The AI Companies Are Setting Your Growth Bar, And Nobody Told You

You planned your year against last year's version of good. The market didn't. It now grades your team against the fastest-growing AI companies on record, and that changes what you bring to your next review. Let me catch you up.

The scoreboard moved while you weren't looking

Investors aren't comparing your growth to last year's startups anymore. They're comparing you to AI companies that are doubling, tripling, quadrupling. Charles Hudson, who has backed more than 500 startups, put it plainly: "They're doubling, they're tripling, they're quadrupling, and the message they're hearing from the market is that's good but not great."

That pressure lands on your desk too. A number that would have looked strong two years ago now reads as flat. The Disrupt 2026 agenda spells out the new floor: $0 to $10M ARR is described as "the new early-stage baseline", and what once took years is now expected in months.

So before you defend your roadmap, know the yardstick you're being measured against. It's not the one you set.

The big number can trap you

Chasing a high valuation or a splashy round feels like winning. Hudson warns it can lock you in. "The real risk with these big rounds is you end up being a prisoner of your own company," he said. "You raise all this money, and you've sold people on a big vision. They don't want the money back, they want you to find a way to build something that's worthy of what they gave you."

The same trap sits inside your product bets. In an AI hype cycle, a usage spike or a pilot win can look like real pull. The Disrupt panel on PMF red flags calls this out directly: excitement is easy to fake, retention is not. Before you scale a feature because the numbers popped, ask whether people keep coming back or just showed up once.

Hiring got harder, and AI is now on the org chart

The talent market is tight and getting stranger. Founders aren't only building with AI, they're deciding what an agent owns versus what a human owns, and rewriting comp to keep people who could leave for an AI startup tomorrow.

Before you copy a hiring bar you inherited, question it. Gergely Orosz argues LeetCode interviews survive for an odd reason: a candidate willing to grind for weeks on a test that looks nothing like the job is signaling they'll "tolerate corporate nonsense." He expects big companies to move back to in-person interviews while keeping those puzzle questions, since AI now solves them in seconds. If your loop is testing tolerance instead of the actual work, you're selecting for the wrong thing.

The skill your team gives up without noticing

Here's the counterweight to all the speed talk. Orosz's take on AI: "AI doesn't make work easier." If life feels easier, he says, "are you trying hard enough?" He uses zero AI in his writing, Grammarly off, because he doesn't want that skill to fade. He does use AI for coding and accepts his hand-coding will degrade.

That's a decision your team should be making on purpose, not by drift. Pick the skills you want to keep sharp and protect them. Let AI take the rest. The point is choosing, so you're not surprised in a year when nobody on the team can do the thing you assumed they could still do.

The deep cut

Hudson's best advice isn't about pitching, it's about honesty. He says he's had more success telling founders, "This is what venture capital needs you to do. Let's abstract away from your company. This is the kind of business you need to want to build. Is that your desire?" Great businesses aren't always venture-scale businesses.

Apply that to your roadmap. The AI-set growth bar only matters if you're actually running the kind of company that has to clear it. If you're chasing a doubling-tripling curve because the market implies you should, but your business doesn't need to return a fund, you're borrowing someone else's pressure. Decide which game you're in before you plan against its rules.

Three questions for your team

• What benchmark are we actually being graded on this quarter, and did we plan against it or against last year's version of good?
• Which of our recent wins are real retention and which are pilot spikes we're about to over-invest in?
• Which skills are we choosing to keep sharp on this team, and which are we knowingly handing to AI?