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Agent coordination, tools, and state transitions are modeled as an explicit, executable state graph consisting of nodes and edges. Typical conditions for use: Coordination must be completely traceable and testable; Complex flows involving cycles and strict conditions must run stably in production. The central trade-off: Extreme predictability and controllabi…
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What organizes, connects, or makes decisions possible.
Graph-based orchestration runs workflows as a graph of nodes and edges: states, dependencies, and transitions are modelled explicitly and executed.
The approach grows out of workflow engines, state machines, and graph processing. Agentic systems extend this lineage to branching, stateful flows in which steps can be repeated or run in parallel.
Nodes represent work steps or agents, edges represent transitions and conditions, and shared state carries results through the flow. The graph makes control flow, resumption, and failure paths visible.
The conceptual focus and typical structure of the approach.
Use in the relevant working context.
Graph-based orchestration helps plan, monitor, and resume complex agent and data workflows in a traceable way.
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