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Workflow Design Patterns

State Machines for Agents

Build reliable, predictable agent behavior with finite state machines

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What Are State Machines?

A state machine is a mathematical model that describes behavior as a set of discrete states and the transitions between them. For agents, state machines provide a structured way to model complex workflows with predictable, verifiable behavior.

Why State Machines for Agents?

🎯

Predictable

Behavior is deterministic and testable

🔍

Debuggable

Easy to trace exactly what happened

📊

Visualizable

States and transitions form clear diagrams

Interactive: Simple State Machine

Click the buttons to trigger state transitions. Watch how the agent moves through defined states.

IDLE
CURRENT STATE:
The agent is in idle state. In a real system, each state would have associated behaviors and valid transitions.

Core Components

States
Distinct modes agent can be in (idle, processing, complete)
Transitions
Rules for moving between states (triggered by events)
Events
Triggers that cause transitions (start, complete, error)

Key Benefits

→
Explicit Behavior
All possible states and transitions are documented
→
Error Prevention
Invalid transitions can be prevented at design time
→
Testing & Verification
Easy to verify all paths and edge cases

💡 Key Insight

State machines make implicit behavior explicit. Instead of scattered if-statements and flags throughout your code, state machines centralize all behavior rules in one place. This makes it dramatically easier to understand, test, and modify agent behavior. If you can draw it as a diagram, you can implement it as a state machine.