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Your Agents Failed. Now What?

Hivemind now provides execution traces, session replay, and AI-powered error correlation — so you can understand what went wrong and why.

GB

Gabriel Bram

February 22, 20265 min read

The Debugging Problem

An agent fails three hours into a complex refactoring task. You see the task.failed event in the log. But what happened before that? Which files did it touch? Did it make a bad decision twenty minutes earlier that cascaded? Was another agent involved?

Without execution traces, you're left reading raw events and piecing together the story manually. That's fine for simple tasks. It's impossible at scale.

Traces
Waterfall execution view
Replay
Step through agent sessions
Errors
AI-powered root cause analysis

Trace Visualization

Every agent session now generates an execution trace — an OpenTelemetry-style waterfall chart showing exactly what the agent did. Each event becomes a span with timing, type, and parent-child relationships.

The waterfall makes it immediately obvious:

  • How long each operation took
  • Where errors occurred in the flow
  • Which tasks were parents of other work
  • The ratio of productive work to overhead
Traces are zero-config — they're derived automatically from your existing events. If your agents include a session field in their source (which the MCP server does by default), traces just appear.

Session Replay

Click into any trace and switch to the Replay tab to get a chronological timeline of the agent's session, grouped into chapters by task boundaries.

This is the view you want during a post-mortem. Instead of scrolling through raw events, you see a structured narrative: "First the agent did this task, then it made this decision, then it edited these files, then it failed here."

Error Correlation

The new Errors page automatically groups related failures across agents. When two agents hit the same kind of error, Hivemind:

1. Normalizes the error message (strips variable data) 2. Fingerprints it for deduplication 3. Groups occurrences together 4. Tracks which agents and sessions were affected

Click Analyze Root Cause on any error group, and Hivemind sends the error context to AI for analysis. You get back a concise hypothesis and suggested fix.

Errors that have been resolved but recur automatically re-open. No more "I thought we fixed that."

What's Next

Observability is the foundation for proactive optimization. In upcoming releases, we'll add automated anomaly detection, performance regression alerts, and suggested agent configuration changes based on trace patterns.

observabilitytraceserror-correlationdebugging