vs. Git Flow
Same precision, fewer branches and rules.
No develop branch, no release branches.
A Git workflow that keeps teams moving.
Lightweight yet precise and clean. Few rules, low overhead, a repository that stays readable over years — with controlled releases, hotfixes, and auditable history built in.
$
git log main reads like a project diary.
main is a clean, near-linear changelog of shipped changes. update/* branches sprout and squash-merge back as one commit each.
testing, staging, and production are pointers into main's history.
A hotfix/* squash-merges into production and is back-merged into main.
Standard change.
branch from main → commit freely →
PR → squash-merge → promote.
Hotfix.
branch from production → PR →
squash-merge into production → back-merge into main.
That's the whole model.
Same precision, fewer branches and rules.
No develop branch, no release branches.
Same lightness, plus a defined release model.
Stages, hotfixes, versions, and changelogs all built in.
Same trunk-centric philosophy.
With explicit staged deployment, hotfixes, and feature flags.
Git Momentum expects to be tailored. A team defines:
Capture these decisions in a document that lives with the repository.
See this project's own
PROJECT.md
for one example.
Three commands:
$ git checkout <stage> $ git merge --ff-only <commit-or-main> $ git push
The push triggers the deployment pipeline. --ff-only
ensures you can't accidentally push a non-fast-forward. If the
stage has an approval gate, the pipeline pauses for approval
before deploying.
Only if your Git platform supports fast-forward-only merges in PRs. Most don't — their default "merge" creates a merge commit, which would break the fast-forward rule on deployment branches. Use the Git CLI above instead.
No. Rebasing is never required in Git Momentum — not here, not
anywhere. Merge main into your branch whenever you
want to stay current; the squash on merge discards your branch's
internal history anyway.
Codify your convention so an AI coding agent enforces it on
every commit. An AI skill — for example a Cursor skill —
captures the rules in a form the agent reads and follows. See
this project's own
commit skill
for one example.
Pick a tag pattern, define the bump rules, and let an AI
coding agent apply them consistently. An AI skill — for
example a Cursor skill — captures the rules in a form the
agent reads and follows on every release. See this project's
own
version skill
for one example.
No — provided your team understands how Git and Git histories work. That's a baseline they should have anyway. Git Momentum is just a handful of conventions on top.