Agent Session Search
Search across coding-agent sessions to find prior decisions, repeated failures, terminal output, implementation attempts, and reusable workflow patterns.
// who it helps
Teams that need to recover context from long or repeated agent sessions.
// the painful moment
Why this matters
Important agent context is easy to lose because it lives across chats, terminal output, local files, and partial attempts. Search needs to understand the work, not just the final commit.
What AgentPM captures
- Searchable prompts, replies, commands, output, and extracted keyframes.
- Conversation-level context across repos, projects, and connected machines.
- References back to exact transcript turns for evidence review.
What teams can do
- Find the session where a decision was made.
- Recover a fix, command, or setup clue from previous work.
- Identify repeated work that should become documentation or a skill.
Questions this answers
- Have we solved this agent setup problem before?
- Which session introduced this implementation decision?
- Where did the agent explain a failed approach?
// roles
Who uses this evidence
Agent Session Search matters to different teams for different reasons. AgentPM keeps the same session evidence useful for the people building, reviewing, funding, and governing coding-agent work.
Builder
Developers
Keep the flow of agent-assisted building without losing the prompts, commands, retries, and decisions that made the work happen.
Read role pageTeam
Engineering Leaders
See how agent-assisted work is unfolding across a team before the only artifact is a polished pull request.
Read role pageDelivery
Product and Program Leaders
Understand how agent-assisted work moves from intent to implementation when the important context never made it into the ticket.
Read role pageRisk
Compliance and Security Teams
Review agent-assisted engineering work with the surrounding session context security teams need for risk triage and policy design.
Read role page// connected use cases
Where this fits in AgentPM
Evidence layer
Coding Agent Observability
See the coding-agent work that happens before a pull request, ticket, or review: prompts, commands, retries, files, decisions, and unresolved loops.
Cursor
Cursor Session Tracking
Capture Cursor agent transcripts alongside Claude Code, Codex, and Grok work so teams can review prompts, edits, tool output, and unresolved loops in one evidence layer.
Coaching
Agent Workflow Coaching
Use real coding-agent sessions to spot repeated friction, planning misses, skill gaps, and reusable practices your team can improve next week.
// comparisons
How to compare this layer
AgentPM is not trying to be the model trace, eval, gateway, ticket, or code host. It preserves the local coding-agent work that explains what happened before those systems have a clean artifact.
Browse comparisonsLLM application framework and LangSmith observability
AgentPM vs LangChain
LangChain and LangSmith help teams build, trace, evaluate, and monitor LLM applications. AgentPM tracks how coding agents build software before the PR.
AI app observability and evaluation with Weave
AgentPM vs Weights & Biases
W&B Weave helps teams evaluate, monitor, and iterate on agents and AI applications. AgentPM tracks coding-agent software development work.
Open-source LLM engineering platform
AgentPM vs Langfuse
Langfuse helps teams trace, evaluate, analyze, and manage prompts for LLM applications. AgentPM tracks the coding-agent work that creates software.
// fit
What AgentPM is not replacing
AgentPM does not replace code search. It searches the surrounding session history that code search and issue trackers usually miss.
A typical workflow
- 01Capture sessions from connected developer machines.
- 02Search by repo, concept, command, file, decision, or error.
- 03Open the notebook or insight that contains the relevant evidence.
- 04Promote repeated patterns into docs, skills, or team conventions.
// common questions
Questions about Agent Session Search
Why not just search GitHub?
GitHub search finds committed code and PR discussion. AgentPM finds the agent work around the code: prompts, commands, failed attempts, decisions, and open loops that may never appear in GitHub.
Can AgentPM help with repeated agent mistakes?
Yes. Searching and reviewing sessions helps teams spot repeated friction, such as missing setup steps, flaky commands, skipped planning, or recurring review issues.
What is AgentPM?
AgentPM is an evidence layer for coding-agent work. It captures local agent sessions, makes them searchable, and helps teams understand what happened before work becomes a pull request, ticket, or review.
How is AgentPM different from LLM observability?
LLM observability usually tracks model calls, traces, cost, latency, and evals inside AI systems. AgentPM tracks agent-assisted software work: what was asked, what the agent tried, what changed, what failed, what shipped, and what should become reusable knowledge.
Does AgentPM replace GitHub, Jira, or Linear?
No. AgentPM captures the work that happens before those systems have a clean artifact. It complements code hosts, issue trackers, and review tools with searchable session evidence.