Laminar

Laminar is built for teams shipping autonomous agents, where traditional application monitoring misses the interesting part: the reasoning chain. It instruments your stack to capture LLM calls, tool calls, sub-agents, token usage and cost, then renders everything as a readable transcript so you can see exactly what an agent did and why. Integrations cover the common agent frameworks and SDKs, so setup is typically a few lines of code rather than a custom telemetry project.

The differentiating feature is Signals: instead of requiring you to define every error condition in advance, Laminar analyzes every run with a custom model optimized for trace analysis and clusters similar failures into patterns. You get a distribution of what your agent actually does wrong, which makes triage far faster than reading logs one by one. Alerts land in Slack, and an agent can answer questions about your traces in-channel.

Once you fix a failure cluster, Laminar can turn it into an eval dataset. Run those evals after each change to catch regressions, and use the CLI or MCP integration to give a coding agent SQL access to platform data so it can investigate traces and verify fixes itself. Laminar is open source, offers a free starting point with GitHub sign-in, and provides paid tiers for production scale on its pricing page.