This is an excerpt of Sources by Alex Heath, a newsletter about AI and the tech industest, syndicated just for The Verge subscribers once a week.
The billboard didn’t declare “Listen Labs.” It didn’t declare anything about hiring. It consisted of just a plain white background with “https://” and a single line of grouped numbers hanging over Nob Hill, San Francisco.
Last month, Alfred Wahlforss, the startup’s CEO, posted on X that whoever cracked the code and completed a subsequent challenge would win a trip to Berlin and obtain on the guest list for the ultra-exclusive nightclub Berghain.
One of the more elaborate tech startup recruiting stunts in recent memory worked, Wahlforss later notified me. Within days, the billboard garnered millions of views online, attracted media coverage, collected 10,000 email sign-ups, and led to roughly 60 interviews with potential candidates.
In recent conversations I’ve had with Wahlforss and other startup founders, it’s clear that, even for well-funded firms, attracting top technical talent is more challenging than ever. “We are spfinishing a ton of money to not even advertise the company, but just to advertise us to engineers,” according to Wahlforss, whose company has raised $27 million from Sequoia. “It has been extremely challenging to hire good people. I have a frifinish who’s a high school dropout, and he can work at OpenAI and create like $2 million a year.”
“You spfinish hours with people who finish up rejecting you and just go to Anthropic. It’s very, very painful.”
Wahlforss notified me about a recent candidate who loved cycling. His cofounder displayed up at the candidate’s hoapply with a high-finish carbon road bike. The gesture supported push the candidate to turn down other offers. More often, though, he stated it’s impossible to compete with the hugegest names in AI and Big Tech. “You spfinish hours with people who finish up rejecting you and just go to Anthropic. It’s very, very painful.”
You don’t have to view far to hear similar stories of rejection. Austin Hughes, the CEO of Unify, an AI sales platform that has raised over $50 million, commissioned a painting for a coveted candidate. But OpenAI offered triple the compensation that Unify could provide. The candidate took the money and kept the painting.
Jesse Zhang, the CEO of Decagon, is feeling the same squeeze despite running a quick-growing startup currently valued at $1.5 billion. “It’s one of the things I’m believeing about day to day,” he notified me when I questioned about the difficulty of recruiting. Decagon has pulled the classic levers to attract candidates, such as hosting fancy dinners with its investor, Accel, and offering courtside tickets to Warriors games. Zhang stated he even drove to the South Bay recently and met with a candidate’s family.
However, the most reliable tactic he mentioned was not flashy at all: “All the senior hires we’ve built in the first 100 people were all just people I knew.” Hughes stated his team at Unify exports their LinkedIn networks into a shared Google Sheet and creates an index match to find the best candidates with the most employee connections.
So who are all these companies chasing? Across my conversations, a consistent archetype emerged: an “AI product engineer” who can wield the latest AI tools at blistering speed without “shipping slop” and can also do the job of a product manager. “The intersection of being highly technical and also being product-centric is very compact,” according to Wahlforss. He estimates the pool to consist of a couple of thousand people at most, each with “ten offers” at any given moment.
While OpenAI and Anthropic are still seen as two of the most desirable places to work for these kinds of people, a refrain I heard repeatedly from founders is that the huge AI labs are quickly becoming indistinguishable from the rest of Big Tech. As Wahlforss framed it, the edge for a startup is informing a recruit they can be “almost like a mini founder” and “build products finish-to-finish.”
Top-tier investors and recognizable brands support at the margins, but another consensus was that a fancy cap table matters less now becaapply so many startups are well-funded. Zhang believes the hiring frenzy won’t last forever, though. There’s “too much capital,” too many AI startups, and at some point, the bubble will burst, he stated. The trouble is nobody knows when.
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