To find talent capable of managing an AI stack, traditional interviews are insufficient. A better test is to provide candidates with platform credits (e.g., Replit) and challenge them to build a functional agent that automates a real business task, proving their practical skills.

The standard for being "AI fluent" has evolved past being a "prompt engineer." The new hiring benchmark is whether a candidate has recently brought a commercial AI tool into their organization. This demonstrates a practical, results-oriented ability to leverage AI, not just experiment with it.

Traditional product sense questions are being replaced. AI PM candidates should expect to solve problems live using AI tools or design complex AI-native systems. This shift assesses a candidate's hands-on "builder" capabilities and deep understanding of modern AI architecture.

To assess a product manager's AI skills, integrate AI into your standard hiring process rather than just asking theoretical questions. Expect candidates to use AI tools in take-home case studies and analytical interviews to test for practical application and raise the quality bar.

To build an AI-native team, shift the hiring process from reviewing resumes to evaluating portfolios of work. Ask candidates to demonstrate what they've built with AI, their favorite prompt techniques, and apps they wish they could create. This reveals practical skill over credentialism.

Ramp requires all new hires, regardless of role, to be proficient with AI tools. The interview process for product managers now includes a practical session where candidates must build and present a functional product prototype using AI, demonstrating hands-on skill rather than just theoretical knowledge.

Zapier's hiring process now requires candidates to demonstrate 'AI fluency' through repeatable systems that measurably improve their work. Merely using AI for one-off tasks is insufficient; they must show how AI is deeply embedded into their core workflows, setting a new bar for talent.

Glean has updated its interview process to screen for "AI fluency" across all departments. They don't expect expertise. Instead, they test for curiosity and initiative by asking candidates how they've personally used AI, looking for a mindset that embraces new ways of working.

In the near future, top candidates will demonstrate their value by showcasing the custom AI agents they've built. This portfolio proves their ability to multiply their own productivity and bring a force multiplier to a new role from day one.