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Plan-and-Solve

🔄 The Agentic Control Loop⏱ 8 min⭐ 60 BASE XP

Hierarchical Planning

While ReAct is great for short tasks, it fails on long horizons because the agent loses track of the overarching goal. Enter Plan-and-Solve.

  1. Planner Agent: Takes the user request and outputs a step-by-step checklist.
  2. Execution Agent(s): Executes the steps sequentially.
  3. Monitoring: Updating the checklist as steps finish.
<plan>
[x] 1. Search for specific python version
[ ] 2. Download installer
[ ] 3. Run installation script
</plan>
SYNAPSE VERIFICATION
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Why is the Plan-and-Solve architecture better than basic ReAct for complex goals?
It uses less tokens overall
It maintains an overarching checklist, preventing the agent from getting lost on long horizons
It allows the agent to bypass API rate limits
It executes tools twice as fast
Watch: 139x Rust Speedup
Plan-and-Solve | The Agentic Control Loop — AI Agents Academy