Project Kickstart Kit · AI Code that Works

3h (edited) • Tools, Templates & Workflows

Project Kickstart Kit

One question seems to come up over and over: "What's your workflow?" I also see people posting questions like, "How do you keep AI from going off the rails?", "Where do you even start?", "How do you organize a project before you start coding?", and "How do you avoid rewriting everything halfway through?" After a lot of experimenting, I finally settled on a workflow that's been producing consistently good results, so I figured I'd share it in case it helps someone else.

My workflow is basically: Idea → MVP PRD → AI architecture review → implementation plan → architecture → technical decisions → code.

I use my Project Kickstart Kit to drive that process. The biggest difference is I don't jump straight into coding anymore. I spend the time getting the project foundation right first, and the AI becomes much more effective because it has a clear roadmap instead of trying to figure everything out as it goes. I've ended up with better architecture, fewer rewrites, and much more consistent results.

TL;DR

💡 Idea → Brain dump the concept and define what problem I'm trying to solve.

📋 MVP PRD → Fully flesh out the product requirements, features, users, goals, and scope until I have a complete blueprint of what I'm building.

🏗️ AI Architecture Review → Have AI act like a senior software architect to challenge assumptions, identify missing requirements, simplify complexity, point out risks, and recommend improvements before any code is written.

🗺️ Implementation Plan → Break the project into logical milestones and small, achievable tasks that can be tackled one step at a time.

🏛️ Architecture → Design how the application will be structured, including folders, database, APIs, authentication, integrations, and how everything fits together.

🧠 Technical Decisions → Document why important architectural choices were made, what alternatives were considered, and the tradeoffs involved so future me (and AI) understands the reasoning.

💻 Implementation → Only after the foundation is in place do I start writing production code. At that point, the AI already understands the product, the roadmap, the architecture, and the reasoning behind it, so coding sessions are much faster and far more consistent.

I've found this "plan first, code second" approach dramatically reduces rewrites, keeps AI from wandering off course, and makes even fairly large projects much easier to manage.

What's the project you're building right now? I'd genuinely like to hear about it.

Comment below with a quick description of your project and a request for my Project Kickstart Kit and I'll send it over to you for free. It's the same documentation-first workflow I use to go from a completed idea to an implementation-ready project before writing production code.

1 comment

Project Kickstart Kit