Talent
Greenhouse’s Daniel Chait: Hiring Is Broken and Nobody’s Winning
For most of the last two decades, hiring has worked like a pendulum. Either employers had the leverage or candidates did. Daniel Chait’s argument is that the pendulum has stopped, and right now, nobody is on the winning side of it.
In this episode, Joelle talks with Daniel Chait, co-founder and CEO of Greenhouse, about how the hiring market ended up in what he calls a doom loop: candidates use AI to apply to more jobs, companies use AI to screen faster, and both sides get worse results for the trouble. They cover what the best companies do differently before AI enters the picture at all, why structured hiring matters more now than ever, and whether an AI interview can actually widen access to a first conversation.
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Chapters
[00:00] Introduction
[00:52] Meet Daniel Chait
[02:07] Hiring is broken, and both sides are losing
[03:18] Volume went up, signal went down
[05:10] The doom loop, and why cutting recruiters deepens it
[08:41] What the best companies do differently
[11:04] Does structured hiring still matter?
[12:52] People are bad at interviewing
[14:52] What candidates actually think about AI interviews
[18:48] The real bias is in who gets an interview at all
[20:27] Opening the funnel wider
[23:12] Joelle’s story: the candidates who weren’t real
[26:44] Who is behind fake applications, and why
[29:58] How fraud rings exploit good interview practice
[32:46] Why the risk is worth taking seriously
[33:58] Greenhouse’s three layers of defense
[36:53] Where does the senior talent of the future come from?
[41:32] Equipping a company for transformation
[43:55] Disrupt ourselves before we’re disrupted
[46:18] Paying for performance in a new era
[48:27] Lightning round
Key Takeaways
Daniel Chait is the co-founder and CEO of Greenhouse, the hiring platform used by more than 7,500 companies. He co-founded the company in 2012 with Jon Stross, after starting the financial technology consultancy Lab49, and he co-wrote Talent Makers, a book making the case that hiring is a leadership responsibility rather than a recruiting one.
Volume went up, and signal went down at the same time. Applications per recruiter on Greenhouse have risen 412% since 2023. When everyone uses the same tools to tailor a resume to the same job description, the fact that someone applied stops telling you anything about whether they want the job or can do it.
Daniel’s diagnosis is that the problem is not AI, it is AI layered on a process that was already chaotic. If a hiring team has never agreed on what good looks like, automating the decision just multiplies whatever idiosyncratic beliefs were already in the room.
The companies where hiring works share two unglamorous traits. Executives and hiring managers treat hiring as their own job rather than something they hand off to recruiting and then critique, and they run a structured process with a defined rubric.
He makes an argument for AI interviews that has nothing to do with cost. According to Greenhouse’s data, Daniel says roughly 99.7% of applications in today’s market are never seen by a person, and the decision about who gets a first conversation has long been one of the most biased points in the process. A well-known field experiment published in 2004 found that resumes with white-sounding names received 50 percent more callbacks than otherwise identical resumes. If a structured first-round interview is cheap enough to offer everyone, that gate stops being a gate.
Candidates are not rejecting AI so much as rejecting how it has been used. In Greenhouse’s 2026 Candidate AI Interview Report, which surveyed 2,950 active job seekers, 63% had already been interviewed by an AI, and 38% had walked away from a process because it included one. The complaints were consistent: the experience felt wooden, most were never told AI would be involved, and few trusted that it was fair.
Fraud in the pipeline is rare and expensive. Joelle describes getting deep into a process with two engineering candidates whose answers were flawless, then discovering on a reference call that the person on screen was not the person on the LinkedIn profile they had sent. Daniel explains that organized groups have learned to exploit good interview practice because a well-run panel discusses how someone answered the questions and never mentions that this candidate looked nothing like the one from the previous round.
Greenhouse’s answer is layered rather than singular, on the theory that no single check holds. Intent matching against a calibrated rubric, then signals from the digital trail an application leaves behind, and then third-party identity verification is handled outside the employer’s own systems.
Show Links
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