This article is adapted from Sources by Alex Heath, a newsletter focusing on AI and the technology sector, made available to Technology News subscribers weekly.
A recently unveiled billboard in Nob Hill, San Francisco, featured a simple design—only a plain white background with the text “https://” and a string of numbers. There was no mention of “Listen Labs” or any hiring announcements.
In a social media post last month, Alfred Wahlforss, CEO of the startup, invited speculation by promising a trip to Berlin and a spot on the guest list at the elite nightclub Berghain for anyone who could decipher the code and complete a follow-up challenge.
Wahlforss later remarked that the recruiting stunt proved effective, generating millions of online views within days, attracting media attention, collecting 10,000 email sign-ups, and resulting in around 60 interviews with prospective employees.
During discussions with Wahlforss and other startup leaders, the consensus emerged that securing skilled technical talent has become increasingly difficult, even for companies with substantial funding. Wahlforss noted, “We are spending a ton of money not just to advertise the company but to appeal specifically to engineers.” His firm has raised $27 million from Sequoia, yet he acknowledged that hiring talented individuals has proven to be a formidable task. “I have a friend who dropped out of high school and can earn around $2 million a year at OpenAI,” he added.
“You spend hours with people who end up rejecting you and just go to Anthropic. It’s very, very painful.”
Wahlforss recounted a scenario involving a candidate passionate about cycling, whose cofounder surprised him with a high-end carbon road bike, a gesture that influenced the candidate to forgo other job offers. However, Wahlforss expressed frustration at the intense competition with larger tech firms, stating, “You spend hours with people who end up rejecting you and just go to Anthropic. It’s very, very painful.”
Similar tales of recruitment struggles are shared widely. Austin Hughes, CEO of Unify, an AI sales platform with over $50 million in funding, once commissioned a painting for a highly sought-after candidate who ultimately accepted an offer from OpenAI, which provided triple the compensation.
Jesse Zhang, head of Decagon, is also navigating similar challenges as his fast-expanding startup is presently valued at $1.5 billion. He noted that attracting talent remains a daily concern for him. To entice candidates, Decagon has employed traditional methods, including hosting luxurious dinners and providing courtside tickets to NBA games. Zhang even visited a candidate’s family in the South Bay recently.
Despite these efforts, Zhang highlighted that the most effective strategy has been quite straightforward: “All the senior hires we’ve made in the first 100 people were just people I knew.” Hughes explained that his team at Unify utilizes their LinkedIn connections by organizing them into a shared database to identify the best candidate referrals.
So who exactly are these companies trying to attract? In discussions, a recurring profile emerged of an “AI product engineer” who can adeptly utilize advanced AI technologies and simultaneously handle product management duties. Wahlforss described this archetype as being rare, estimating that only a few thousand individuals fit this description and many possess “ten offers” at any given time.
While OpenAI and Anthropic continue to be popular choices for these professionals, many founders have observed that big AI labs are quickly blending in with traditional tech giants. Wahlforss emphasized that startups’ advantages lie in offering candidates a chance to be “essentially a mini founder” and contribute to product development from start to finish.
While backing from prominent investors and reputable brands can add some appeal, many believe that these factors are becoming less significant since numerous startups are well-capitalized. Zhang voiced concerns about the longevity of the current hiring surge, suggesting that an oversaturation of capital and AI startups could eventually lead to a downturn; however, the timing of such an event remains uncertain.
