Dave McClure

At our recent LP Advisory Council meeting, LPs asked about headlines claiming AI is undermining SaaS. Our view is that the two are mutually reinforcing, not mutually exclusive. We are bullish on AI, and we believe certain SaaS leaders (with systems of record/action, first-party data and data rights, network effects, ambitious AI roadmaps, etc.) are well-positioned to capitalize on the agentic AI opportunity. There are multiple reasons for this. To start, consider what’s happening today with SaaS. The median company in the SEG SaaS Index grew 13% in Q2 while doubling its EBITDA margin year over year, with a top quartile growth rate above 20%. SaaS accounts for only 25% of overall software revenue in 2025, according to Gartner, so secular growth from on-premise to SaaS migrations should continue for years. Notably, this growth largely comes before many SaaS firms monetize a new wave of agents. Meanwhile, small AI startups with little revenue are burning cash and trying to sell. At the other end of the spectrum, Klarna’s much-hyped move to replace Salesforce with AI proved overstated; the CEO later said he was “tremendously embarrassed” by the fallout. SaaS pessimists might ask themselves: Has any large enterprise successfully replaced SaaS systems of record with an LLM? Rather than the AI-SaaS story being one of complete disruption, I believe it’s moving in waves, not unlike how businesses have historically incorporated new technologies:  ● Wave 1 (2023): “Get me some AI so we’re not left out” (a reprise of 1996’s “build a web page and we’ll figure it out later”). ● Wave 2 (2024-mid 2025): “Show me the budget and ROI. Also, why do we need an expensive AI model over a cheap one?” ● Wave 3 (late 2025): "I need enterprise-grade AI that integrates seamlessly, delivers measurable results and won’t disrupt core ops with experimental tools." We can’t say for sure what will happen next, but we do know how software brings value to the enterprise. SaaS is more than software code; it’s digital business intelligence using code to express that intelligence. That takes massive data sets and business experience brought to bear on enterprise functions, at scale and over time. It’s about executing tasks efficiently today, then innovating new tasks over time. For these reasons, we see a supercharged future of AI-enabled enterprise software that enhances productivity and innovation in dramatic ways. That future is less about ever-larger foundation models or narrow AI startups that complicate the stack. Instead, we see integrated software systems that orchestrate digital services to accelerate complex tasks, with agents as the 2026 step-function. AI is a massive force multiplier in that equation, but not a radical disruptor. At Thoma Bravo, we welcome the AI-SaaS conversation. We’re healthily paranoid as part of our mindset. But evidence, history, and business logic suggest that the AI revolution is set to accelerate SaaS value and growth, not undermine it.

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Pablos Holman funds what shouldn’t be possible. Not in labs with neat rows of test tubes. Not in boardrooms with PowerPoints. He builds it in the chaos where ideas meet code, and technology meets the impossible. He helped start Blue Origin for Jeff Bezos and the Intellectual Ventures Lab for Nathan Myhrvold. He didn’t just follow instructions. He invented technologies no one had thought possible, tackling some of the biggest challenges facing humans. “Most people look at technology and see tools. I see superpowers,” he says. “If we push hard enough, we can change everything humans do.” Pablos is a hacker in the truest sense. Fluent in everything about computers. Obsessed with zero to one. He’s not satisfied with incremental progress. He wants breakthroughs. He shares his explorations and conversations on The Deep Future Podcast, giving listeners access to the same ideas and debates that shape his own thinking. It’s not just about technology. It’s about making the future as awesome as possible. If you want to understand the frontier of human innovation and how technology can solve the world’s biggest problems, you’ll want to pay attention to Pablos.

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Is your AI startup's first $10M ARR really just a tech echo chamber? Our latest analysis reveals that for Bay Area founders, 60-65% of early revenue comes from fellow tech companies—not the broader U.S. market in states like Ohio or Florida—based on data from CB Insights, PitchBook, and McKinsey. We've unpacked global variations, counterexamples like Veracyte and Kabbage, and actionable strategies to break free—check out the full breakdown in my new post! What’s your take on diversifying beyond the Valley bubble? Share your experiences or tips in the comments! https://lnkd.in/gCKTVyT4 #AIStartups #TechRevenue #Entrepreneurship #VentureCapital

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