How Podium Traces Every AI Agent Decision
Podium uses LangSmith to trace agent chain-of-thought and debug unexpected AI behavior
“The reality is when you really get into the details of what context that agent was provided, It becomes obvious the agent was behaving rationally.”
Podium deployed AI agents in production and adopted LangSmith for end-to-end tracing to understand why agents produced unexpected outcomes. The key insight is that apparent misbehavior usually traces back to unclear or incomplete context and instructions given to the model. This reinforces the growing practitioner consensus that agent observability tooling is essential for production AI systems.