As you manage a fleet of agents, you cannot manually review every output. Platforms like HyperAgent use "Rubrics"—an evaluation framework where one LLM judges another's work against predefined criteria. This automates quality control, which is essential for scaling an agent-first business.

Despite extensively using custom AI for interview analysis, Formation Bio finds that AI for candidate sourcing is still immature. Their talent team insists on a human reviewing every resume, highlighting that sourcing remains a significant automation challenge due to the need for nuance and confidence in evaluation.

Rather than creating assessments that prohibit AI use, hiring managers should embrace it. A candidate's ability to leverage tools like ChatGPT to complete a project is a more accurate predictor of their future impact than their ability to perform tasks without them.

To evaluate candidates, run the same case study through an AI agent like Claude. This creates an objective performance floor; if a human candidate cannot outperform the AI's output, they fail to meet the minimum standard for the role, providing a practical filter in the hiring process.

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.

The next wave of AI in hiring moves beyond asynchronous video interviews where recruiters manually review recordings. Talent Sprout exemplifies this shift by using conversational AI that not only engages candidates naturally but also evaluates their responses in real-time. This dual capability—conversation and evaluation—automates the initial screening process.

Create an AI agent that automatically reviews interview transcripts. By feeding it a job description and company values as knowledge sources, the agent can provide a "yes/no/maybe" hiring recommendation with reasoning, serving as an effective thought partner and bias check for hiring managers.

The company uses a custom AI tool that analyzes interview transcripts and scorecards. By providing the AI with context on company values and philosophy, it can identify thematic signals of alignment, moving beyond simple keyword matching to a more nuanced evaluation of a candidate.

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.