Issue-to-Pull-Request AI Engineering Agent

Problem Context

Software engineering teams face growing backlogs of issues — bugs, feature requests, and technical debt. An AI agent that can understand an issue, explore the codebase, form a hypothesis, implement a fix, run tests and generate a pull request — while remaining reviewable by a human — dramatically accelerates delivery.

Challenge Requirement

Build an AI agent that takes a GitHub issue, explores the relevant codebase, forms a technical hypothesis, implements code modifications, executes tests, analyses failures, iterates, and produces a patch or pull request ready for human review before deployment.

Mandatory Capabilities (8)

Illustrative Scenario

Issue #247 reports a duplicate-order bug triggered by a retry mechanism. The agent explores the order service, identifies the missing idempotency key, implements the fix, runs the test suite (3 failures → 2 iterations → all passing), and opens a PR with a structured description referencing the issue, the root cause, the fix and the test results.