Why We Should Stop Paying Attention to the % of AI Projects which Fail (and Instead Learn Why the Others Succeed)

This episode starts with a familiar scene. A role opens, the applications pour in, and suddenly you're staring at a mountain of resumes that deserve real attention but arrive faster than anyone can process. The mix had everything… experienced candidates, newcomers trying to break in, and a growing stack of AI-generated submissions that looked sharp until you asked a second question. That's where Haystack came in. Instead of using AI as a blunt filter, Rob and the team treated it like a collaborator. Teach it what matters. Teach it what P3 looks for in a teammate. Teach it how to separate real signal from polished noise. What came back wasn't a robot recruiter. It was clarity. And Haystack is only half the story. As the conversation unfolds, Rob and Justin zoom out into the broader pattern they're seeing across all the small, useful agents taking shape inside P3. The stuff that isn't blind hype. The stuff that quietly fixes overloaded parts of the business and makes the human decisions easier to get right. Because that's the through-line here. When AI handles the overflow, people get to spend their time on the work that actually requires judgment. Queue it up and hear what happens when AI stops pretending to be magic and starts doing real work. And if you've got a corner of the business that's begging for that kind of clarity, we can help you find the tiny build that changes everything.