Snowtree is Databend Labs' review-driven workflow for keeping AI coding sessions safe, auditable, and merge-ready.

AI generates code. You must review. You can't review everything or roll back safely.
Snowtree fixes this with worktree isolation, incremental review, and staging snapshots.

Snowtree Demo

• Worktree isolation – every AI session runs in its own Git worktree, so you can spike multiple ideas in parallel with zero merge headaches.
• Incremental review loop – review, stage, and lock in vetted changes after each AI round; subsequent rounds only diff against staged code.
• Native CLI agents – run Claude Code, Codex, Gemini CLI, or Kimi Code CLI directly without wrappers, meaning no extra queues or limits.
• Stage-as-snapshot – staged files become the canonical baseline. When you're ready, merge them back and ship the PR.

• AI agent writes code – edits live in the isolated worktree while you review.
• AI agent commits – generates messages and commits the staged snapshot.
• AI agent syncs PRs – opens or refreshes pull requests on demand.
• AI agent updates from main – rebases/merges the latest upstream changes.
• AI agent resolves conflicts – fixes merge conflicts without touching staged files.

Install at least one AI coding agent:

One-line installer (macOS/Linux):

curl -fsSL https://raw.githubusercontent.com/databendlabs/snowtree/main/install.sh | sh

Manual download: GitHub Releases

make install # Install dependencies
make run # Start development server
make check # Typecheck, lint, and test
make build # Build packages

Snowtree: Databend's Best Practices for AI-Native Development

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