Agent memory and context

PlutoAI keeps context about your project so the agent does not start from scratch each time you return. This is what keeps changes consistent as your app grows.

What the agent remembers

• The plan and goals for your project, so new work fits what you already built.
• Key decisions made along the way, so it does not undo them by accident.
• Your own rules and preferences, when you have set them, so it builds the way you want.
• What it learned from earlier changes in the project.

Because of this, you can come back to a project after a break, describe the next change, and the agent picks up where you left off instead of asking you to re-explain everything.

Why it matters

Consistency is the payoff. When the agent carries the plan and past decisions forward, a change you ask for in week three still matches the choices you made in week one: the same layout conventions, the same data shape, the same naming. You get an app that grows as one coherent project rather than a pile of unrelated edits.

Specialized know-how

The agent also has libraries of task-specific know-how. It pulls one in only when a task actually calls for it, rather than carrying everything at once. You do not have to manage this. It happens as part of doing the work.

Keeping context useful

You get the most consistent results when your requests are specific and you change one thing at a time. Clear, focused requests give the agent a clear record to build on. A few habits help:

• State any standing preferences early, for example "always use the existing color palette."
• Name decisions you want kept, so a later change does not quietly reverse them.
• Keep each request focused, so the record of what changed stays clean.

See Prompting effectively.

Next steps