Show HN: I build a tool to encourage before reviewing code, review intents
Mainline is a new tool designed to enhance code review processes by focusing on reviewing the intent behind code changes. It provides a memory layer that captures important context and decisions made prior to code edits, which is crucial in a landscape where AI agents generate code quickly. By making intent reviewable before code review, Mainline aims to prevent issues that arise from misunderstanding the rationale behind changes.
- ▪Mainline records the intent behind engineering work, capturing user goals, decisions, and constraints.
- ▪The tool aims to address challenges posed by coding agents that produce large diffs quickly, making it hard to infer intent from the final code alone.
- ▪Mainline is not a replacement for Git or traditional code review systems, but rather a supplementary memory layer that travels with the code.
Opening excerpt (first ~120 words) tap to expand
Mainline Website: https://mainline.sh Hosted Hub: https://mainline.sh/hub/ Detailed reference: docs/reference.md 中文版本: README.zh.md We have code review. Now we need intent review. Mainline is a Git-native memory layer for coding agents. It gives agents and reviewers repo memory before the diff: prior decisions, constraints, abandoned approaches, validation notes, and related in-flight work. AI agents make code cheap to produce and harder to review. Mainline makes the intent reviewable before the generated code lands. Review the intent before you review the code. The Problem Code review was built for a world where humans wrote most of the code. The diff was expensive, so it was usually small enough for reviewers to infer the intent. Agent work changes that.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.