Velocity is the moat

“For more than a decade, equity markets were built around a simple premise: durable franchises deserved durable multiples. Investors weren’t just buying earnings. They were buying time.”

That’s Jordi Visser, quoted in Chris Neumann’s Q1 2026 newsletter, and I’ve been turning it over ever since. The full line goes: “AI does not simply disrupt business models. It compresses time.”

If you accept that framing — and I think it’s basically right — then the downstream consequences are significant. Because if time was the moat, AI is the acid.

The traditional logic of durable competitive advantage was: you get to something first, you build, you compound. The time buffer between your advantage and someone else copying you was worth paying for. That’s what “durable multiple” actually meant. You were paying for runway, not just earnings.

AI shrinks the runway. The gap between good idea → working product → distribution is collapsing. Chris’s VC data makes this vivid: Carta’s numbers show the top 5% of US Seed rounds in Q4 2025 had an average valuation of $115.5M. The median was $24M. Same round class. Five times the spread. The explanation isn’t randomness — it’s the AI-native companies whose revenue tracks usage, growing faster than the traditional startup growth curve ever allowed. Not optimizing the curve. Compressing it.

So what’s the moat now?

Jordi’s answer is velocity. The ability to learn and adapt faster than the competition. Not what you’re building — how fast you can rebuild when the world shifts.

I think that’s right, but incomplete. Velocity is necessary. It’s not sufficient. Adaptability without direction is just motion. The question isn’t only how fast you move — it’s how fast you move toward the right thing.

When I look at the companies I see pulling away right now, they share something more specific than raw speed. They have genuine, hard-won insight about a specific problem domain, and they’re using AI to act on that insight faster than anyone else can. The knowledge is the direction. AI is the engine.

Which means the winner isn’t necessarily whoever learns to use AI first. It’s whoever had the deepest understanding of their customer and their market before AI, and can now move on it at machine speed. That’s a traditional moat — domain expertise, customer trust, years of accumulated pattern recognition — turbocharged.

There’s a warning buried in Chris’s post for founders right now. He’s calling it a Seed crunch, and it’s not driven by a lack of capital. It’s because most Seed funds are rethinking their investment criteria from scratch. Companies with real revenue and prominent logos aren’t getting first meetings. The goalposts moved, fast, and most people outside of the Bay Area don’t know it yet.

Chris puts it simply: the rate of change in San Francisco has gone stratospheric over the last three months, and founders outside Northern California genuinely have no clue.

I’m in Seattle, not SF. Close enough to feel this. Far enough to watch the gap grow.

The practical upshot for any founder raising capital in 2026: if AI is compressing your timeline to traction, that’s leverage. If it’s compressing your timeline to commoditization, you have a different problem.

Time was the moat. Use whatever time is left.