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Companies
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Key Quotes
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Topics
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Insights
🎯 Summary
20VC Podcast Summary: The Shifting Sands of SaaS, AI Disruption, and VC Strategy
This episode of the 20VC podcast, hosted by Harry Stebbings, features a candid discussion with venture capital heavyweights Jason Calacanis and Rory O’Driscoll (GP at Scale). The central narrative arc revolves around the death of first-generation SaaS investing metrics due to market saturation and the radical disruption caused by generative AI, forcing VCs to underwrite significantly higher risk for potentially massive upside.
Key Takeaways for Technology Professionals:
1. The End of Spreadsheet SaaS Investing
- Obsolescence of Old Rubrics: The traditional SaaS playbook—relying heavily on metrics like Net Revenue Retention (NRR) and predictable growth rates (e.g., the “1 to 10 in five quarters” S-tier benchmark)—is declared “dead.”
- Market Saturation: Existing SaaS markets (like document signing or basic cloud migration) have largely saturated. Companies that once achieved predictable “triple, triple, double, double” growth are now flattening out at lower rates (e.g., $50M ARR growing at 10-20%).
- Actionable Insight for SaaS Founders: While traditional, high-growth SaaS companies with proven models are still viable and attractive to investors like Rory O’Driscoll, the real challenge lies with the vast number of mature, slower-growth SaaS companies that lack the “AI magic pixie dust” story needed to excite momentum investors.
2. AI’s Impact: Transient Product-Market Fit (PMF)
- Rapid Evolution: Unlike previous SaaS cycles where products remained static for years (e.g., Box, DocuSign), AI-native startups are experiencing PMF that can be gained and lost in weeks or months.
- Underwriting Extreme Volatility: This rapid change, driven by model progress and evolving user understanding of AI capabilities, means VCs are underwriting significantly more risk at every stage. The upside remains huge, but the downside risk is amplified.
- Founder Intensity: The current environment demands extreme founder dedication. The best AI SaaS startups are characterized by intense, 7-day-a-week work schedules, contrasting sharply with the more relaxed pace seen in some 2021 startups.
3. Strategic Shifts in Venture Capital
- Risk vs. Reward Reassessment: VCs acknowledge they know significantly less about the long-term viability of AI companies than they did about established SaaS models at similar stages. They are underwriting higher risk for a potentially larger upside. The concern is whether current high valuations adequately compensate for this increased risk.
- Bimodal Outcomes: The increased risk and elongated holding periods are predicted to lead to more bimodal results across the VC landscape, meaning more funds will significantly underperform as portfolio construction becomes critical in a riskier game.
- The Momentum Shift: A significant portion (estimated 70-80%) of established cloud SaaS investors are now exclusively focused on AI deals, unwilling to look at traditional SaaS, driven by the desire for rapid, massive returns (e.g., tripling in eight months).
4. The Liquidity Crisis for Mature SaaS
- The $2 Trillion Problem: A massive amount of capital (estimated at $1 to $2 trillion) is tied up in mature, slower-growth SaaS and cloud companies that are too large for small exits but lack the growth profile for current IPO windows.
- Grim Industrial Work Ahead: Exits for this cohort will require “grim industrial work”—grinding toward profitability, pursuing Private Equity (PE) exits, or executing private-to-private consolidations.
- PE Indifference: A major concern highlighted is the lack of “tire-kicking” from PE firms for these sub-scale, non-hyper-growth SaaS companies. PE firms often prefer boring, vertically focused software with high market share where they can raise prices, which are precisely the companies that fail to achieve the billion-dollar outcomes VCs fund.
5. Mentioned Thought Leaders and Frameworks
- Key Personalities: Harry Stebbings, Jason Calacanis, Rory O’Driscoll (GP at Scale), and Victor Lazarte (Benchmark).
- Frameworks/Concepts: The “1 to 10 in five quarters” S-tier metric (attributed to O’Driscoll), and the concept of underwriting risk against inflated upside in the current market.
Context and Significance
This conversation is vital for technology professionals because it confirms a major inflection point: the playbook that generated massive wealth in the 2010s SaaS boom is functionally over. Founders and investors must now navigate an environment defined by speed, volatility, and technological paradigm shifts (AI), where traditional financial guardrails are less reliable, and operational intensity is paramount. The discussion also signals potential future challenges in the mid-market SaaS sector regarding capital realization and exit pathways.
🏢 Companies Mentioned
Lakecraft
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tech/finance
Superintelligence
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tech
SaaS winners (as a group)
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Tech/Software
GC
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Finance/Venture Capital
Volt
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Tech
Dan House
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Finance/Venture Capital
KP
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finance
20VC listeners
✅
media
It I
✅
unknown
And Anthropic
✅
unknown
Now I
✅
unknown
Fidelity Growth
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unknown
New York
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unknown
Fidelity Growth Fund
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unknown
OpenAI IPO
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unknown
💬 Key Insights
"In all my hotter companies the last whatever months, I've seen the later-stage investors put everything into the terms you possible to win. Does no more waiting for rev, the maximum secondary, the maximum refresh, the maximum even cram down the prior investors..."
"If it's an aqua-hire, every dollar you give the venture guys is wasted. So you, you exactly right. You do small headline deal and then large earn-out contracts..."
"Every acquirer is looking for ways to get around all the VC preference stacks. It's aggressive, like it was always true, but now it's like super aggressive."
"Hmm, they cracked the magic code in OpenAI. They have the secret recipe. Fund people who have the secret recipe, and it works. Fund anyone else, and you kind of get a me-too outcome in retrospect."
"If you fast forward three years, all the foundation model companies that weren't populated by people who were at OpenAI haven't done great. And Anthropic... has done pretty well."
"Fund people who have the secret recipe, and it works. Fund anyone else, and you kind of get a me-too outcome in retrospect. That was the larger for doing on topic. They have the secret recipe, they snuck away with the secret recipe back then."
📊 Topics
#artificialintelligence
144
#startup
86
#investment
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#generativeai
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🧠 Key Takeaways
have done when we passed on all the deck of horns because you're in every one, and it maybe solves to $20 billion