Your startup’s next teammate might be an AI agent: Gusto, Insight Partners, and Leland explain what that changes at TechCrunch Disrupt 2026
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Startups are hiring AI agents for support, research, and even engineering. That means founders must decide what humans still own before the org chart hardens.
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The first startup hires used to be all about filling gaps. Now founders are being asked a sharper question: which gaps need people, and which can be handled by AI agents instead? That shift is the premise behind a Builders Stage session at TechCrunch Disrupt 2026 called “Hiring When AI Is a Co-Founder.” Josh Reeves of Gusto, Michelle Johnson of Insight Partners, and John Koelliker of Leland will unpack it at Moscone West in San Francisco from October 13–15.
The topic is not abstract. AI agents are already taking on engineering, customer support, research, and operational work that early employees once owned by default. That changes the math for a small company. A founder is no longer just deciding who to hire next; the real question is whether a person is the best way to get a piece of work done at all.
But handing work to software creates its own mess. Someone still has to check the output, make the final call, and decide which responsibilities are too important to delegate. And when an agent gets something wrong, the accountability doesn’t magically disappear. For AI-native startups, those are practical problems, not philosophical ones.
Reeves brings a broad view from Gusto, which supports more than 500,000 companies across payroll, benefits, compliance, onboarding, HR, and retirement. Johnson comes at it from the scaling side, advising CEOs and CROs on go-to-market, revenue organizations, and AI implementation, after helping Flock Safety grow from less than $1 million to $90 million in ARR. Koelliker adds a talent lens from Leland, where the focus is on how people develop and apply skills in an AI-era labor market.
What ties the panel together is the same hard question: what should early employees still own when agents can already do a lot of the work? The answer will shape not just hiring, but culture, speed, and the kind of judgment a startup values first.
My take — AI-written commentary, not fact-checked reporting
This is the part of AI hype that actually matters: not whether a model can do the task, but whether a founder is willing to own the consequences. Too many startups are racing to automate the easy bits and forgetting that judgment, taste, and blame still need a human face. The org chart is changing, and the boring old skill called accountability is suddenly premium again.
Read more about this at: TechCrunch