State Management

In a multi-agent system, state is the shared truth about what's happened, what's in progress, and what's been decided. Without state management, agents work with stale or conflicting information — and the user pays the cost in repeated questions, contradictory answers, and lost progress.

State management is the plumbing skill of multi-agent design. Get it wrong and every other skill in this plugin gets harder.

Types of state

• Task state: where the overall task is in its lifecycle. Which subtasks are complete, in progress, or pending.
• Context state: what each agent knows. What has been shared, summarised, or dropped.
• User state: preferences, history, and current emotional state.
• Decision state: decisions made, options considered, options rejected (and why).
• Error state: what has failed, been retried, been escalated.

State architecture patterns

• Centralised state: one shared store all agents read from and write to. Simple, debuggable. Bottleneck risk at scale.
• Distributed state: each agent maintains its own state and syncs with others. Flexible. Consistency risk.
• Event-sourced state: state is built from a log of events. Every change is recorded. Auditable. Complex.
• Blackboard pattern: shared workspace where agents post results and read others' contributions. Good for collaborative problem-solving.