my-git

AI Native Development

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This directory discusses Git workflows in the age of AI programming: AI can generate code faster, and humans need to use Git to organize changes into reviewable, verifiable, and rollback-ready engineering units.

What to Read First

Problem you want to solve	Recommended Reading
Establishing a Git workflow for AI programming	AI Native Git Workflow
Don’t know how to review code after AI modifications	AI Change Review Practice Example
Systematically reviewing AI-generated code	How to Review AI-Generated Code
AI modified too many files at once	AI Commit Splitting
Large diffs need to be split into multiple PRs	Stacked PR for AI-Generated Changes
Parallel development with multiple agents	Multi-Agent Branch Strategy

Tool Practices

• Codex / Claude Code Git Practices
• Git Integration Practices for AI Coding Tools
• Worktree for AI Agents
• AI Reviewer and Human Reviewer

Tools change, but underlying principles remain stable: isolate tasks, review diffs, split commits, retain validation, and let humans be responsible for the final merge.

Recommended Combinations

Scenario	Recommended Combination
Single small fix	AI Workflow + AI Review
Large feature	AI Workflow + Commit Splitting + Stacked PR
Multi-agent parallel work	Worktree + Multi-Agent Branch Strategy
Team adoption of AI Review	AI Generated Code Review + AI Reviewer and Human Reviewer

Related Content

• Team Collaboration
• GitHub Engineering Governance
• AI Code Review Checklist

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