Episode Details

What's really happening inside AI agents when they give you the wrong answer?

The common story is that smarter models mean safer agents — but the reality is that reasoning traces and final outputs often operate as two entirely separate processes.In this episode, I share the inside scoop on why AI agents fail in production and how to build evals that actually catch it:

- Why agents perform worst precisely where the stakes are highest

- How reasoning traces routinely contradict an agent's final recommendation

- What factorial stress testing reveals that standard benchmarks completely miss

- Where to build the four-layer architecture that keeps agents honest in production

Operators who ignore this now will face it later — through customer harm, regulatory pressure, or an insurance policy they can't obtain.

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