AI pair programming is a development workflow in which a person and an AI system work on the same coding task through short feedback loops. The human sets intent, evaluates tradeoffs, and accepts changes; the AI suggests code, explains options, runs checks, and helps revise the implementation.
It can operate at several levels:
- Completion: The AI predicts a line or small block while you type.
- Conversation: You ask for an explanation, design option, or focused edit.
- Agentic work: The AI plans and changes several files, then runs tests.
- Review: The AI examines a diff for bugs, missing cases, or unclear code.
Pair programming differs from unattended automation because the human stays inside the decision loop. A useful rhythm is: state the goal, ask for a small plan, approve one step, inspect the diff, run checks, and discuss anything surprising. The AI provides speed and recall; the developer provides product knowledge, architecture judgment, and accountability.
Choose the level that matches the task. Completion may be enough for familiar boilerplate, while a multi-file feature benefits from a plan and explicit checkpoints. Treat the AI's output as a proposal, not authority. The strongest pair is one where the developer can explain the final code and the agent makes that understanding faster rather than optional.
Related reading: How to write requirements for an AI coding agent and How to validate AI-generated code.
