TRACE SUMMARY
run_8F3A2D
DECISIVE ERROR STEP
span_42·Agent: Planner
Downstream impact high
OpenTelemetry-native debugger for multi-agent systems
Find the step that changed everything.
Turn a failed agent run into a causal diagnosis. 404 AI finds the earliest decisive error step, then lets you replay the fix without stochastic noise.
01 / CAUSAL GRAPHStructure over noise.
What changes
From a long trace to one defensible next move.
3framework starting pointsLangGraph · CrewAI · AutoGen
1decisive error stepearliest causal break
4moves from failure to fixingest · graph · traverse · replay
The diagnosis
A failed run is not the diagnosis.
Observability can show what happened. 404 AI follows the causal chain to the earliest step whose correction could change the outcome.
TRACE / 8F3A2D
Make the signal legible.
See the agent, tool call, memory state, deviation, and downstream impact that support a suspected decisive step. The graph is the explanation, not another log view.
Inspect the workflow
SIGNAL / EARLIEST BREAK
How it works
Trace the cause. Test the fix.
A debugging workflow built for systems where one small reasoning step can shape everything downstream.
01
Ingest the run
Bring in OpenTelemetry spans from LangGraph, CrewAI, or AutoGen without changing the workflow you are debugging.
span / tool_call / memory02
See the causal graph
Agent steps, tool calls, memory operations, and downstream effects become one Multi-Agent Cognitive Execution Graph.
MACEG / structure03
Traverse the failure
Counterfactual Causal Traversal backtracks to the earliest Decisive Error Step, then tests whether a correction changes the outcome.
CCT / DES04
Replay the branch
Snapshot state at span boundaries and replay with controlled seeds, temperatures, and mocked tool outputs.
replay / controlledDeterministic control
When the fix matters, replay it.
Snapshot state at span boundaries. Reinject the same context. Change one variable. See whether the branch recovers.
REPLAY / CONTROLLED BRANCH
State snapshots
at span boundaries
Controlled variables
seeds · temperatures · tool outputs
Counterfactual check
did the outcome change?
Evidence first
Stop rerunning the whole system.
Move from broad inspection to a precise question: which step first put the run on the path to failure?
Confidence and uncertainty stay visible.
failed
Start with the trace you already have
Make the next failure explainable.
Instrument a workflow. Inspect the causal graph. Replay the branch that matters.
Start using 404 AI