaS era (Slack, Figma, Glean).
Winston Weinberg (Harvey) - Praised for having the clearest founder-market fit presentation.
Jony Ive (LoveFrom / Ex-Apple) - Mentioned regarding his secretive hardware design collaboration with OpenAI and Ferrari.
Companies/Tools:
Claude Code - Highlighted by Swisher as a tool he personally uses that fully convinced him of AI's imminent disruption of labor.
Anthropic, OpenAI, Revolut, SpaceX, OpenEvidence, Canva, Databricks - Cited as the definitive "platform companies" driving private market returns.
10. Speakers & Credentials
Harry Stebbings (Host): Founder of 20VC; prominent venture capital podcaster and early-stage investor.
Lucas Swisher (Guest): Co-leads the Growth Fund at Coatue. Former investor at Kleiner Perkins (under Mary Meeker and Mamoon Hamid) and Insight Partners. Specialist in hyper-growth, AI, and enterprise platform companies.
11. Actionable Next Steps
Shift Focus from SaaS Gross Margins to AI Operating Margins: If assessing AI-native startups, model their long-term Opex savings against their short-term API/inference costs rather than instantly penalizing sub-80% gross margins.
Evaluate Portfolio Loss Ratios: For capital allocators, strictly audit your current portfolio to ensure you aren't holding pre-revenue, high-valuation assets that risk going to zero, as recovering from zeros at the growth stage requires near-impossible 6x returns.
Use AI to Experience the Shift: Swisher explicitly recommends using tools like Claude Code personally to truly grasp the transition from "AI assistants" to "AI agents" capable of labor displacement.
Index for Multiple TAM Expansions: When evaluating a scale-up, ensure the founding team has a demonstrated ability to jump "S-curves" (like Canva moving from yearbooks to enterprise design suites) to justify multi-billion dollar valuations.
Jul 16, 2026
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Target Fund Return
3x
The net return multiple required to be considered a top-quartile fund (roughly 25% net IRR).