From CLI tool to AI workspace extension: building Workspai on top of RapidKit

I've been working on RapidKit for two years — an open-source toolkit that scaffolds backend workspaces for FastAPI, NestJS, and Go.

It generated real project structure, installed modules, and maintained a manifest of what was already in the project. Developers liked the structure, but I kept hearing the same feedback: after scaffolding, they still had to explain their project to AI tools from scratch every time.

That was the insight behind Workspai.

AI coding tools are usually file-aware, not workspace-aware. They see the file you're editing, but not the broader project layout, installed modules, recent changes, or team conventions. For backend systems, that makes AI much less useful than it should be.

So I built Workspai as the AI layer on top of RapidKit. It's a VS Code extension that reads the workspace before every AI prompt — framework, layout, installed modules, entry files, git changes, and workspace memory — so the AI can answer with real project context instead of generic guesses.

The biggest lesson so far has been positioning. RapidKit and Workspai are closely related, but they solve different problems. RapidKit is the execution and trust layer. Workspai is the intelligence layer on top.