Workflow

A month ago I wrote about making Claude Code actually ship software. The workflow has been through at least six revisions since I started, but this latest version has been stable. Now it’s packaged as momentum. What This Actually Is Not another “make AI smarter” attempt. This is a workflow that assumes you know what you’re doing and gives you tools to do it faster. A recent post about building Log Carver at C-speed nailed it: “AI is no longer just a productivity booster. It’s a compiler for ideas. But like any compiler, it needs constraints, tests, and a damn good operator behind the keyboard.” ...

TL;DR Claude Code is powerful, like really.. but chaotic without some structure. Many people probably use it an ad-hoc fashion and there’s nothing wrong with that. I built a systematic workflow that turns it into a shipping machine. The magic is in the command structure. /plan-iteration → /plan-task → implement → /complete-task → /complete-iteration. Each command has specific responsibilities and quality gates. Evidence-based completion prevents the “is it done?” problem. /complete-iteration requires concrete proof that users can access working software. No more marking things “complete” when they’re just coded. ...

TL;DR I had a critical gap in my Claude Code workflow. Everything was optimized except the moment Claude actually writes code. Even with auto-accept enabled, I was gambling that /complete-task would catch violations after many changes. Hooks let you inject real-time quality checks. When Claude Code hooks became available, I could finally add guardrails that run outside Claude’s context but feed results back through JSON decision control to block bad edits. ...