1 min lesson
Agent loops and applying edits
Explain the practical point behind "Reviewing PRs of AI-generated code, coordinating multi-file edits."
Step 1 of 3
A completion suggests. An agent acts. The jump from autocomplete to an agent that reads files, runs tools and rewrites five files in one turn is where most of the hard product decisions live.
Cursor builds the surfaces for AI-native workflows - reviewing PRs of AI-generated code, coordinating multi-file edits - so an interviewer will want you to reason about the loop itself, not just the model behind it. The loop is a control system wrapped around a probabilistic core.
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Full explanation
One Pass Through the Agent Loop
Interactive diagram. Step through it with the Next and Previous controls below, or Tab to a region to read its detail.
Verify is the gate that turns a probabilistic core into a system people trust.
The difference between a demo agent and one people trust is whether it reads the result of its own actions. An agent that proposes an edit and moves on is guessing. One that applies the edit, runs the type-check, sees the error and fixes it is closing the loop - and that loop is what makes a probabilistic system behave reliably.