Agent Decision Tracer
3
discussions evidencing this problem
Capture decision context and reasoning traces alongside execution logs to reconstruct why an agent made each choice, enabling fast post-mortem debugging and outcome analysis.
3×
discussions evidencing this
3
pain statements
3
distinct people
2
communities
What a useful app would help with
It could help you work out:
- Decision tree with branch conditions
- Outcome correctness assessment
- Recommended action patterns
Based on agent execution logs, tool call sequences, agent state snapshots.
Where the evidence comes from
A sample of the discussions behind this problem.
AI agent builders: what breaks most often in production?
r/AI_Agents
I got tired of my agents repeating the same mistakes, so I built a feedback loop for them — here's what I learned
r/AI_Agents
Debugging agents from traces feels insufficient. Is it just me?
r/LLMDevs
Investigate this idea
Use this as a starting point. Narrow the audience or workflow, then check whether the evidence supports your version.
🔒 You're reading a preview
Sourced from r/AI_Agents and r/LLMDevs. The complete analysis adds:
- The verbatim excerpts behind every pain statement
- The complete source-discussion list, with links to each
- The full set of capabilities people asked for
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