Definition
An execution graph is a run-oriented graph of executable steps and the control or data dependencies between them. Some nodes may be known when the run begins; others may be created when an orchestrator decomposes work, spawns agents, or discovers new requirements.
The graph should make scheduling facts explicit: who owns each node, what inputs it needs, which work may run concurrently, where results join, how many retries are allowed, and which failures block downstream work. Persisting those facts lets a long-running process resume without reconstructing its state from chat history.
Execution graphs are especially useful when many tasks proceed in parallel. They do not eliminate coordination costs. Shared resources, duplicate work, incompatible assumptions, and weak join criteria can still make a large graph slower or less reliable than a small loop.
Distinguish it from nearby terms
A control graph describes allowed routing. An execution graph represents work instantiated for a run. An execution trace records the events and outcomes that occurred. The trace is evidence of one traversal, not the complete set of possible paths.
Check your understanding
Three agents produce reports that all depend on the same dataset, but the graph records no dataset version and no join rule. The tasks can finish individually while the combined result remains inconsistent.