Plan & Execute
Plan & Execute is an AI agent UX pattern where the agent first breaks a complex goal into an explicit, ordered list of steps, then works through that plan sequentially while showing progress. Users can review, edit, or approve the plan before execution starts, which improves reliability and gives visibility into a multi-step task before any action runs.
When to use
Ideal for autonomous AI agents, complex task automation, and workflow tools where planning before execution improves success rates and user confidence.
When not to use
- Single-step requests where a plan adds a review step with nothing to actually review.
- Latency-sensitive interactions where users want an immediate answer, not a proposal to approve first.
- Highly exploratory tasks where the right steps only emerge as the agent learns from early results.
Anti-patterns
- Showing a plan once and then silently deviating from it during execution with no updated view.
- Plans so granular they bury the real decision points under dozens of trivial sub-steps.
- No way to edit or reject individual steps, only accept-all or cancel-all.
- Re-planning from scratch on every minor failure instead of adjusting the remaining steps.
How products use it
| Product | Implementation |
|---|---|
| AutoGPT | Generates a task list from a goal and executes items sequentially with visible state. |
| CrewAI | Assigns planned sub-tasks across role-based agents with a defined execution order. |
| LangChain (plan-and-execute agents) | Separates a planner step from an executor loop that carries out each planned action. |
| Cursor Agent | Drafts a todo-style plan for multi-file tasks before making edits. |
Use this pattern in your project
Copy this prompt to generate a production-ready implementation in Cursor, Claude Code, Lovable, or any AI coding agent.
Generate a production-ready implementation of the "Plan & Execute" AI interface design pattern.
Pattern Definition:Enter a task below to see the AI create a plan
Frequently asked questions
What is the Plan & Execute pattern in AI agents?
Plan & Execute means the agent first produces a visible, ordered breakdown of a goal into steps, then works through those steps one at a time, updating status as it goes. It separates "what will happen" from "doing it" so users can review intent before commitment.
Why show the plan instead of just running the task?
Showing the plan lets users catch a wrong approach before any side effects occur, and it gives a legible progress model during long-running tasks. It also makes failures easier to diagnose since users can see which step broke.
Should users be able to edit the plan before execution?
Yes, for anything consequential. Letting users reorder, remove, or edit individual steps before execution turns the plan into a real checkpoint rather than a formality, and reduces wasted runs on the wrong approach.
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