Agent Observability

Why logging isn't enough for AI agents — the case for tracing

Following the chain from input to output across multi-step workflows

Logs that machines and humans can read — what, when, how

Latency, token usage, success rates, cost per task

Root cause analysis for non-deterministic systems

LangSmith, Langfuse, Helicone, Weave, Phoenix, Braintrust — setup and comparison

Real-time visibility into agent performance and health

Alerts, anomaly detection, and incident response for agents

Know where every token dollar goes — budget alerts and controls

Proxy-based observability, experiment tracking, and the 2025+ tool landscape

Treating prompts as versioned artifacts with A/B testing