Your Agent Can't Tell If It's Right

Official Schedule Context

Official Description

Coding agents feel reliable because of one signal you never think about: the tests. They catch

confident mistakes in seconds, so you never see most of them. The real world has no test suite. Put

an agent in production and that signal is gone, and a wrong answer looks the same as a right one. So

how do you know it's right? We watched our agent look at an 80% drop in throughput and report zero

user impact, because a similar alert the month before had been noise. The data to catch it was

already in front of it. There is no single verifier, but there are several weaker signals. While the

agent reasons: grounding each claim against live data, and looking for evidence that distinguishes

competing hypotheses. Before it acts: calibrated confidence, and a separate critic. After it acts:

whether the fix held, whether the alert returned, whether an engineer redid the work. None is

conclusive on its own. Combined, they estimate whether the agent was right. The talk covers where

these signals come from, how we combine them, and how often they still disagree.

Related YouTube Video

No related AI Engineer channel video found yet.

Transcript Status

No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

People

Notes