Research notes from the lab.
Method notes, findings, and field observations.
How to Know If AI Is Any Good at Employee Listening
AI in HR has no shared standard for evaluating quality — no bar exam, no FDA equivalent — leaving organizations to guess whether the tools they're deploying are actually reliable. This post introduces PYX Labs and the thinking behind PYX-Voice, the first benchmark built to close that gap in workplace AI: domain-specific, expert-graded, and designed to measure not just whether AI can complete employee listening tasks, but whether it applies the right judgment when it does.
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What Frontier AI Gets Wrong About Employee Feedback: Inside the First PYX Labs Webcast
In our first webcast, Joe Freed and Sarah Foster sat down with Stanford's Melissa Valentine to unpack what PYX-Voice found when we tested seven frontier AI models on real employee-listening work. The short version: the models are more fluent than they are reliable, reasoning power didn't predict performance, and the harder and more human the feedback, the more they struggled. Here's the recap, plus the full recording.
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AI Can Summarize Employee Feedback. A New Benchmark Shows It Doesn't Always Understand It.
PYX-Voice, the industry's first benchmark for how AI understands employee feedback, finds it often misses the meaning behind complex workplace experiences.
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Introducing PYX Labs: How Good Is AI, Really, at Understanding People at Work?
AI already shapes how organizations read employee feedback. PYX-Voice, our first benchmark, found frontier models far stronger on numbers than interpretation.
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