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Ship reliable agents

Laminar catches every agent failure, surfaces what to fix, and confirms the fix resolved it.

01.

Get alerts when your agent breaks.

Describe what you want to track in plain English. Laminar analyzes traces of your agent and pings you in Slack the moment a trace matches.

Laminar

APP

3:18 pm

Failure

: New Event

Agent run flagged 4 issues. In one anthropic.messages the agent decided to run python (macOS only ships python3), Bash then hit command not found three times before recovering, a parallel Bash pair cascade-cancelled, and Read missed when the shell CWD drifted after a cd.

View Trace

View similar events

NotificationsLearn more
02.

Understand why in seconds.

Go from issue description to the exact step that caused it.

Agent run hit avoidable failures

Agent run flagged 4 issues. In one ai.streamText.doStream the agent decided to run python (macOS only ships python3), bash then hit command not found three times before recovering, a parallel bash pair cascade-cancelled, and read missed when the shell CWD drifted after a cd.

Trace viewLearn more

Clear, concise view of your agent run

Laminar makes the agent run navigable by surfacing input, LLM reasoning, tool calls, and sub-agents as a readable transcript.

Trace transcript
TranscriptLearn more

Long complex run? Chat with AI

Ask any question, dive deep into any agent run. Click span references to jump straight into context.

03.

Has this issue occurred before?

Laminar groups the events your Signals find into named clusters and tracks each one over time. When a cluster stops recurring, Laminar resolves it — and reopens it if the issue returns.

Signal clustersLearn more
04.

Claude, fix my agent

With the Laminar MCP or CLI your coding agent gets all the context. It can write the fix, run your agent again, and query data with raw SQL to confirm the fix worked.

>
? for shortcutsclaude-opus-4-7 · 1M context
05.

Did my fix work?

Every error cluster you fix can automatically be turned into an eval dataset. Run evals after a change to catch regressions and iterate with confidence.

evaluations/opus-4.5
Average
0.41
0.58
0.17 (40.61%)
Status
Target
Duration
Index
Data
Metadata
"pyknotid"
591.90s427.30s
0
"pyknotid is a knot identification library — implement the new identifier."
{ "lang": "py", "tier": "swe-bench" }
"pMARS sim"
788.41s204.31s
1
"Build pMARS (the Multi-Arena Redcode Simulator) from the seed sources."
{ "lang": "c", "tier": "swe-bench" }
"flat ancestry"
290.56s96.14s
2
"You're given a tree of users — produce a flat ancestry mapping."
{ "lang": "py", "tier": "easy" }
"husky hook"
110.35s344.15s
3
"Configure a git pre-commit hook that runs lint and type-check."
{ "lang": "shell", "tier": "easy" }

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One platform for every stage of agent development.

“We run millions of agent sessions in our cloud, and when something goes wrong, Laminar’s trace view is the first place we look”

Magnus Müller, CEO

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