Built for AI code editors
Every platform deploys in minutes — to your GitHub, your Vercel, your Neon database. Then hand it to Claude Code, Cursor, Windsurf, or any AI editor and build on top of a platform that's already live. Extend by prompt or by API. Ship from your local machine to production in a single push.
These are standard Next.js + TypeScript codebases with AI context baked in — so whatever editor you reach for already understands them.
Every platform ships with a CLAUDE.md and a planning/ reference tree, so Claude Code knows the schema, patterns and gotchas before it writes a line.
Open the repo in Cursor and the included rules + docs give the model full project context for fast, on-pattern edits.
Agentic flows work out of the box — point Windsurf at the codebase and let it plan, edit and verify across files.
Standard Next.js + TypeScript means Copilot and the VS Code ecosystem feel right at home, no special setup.
Several platforms expose a Model Context Protocol server, so you can drive them from any MCP-capable assistant.
The bundled prompt library and documented patterns transfer to any capable model — you are never locked to one tool.
The hard part of letting AI work on a codebase is context. We hand it to you — extensive docs, files and markdown instructions in every platform.
A project brief written for AI editors: the rules, the do/don't list, the checkpoint routine and the map of where everything lives.
A planning/reference tree covering architecture, schema maps, API patterns, UI patterns, query patterns and a living gotchas file.
A built-in /docs section — quick-start, API reference and tech guides — that ships and deploys with the platform.
A fully-typed Drizzle/PostgreSQL schema with migration scripts, so the data model is explicit and safe to evolve.
Clean Route Handlers (GET/POST/PUT/DELETE) with consistent conventions, ready to call from anything that speaks HTTP.
Every integration key is documented with example env files, so connecting services is fill-in-the-blank, not guesswork.
Local to repo to Vercel — the same path a professional team uses, driven by a sentence.
01 · Step
The moment you buy, you connect GitHub, Vercel, and Neon — one click each — and press Deploy. Your platform is live before you open your AI editor. Clone the repo, and your AI editor reads the bundled docs for instant context.
02 · Step
Ask in plain English — 'add a CSV export', 'wire up Stripe', 'add a new dashboard tab'. The model edits real files against a known schema and patterns.
03 · Step
It's your code in your GitHub. Commit, branch, review and collaborate exactly like any other professional codebase.
04 · Step
Your Vercel deployment was created the moment you pressed Deploy. Every subsequent push ships to production automatically — preview builds for branches, production on main.
Talk to your editor in plain English, or call the platform's own REST API from anywhere. Two doors into the same well-structured code.
By prompt
Open the repo in your AI editor and describe the change. It reads the bundled docs, edits the right files, and follows the existing patterns.
> Add a CSV export button to the leads table and a /api/leads/export route. > Wire up Stripe checkout on the pricing page using STRIPE_SECRET_KEY. > Add a "status" filter to the admin dashboard and persist it in the URL.
By API
Every platform exposes documented REST endpoints. Create, read, update and delete records from your own scripts, tools or other apps.
curl -X POST \
https://your-platform.vercel.app/api/records \
-H "Content-Type: application/json" \
-d '{
"title": "New record",
"status": "published"
}'Our platforms already speak to the services modern software runs on — and because you own the code, you can add any other API you need.
…and any other service with an API. It's your codebase — extend it however you like.
Buy a production-ready platform and make it yours with the AI tools you already use — no agency, no lock-in, no waiting.
100%
Code ownership
Prompt
or API — your choice
Local → Vercel
Ship in one push