Every major advance in software development has changed how teams express intent. Waterfall relied on heavy documents because course changes were slow. Agile reduced the paperwork because iteration was cheap and teams learned through motion.

Agents require their own planning style. Instead of a gated process that freezes intent too early, they reward a planning approach that provides upfront direction while staying alive and grounded in real work.

#What agents need to be effective

Agents stay on track when they can expand the problem into clear language. They ask questions, remove assumptions, and outline the path before touching code. Their training reinforces that behavior.

When the plan is explicit and adaptable, they can take on longer stretches of work without drifting. This is why planning for agents benefits from an iterative surface rather than a fixed spec. The plan becomes part of the loop.

As the agent discovers constraints, it updates the plan. As the user refines intent, the plan shifts again. This rhythm fits the grain of agentic development much better than discrete planning stages inherited from earlier eras.

#How Cursor designs planning for agent intelligence

We built Plan Mode based on our understanding of how software development teams get the most done with agents. It's a powerful, general-purpose planning approach designed specifically for agentic development.

Plan Mode gives agents a place to ask questions, scan the codebase, propose a path, and refine it with the user. It can stay lightweight for quick tasks, or become a longer-lived, canonical artifact. The process follows five steps:

1. Clarifying questions. The agent asks questions that remove ambiguity. Agile teams handle this through quick back-and-forth. Spec-driven development (SDD) moves it into a formal requirements step. Plan Mode takes the same goal of reducing ambiguity but lets the agent drive the questioning directly, which better fits the pace of agentic work.

2. Research. The agent scans the codebase to identify the places it will need to interact with. Older workflows treated this as a separate design phase. Plan Mode folds it directly into the agent's reasoning.

3. Drafting the plan. The agent writes an editable plan file that explains the changes and the steps to implement them. SDD freezes this as a fixed spec. Agile often lets docs drift. Plan Mode keeps the plan alive so you and the agent can refine it as new information appears.

4. Executing the work. The agent works step by step and checks off tasks as it goes. Traditional methods split planning and implementation. Plan Mode treats them as one process so the plan can adapt.

5. Revising the plan. When things go off track, the plan is also the reset point. Instead of patching behavior with follow-up prompts, teams can revert the work, refine the plan, and run it again. This keeps intent explicit and produces cleaner results than steering an agent mid-execution.

Plans save to your workspace as version-controlled files in .cursor/plans/. They sit alongside your code, tracked in git like any other project artifact. You can see what changed, when, and roll back if needed.

#Flexible planning primitives

Teams organize intent in different ways. Some rely on formal requirements. Others use evolving designs or phased workflows. A planning framework should be flexible to accommodate how teams prefer to work.

That matters even more now because the ground is shifting rapidly. Waterfall defined planning for decades. Agile shaped teams for another two. Agent intelligence is advancing on a much shorter timeframe. Any fixed process will age quickly.

This is why we built our approach around simple primitives that you can shape as you want. You can use Agent Skills to define the planning structure your team prefers, and the agent will follow that structure consistently.

Some teams encode a more formal, spec-driven workflow as an agent skill. Others define skills that create lighter-weight plans that evolve as the work advances. Because plans are shaped by skills rather than a fixed process, both approaches fit naturally inside Plan Mode.

The point is not that our approach to planning is backward compatible, though it is. It's that it is forward-looking. A framework built on a small set of shared primitives gives teams room to evolve their methods as agents take on work that older planning styles never anticipated.

#Looking ahead

The size and complexity of work agents can handle is increasing quickly. Because we built Plan Mode on simple primitives with agents in mind, it's able to keep pace with these advances.

We are testing agents that stay with a project for extended runs, keep context across sessions, and create subagents when a task benefits from parallel work. Multiple developers will soon be able to join the same session, see how the plan evolves, and guide the agent as the project unfolds. Our aim is to widen the scope of what agents can complete while preserving the same core elements software teams have always wanted from planning: clarity, visibility, and user control.