Why it matters

Complex tasks benefit from explicit planning. Understanding shapes reliable agent design.

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The architecture

Planner LlmAgent: prompted to produce structured plan (JSON list of subtasks).

Executor: SequentialAgent runs subtasks; each may be another LlmAgent with narrow scope.

Planning patternPlanner LlmAgentproduces planSequentialAgentexecutes subtasksOptional replanon failureStructured plan output enables validation before execution
Planning flow.
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How it works end to end

Structured output: use Pydantic-style schema. Validate before execution.

Replanning: on subtask failure, invoke planner again with context.

Cost: extra LLM calls for planning; worth it for complex tasks.