Agent Pull Request

An Agent Pull Request (Agent PR) describes the end-to-end process in which an AI coding agent — such as Claude Code, OpenAI Codex, or similar systems — autonomously implements code changes and submits them as a pull request in a version control system like GitHub, without requiring a human developer to perform the submission step. Unlike traditional AI coding assistants that merely surface suggestions, an agentic system executing an Agent Pull Request owns the complete execution chain: analyzing the task, implementing the changes, running tests, resolving failures, and submitting the code for review. This process can be fully automated or operate within a human-in-the-loop model where a developer reviews the finished PR before merging. The Agent PR Protocol — a pattern popularized by coding agents like Claude Code — formalizes this workflow and represents one of the most concrete use cases of agent-driven software development. Common scenarios include automated bug fixing, small feature implementation, code refactoring to established standards, and test generation for existing codebases. Quality control for Agent Pull Requests typically involves diff-first review practices, automated CI/CD pipeline validation, and supplementary AI code security reviews. Larger engineering organizations embed Agent PRs into structured review loops to ensure consistency, traceability, and compliance with development standards. The Agent Pull Request concept marks a fundamental shift in how AI participates in software development — from passive assistant to active contributor — and is a cornerstone of modern agentic engineering workflows.