State Machines for Agents
Build reliable, predictable agent behavior with finite state machines
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0 / 5 completedStates & Transitions
States represent distinct modes of operation, while transitions define how an agent moves between states in response to events. Together, they form the structure of agent behavior.
Interactive: State Diagram Builder
Click a state to select it, then click "Add Transition" and click another state to create a transition. Add new states or reset the diagram.
Start
Processing
Done
INSTRUCTIONS:
- • Click any state to select it (highlighted in bright emerald)
- • Click "Add Transition" then click a different state to create a transition
- • Add new states with custom names
- • States: 3 | Transitions: 2
Designing States
Mutually Exclusive
Agent can only be in one state at a time
Complete Coverage
Every possible situation should map to a state
Meaningful Names
State names should describe what the agent is doing
Transition Rules
→
Event-Triggered
Transitions happen in response to specific events
→
Atomic
Transition happens instantly, no in-between states
→
Deterministic
Same event in same state always produces same result
Common State Patterns
Linear Flow
Simple progression: Start → Processing → Done
Use for: Sequential workflows, pipelines
Branching
Multiple paths: Start → [Success | Error] → Done
Use for: Error handling, conditional flows
Loops
Repeating cycles: Idle → Working → Idle (repeat)
Use for: Retry logic, polling, continuous processes
Hierarchical
Nested states with sub-states (state within state)
Use for: Complex agents, modal behaviors
💡 Key Insight
Good state design is about balance. Too few states and behavior becomes hard to reason about (giant switch statements). Too many states and the diagram becomes overwhelming. Aim for states that represent meaningful, distinct modes of operation. If you're adding states that are only subtly different, consider using state variables (context) instead.