Git Workflow And Versioning

Git Workflow and Versioning

Overview

Git is your safety net. Treat commits as save points, branches as sandboxes, and history as documentation. With AI agents generating code at high speed, disciplined version control is the mechanism that keeps changes manageable, reviewable, and reversible.

When to Use

Always. Every code change flows through git.

Core Principles

Trunk-Based Development (Recommended)

Keep main always deployable. Work in short-lived feature branches that merge back within 1-3 days. Long-lived development branches are hidden costs — they diverge, create merge conflicts, and delay integration. DORA research consistently shows trunk-based development correlates with high-performing engineering teams.

main ──●──●──●──●──●──●──●──●──●──  (always deployable)
        ╲      ╱  ╲    ╱
         ●──●─╱    ●──╱    ← short-lived feature branches (1-3 days)

This is the recommended default. Teams using gitflow or long-lived branches can adapt the principles (atomic commits, small changes, descriptive messages) to their branching model — the commit discipline matters more than the specific branching strategy.

• Dev branches are costs. Every day a branch lives, it accumulates merge risk.
• Release branches are acceptable. When you need to stabilize a release while main moves forward.
• Feature flags > long branches. Prefer deploying incomplete work behind flags rather than keeping it on a branch for weeks.

1. Commit Early, Commit Often

Each successful increment gets its own commit. Don't accumulate large uncommitted changes.

Work pattern:
  Implement slice → Test → Verify → Commit → Next slice

Not this:
  Implement everything → Hope it works → Giant commit

Commits are save points. If the next change breaks something, you can revert to the last known-good state instantly.

2. Atomic Commits

Each commit does one logical thing:

# Good: Each commit is self-contained
git log --oneline
a1b2c3d Add task creation endpoint with validation
d4e5f6g Add task creation form component
h7i8j9k Connect form to API and add loading state
m1n2o3p Add task creation tests (unit + integration)

# Bad: Everything mixed together
git log --oneline
x1y2z3a Add task feature, fix sidebar, update deps, refactor utils

3. Descriptive Messages

Commit messages explain the why, not just the what:

# Good: Explains intent
feat: add email validation to registration endpoint

Prevents invalid email formats from reaching the database.
Uses Zod schema validation at the route handler level,
consistent with existing validation patterns in auth.ts.

# Bad: Describes what's obvious from the diff
update auth.ts

Format:

<type>: <short description>

<optional body explaining why, not what>

Types:

• feat — New feature
• fix — Bug fix
• refactor — Code change that neither fixes a bug nor adds a feature
• test — Adding or updating tests
• docs — Documentation only
• chore — Tooling, dependencies, config

4. Keep Concerns Separate

Don't combine formatting changes with behavior changes. Don't combine refactors with features. Each type of change should be a separate commit — and ideally a separate PR:

# Good: Separate concerns
git commit -m "refactor: extract validation logic to shared utility"
git commit -m "feat: add phone number validation to registration"

# Bad: Mixed concerns
git commit -m "refactor validation and add phone number field"

Separate refactoring from feature work. A refactoring change and a feature change are two different changes — submit them separately. This makes each change easier to review, revert, and understand in history. Small cleanups (renaming a variable) can be included in a feature commit at reviewer discretion.

5. Size Your Changes

Target ~100 lines per commit/PR. Changes over ~1000 lines should be split. See the splitting strategies in code-review-and-quality for how to break down large changes.

~100 lines  → Easy to review, easy to revert
~300 lines  → Acceptable for a single logical change
~1000 lines → Split into smaller changes

Branching Strategy

Feature Branches

main (always deployable)
  │
  ├── feature/task-creation    ← One feature per branch
  ├── feature/user-settings    ← Parallel work
  └── fix/duplicate-tasks      ← Bug fixes

• Branch from main (or the team's default branch)
• Keep branches short-lived (merge within 1-3 days) — long-lived branches are hidden costs
• Delete branches after merge
• Prefer feature flags over long-lived branches for incomplete features

Branch Naming

feature/<short-description>   → feature/task-creation
fix/<short-description>       → fix/duplicate-tasks
chore/<short-description>     → chore/update-deps
refactor/<short-description>  → refactor/auth-module

Working with Worktrees

For parallel AI agent work, use git worktrees to run multiple branches simultaneously:

# Create a worktree for a feature branch
git worktree add ../project-feature-a feature/task-creation
git worktree add ../project-feature-b feature/user-settings

# Each worktree is a separate directory with its own branch
# Agents can work in parallel without interfering
ls ../
  project/              ← main branch
  project-feature-a/    ← task-creation branch
  project-feature-b/    ← user-settings branch

# When done, merge and clean up
git worktree remove ../project-feature-a

Benefits:

• Multiple agents can work on different features simultaneously
• No branch switching needed (each directory has its own branch)
• If one experiment fails, delete the worktree — nothing is lost
• Changes are isolated until explicitly merged

The Save Point Pattern

Agent starts work
    │
    ├── Makes a change
    │   ├── Test passes? → Commit → Continue
    │   └── Test fails? → Revert to last commit → Investigate
    │
    ├── Makes another change
    │   ├── Test passes? → Commit → Continue
    │   └── Test fails? → Revert to last commit → Investigate
    │
    └── Feature complete → All commits form a clean history

This pattern means you never lose more than one increment of work. If an agent goes off the rails, git reset --hard HEAD takes you back to the last successful state.