Three steps. Three approvals. No surprise commits.
A simple workflow that lets AI do the heavy lifting — and lets you stop it before it ships something you didn't agree to.
MIT License · Works with Claude Code, Cursor, or any AI assistant
A real exchange. The AI announces what it's about to do, and waits for you.
Add Google OAuth login to the app.
Before I write any code, here's what this will touch:
auth/google.ts, routes/oauth.tsoauth_provider column to userspassport-google-oauth20Does this scope look right?
The AI cannot move forward until you click. Same checkpoint repeats before planning, and again before any code reaches your repo.
Three people who keep asking the same question: how do I trust this?
You use AI every day. You're tired of it touching files you didn't ask about, or "improving" things mid-task. You want it to ask first.
Your team uses AI. You need a paper trail: what was decided, by whom, and why. Code review starts with knowing what should have been built.
You don't trust AI-generated code — and you shouldn't, by default. You want hard checkpoints where you can say stop before things get out of hand.
Three steps, each ending with a checkpoint you control.
The AI reads your code and confirms what the task actually is — in your terms, not its assumptions.
You see: A short description of the problem, which files are affected, and the agreed scope.
The AI proposes how to solve it — sometimes with a small prototype you can click through — before writing real code.
You see: A written plan, a prototype if relevant, and a record of any architectural decisions.
Only now does the AI write production code — following the plan you approved, nothing more.
You see: Working code, passing tests, a clean commit on your main branch.
The AI cannot cross any of these without your explicit approval.
Did we understand the task?
Before any planning starts.
Is the plan good?
Before any production code is written.
Does it actually work?
Before the change is considered done.
Everything else follows from these.
An AI without context invents things. The first step is always understanding.
Quickly generated code must be reviewed and understood before it ships.
Validate after each step. No silent leaps from idea to merged code.
The AI suggests. You approve. The responsibility never moves.
Browse the framework topic by topic
3 steps × 7 roles × 3 modes. The 6 decisions per step.
G1 / G2 / G3 evidence-based gates. Approval requires evidence.
Core principle — every step measurably reduces uncertainty.
Internal sceptic. Top-3 failures, ≥2 alternatives, counter-argument.
Gatekeepers, Architecture-Reviewer, Governance-Auditor.
Every decision is a click. Free-text questions are forbidden.
/context /explore /produce /gate-check /approve /promote …
create-adr, create-ctx-plan, create-exp-plan, sync-plan-issues.
Mode reminder, gate enforcement, provenance check.
16 ready-to-use templates — ADR, plans, problem statement…
10 cross-cutting rules — uncertainty, governance, knowledge routing …
Kanban, Scrum, SAFe, monorepos, Power Sessions.
Pick the path that matches you.
Two minutes. One file change.
CLAUDE.md (or create one).
@url https://chevp.github.io/chevp-ai-framework/chevp-ai-framework.md
That's it. No fork, no submodule, no install.
For a project where you'll keep plans, specs, and decisions versioned in git.
mkdir -p context/{architecture,adr,guidelines,plans/finished,specs}
The plugin is optional. The framework works either way.
The questions people actually ask.
Yes — on small tasks. A one-line fix doesn't need three checkpoints. You can skip the framework for those.
For real work, it's faster overall. The time you spend on a 30-second scope check at the start is time you don't spend rolling back a half-finished feature the AI invented in a direction you didn't want.
No. The framework is plain Markdown that any AI assistant can read — Claude Code, Cursor, Copilot, ChatGPT, whatever you use.
Claude Code gets a few extras (a plugin with slash commands and automatic enforcement), but the workflow itself is portable.
Reading code, explaining things, answering questions — all free. No checkpoints.
The framework only kicks in when the AI is about to create, edit, or delete a file. That's the line where things get serious.
Both, but the value shifts. Solo: you avoid losing an afternoon to a rabbit hole the AI happily dug for you. Teams: you get plans and decisions written down, so code review starts with shared context instead of guesswork.
Yes. The core is generic. You can layer a domain-specific framework on top with your own templates, conventions, and rules. See the repo for the extension pattern.
Fair question. The whole framework is three steps and three checkpoints — that's the entire surface. Everything else (templates, role definitions, the deeper docs) is optional structure for when you want it.
If a one-paragraph rule in your CLAUDE.md already does the job, use that. The framework is here when ad-hoc rules stop being enough.
Two minutes to try. One line to integrate.