I Replaced My Entire Dev Workflow With 4 AI Agents — Here's the Architecture

Most AI workflows are just prompt chains held together with hope. You paste something into ChatGPT, copy the output, paste it somewhere else, tweak it, run it again. Nothing connects. Nothing finishes reliably. Every step requires you. I got tired of that. So I built a system where 4 AI agents do real work — and deterministic software controls all of them. This is the architecture. The Problem With "Just Use AI" When people say "use AI to build faster," they usually mean: type prompts until something works. That breaks down fast: No coordination. Each AI session is isolated. Agent A doesn't know what Agent B produced. No validation. The output might be wrong but nothing catches it. No state. You're the memory. You track what's done, what's next, what failed. No control. The AI decides what to do. You react. The missing piece isn't a better model. It's a control layer — software that governs what each agent does, in what order, with what constraints. That control layer is called an AI o