Graph-Based Workflows
Build scalable multi-agent systems with directed acyclic graphs
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0 / 5 completedDAG Fundamentals
Directed Acyclic Graphs (DAGs) ensure workflows have no cycles, guaranteeing termination. The topology determines which tasks can run in parallel and which must wait for dependencies to complete.
Interactive: DAG Execution Simulator
Watch how a DAG executes step-by-step. Notice how B and C run in parallel after A completes.
Fetch Data
A
Process
B
Analyze
C
Combine
D
Report
E
Complete
Running
Pending
Blocked
DAG Properties
Directed
Edges have direction (A → B, not B → A)
Acyclic
No loops - cannot return to a previous node
Topological Order
Linear ordering respecting all dependencies
Execution Patterns
→
Sequential
Tasks execute one after another
→
Parallel
Independent tasks run simultaneously
→
Join
Multiple inputs combine into one task
💡 Key Insight
DAGs automatically expose parallelism. You don't need to manually identify which tasks can run concurrently - the graph topology reveals it. Tasks with no shared dependencies can execute simultaneously, dramatically improving throughput without additional complexity.