Plan Mode

Use different models for planning and execution.

Dual model lets you choose one AI model for planning and another for execution. This means you can use a smarter, more expensive model to plan the steps, but save money by using a cheaper model to carry out the tasks. Each model gets to do what it does best.

Advantages:

• Save money by not using an expensive model for every step
• Take advantage of different strengths—some models are better at planning, others at doing

Let agents ask clarifying questions.

When writing out a task, it’s easy to overlook details or leave out important information. As humans, we make mistakes and have blind spots. Agents that ask clarifying questions can help identify these gaps in your instructions, making sure nothing critical is missed.

Edit plans directly without running the model.

Make precise, targeted edits directly in the plan instead of running the model.

Sometimes we need to make changes to the plan. We could ask the model, “please, fix the plan: [proposed changes].” However, it’s often easier and more efficient to edit the plan directly rather than try to get the model to interpret your intended changes.

Delegate complex tasks to specialized agents.

Plan Mode on steroids. The agent delegates each task to specialized agents, which allows it to achieve:

1. Each agent has only the required context. Previous unrelated history doesn’t affect your task. For example, if you run tests in a cycle and have a lot of useless logs in the history, a new agent for the next edit task doesn’t see the test logs because they are not needed for editing.
2. You can run agents in parallel if needed, because the orchestrator controls their execution area. For example: parallel fetching of information from the web.

Track progress with auto-generated task lists.

You have to generate todo-list before plan execution to move the progress tracking from the model to your agent. It is useful for complex features because a model has no chance to skip any required step in the plan.

How it works:

When you build a plan and click execute. The agent creates a numbered list of subtasks that need to be completed. Each todo item represents a specific action or milestone in the implementation. As the agent executes the plan, it marks items as complete, giving you real-time visibility into progress.

Why it matters:

• Agent forces a model to follow the plan step by step;
• Agent can run some steps by himself without calling the model. For example: tests. If they are green, the agent don’t need to include the result into the context;
• Clear visibility into what’s been completed;
• Easier to review and approve before execution;
• Agent can create checkpoints between steps for easy rollback if needed. You don’t need rollback all the work if some step was finished incorrectly.