Debugging
Why your AI agent failed last Tuesday (and why you will never know)
The uncomfortable truth about AI agent failures in production: there are no logs, no replay, and no way to reconstruct what happened after the fact.
Debugging, reliability, and the hard problems of running AI agents in production.
The uncomfortable truth about AI agent failures in production: there are no logs, no replay, and no way to reconstruct what happened after the fact.
Beyond downtime: the compounding costs of running agents you cannot see — from customer impact to engineering time lost to debugging in the dark.
A deep comparison of logging capabilities across the major agent frameworks — what they capture natively, where they fall short, and how to fill the gaps.
Adapting traditional SRE post-mortem practices to AI agent failures — what's different, what's harder, and a step-by-step process that works.
Tracking token usage and latency is not enough. Here's why agent observability is a fundamentally different problem from model observability — and what you actually need.