I detected a bad Agent action, what do I do about it? this is pretty much the main question that will power the future’s Human+Agent driven …

I detected a bad Agent action, what do I do about it? this is pretty much the main question that will power the future’s Human+Agent driven improvement loops Gather data -> Mine Errors -> Find out which piece(s) of the agent is contribute to this behavior -> Apply Fix -> Test -> Loop The most important boundary in agents is the context window, it’s the box on which all LLM computation actually happens. The first thing you want to try is optimizing context engineering. No model can solve an issue without the necessary information From there work backwards all the way to swapping out or adding a model or The loop is driven by running agents, Tracing + Monitoring them, and gathering feedback to classify, understand, fix, and test errors at scale Every piece of data an Agent produces is a potential avenue to improve it, the dream is to help every team turn that data into actionable edits to improve agents over time and at scale

Source: Harrison Chase (X) | 2026-05-05