Matt Hoffman on why AI should make hiring better, not just faster

Matt Hoffman, Head of Talent and Partner at venture firm M13, joined Kathy Enderes, SVP of Research at The Josh Bersin Company, to talk about how AI has changed the way his team builds talent strategy for early-stage startups.

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Most people pitch AI in recruiting as a speed play: more candidates, faster screens, quicker fills.

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Matt Hoffman doesn't buy that framing, and his job gives him a wide enough view to test it. As Head of Talent and partner at M13, a venture firm that invests in seed and Series A companies, Hoffman and a four-person talent team support close to 100 portfolio companies — building the recruiting, compensation, coaching, and development infrastructure that early founders rarely have time to figure out on their own.

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He joined Enderes on the What Works podcast to talk about where AI actually earns its place in that work, and where it doesn't.

Every hire moves the needle harder in a 10-person company

Hoffman's central argument is that speed is the wrong scoreboard. "You measure recruiting success over 6 to 9 to 12 months," he said. "If you just stop at one person's in the seat, you are not measuring anything but speed. And it actually creates the wrong incentives, because you will hire fast but you won't hire good."

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The stakes are different at the stage M13 invests in. "Imagine you're a 10-person company. Every time you make a hire, you've increased headcount by 10 percent," he said. A bad hire doesn't get quietly absorbed into a larger org chart. It reshapes the team. So Hoffman uses AI to buy his portfolio companies time, not shave it off: less time spent on top-of-funnel triage, more time spent understanding whether a candidate is actually right for the stage the company is at.

Finding the person who did it before, not the person doing it now

Founders default to wanting someone from a recognizable, successful company. Hoffman pushes back on that instinct: what matters isn't where someone works now, it's whether they've already done the specific job the company needs done next.

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"Everyone always wants to hire someone from Google, because they've got pedigree, they've got their experience," he said. "But a lot of early-stage companies don't want someone who's successful at the 500, 1,000, 10,000-person organization. They want someone who's seen the growth."

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His team's version of that query: find someone who worked at a comparable company, in a comparable role, at the exact size and stage the client is at now. Not who holds that title today, but who held it during the stretch that matters. That's the kind of targeting M13 uses Findem to calibrate.

Fall in love with the problem, not the solution

Hoffman's advice to other talent leaders considering AI tools is less about which platform to buy and more about the order of operations. "I always find that to be very shortsighted," he said of teams that start with a technology's capabilities and then look for a use case. "I really encourage HR leaders, founders, anyone I work with, to start with: what do you want to get better at? What is the outcome you'd like to see? And then, from that, find the way the technology can augment that."

AI augments the recruiter, not replaces them

Hoffman's team uses AI to find candidates outside a founder's immediate network and to keep a record of good people over time, so someone they met six months ago can still be the right match when a role finally opens. What AI doesn't do is replace the conversation where a founder figures out what "good" actually looks like for their specific team.

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"That conversation cannot be replicated," he said. His team can't be the full-time recruiting function for every portfolio company, so they've drawn a clear line: go deep with individual founders on defining success criteria and teaching good hiring practice, and go broad across the platform to build a talent community that benefits every company at once.

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Hoffman's conversation with Enderes runs about 25 minutes. It also gets into how his team uses AI to spot the patterns behind why people actually leave a company, and how they tie that back into how they hire. Listen to the full episode on The Josh Bersin Company's site.