The distance between a Figma file and a live product used to be an engineering team. With an AI-native workflow it's now a stack choice and a few weeks of disciplined work. Here's the practical path I recommend to designers — the same one behind my own shipped products.
Pick a boring, managed stack
- Hosting: Vercel. Push to deploy, automatic preview links, analytics built in. Zero server management.
- Database: Supabase or Neon. Supabase if you want auth, PostgreSQL and file storage in one product — ideal for a first app. Neon if you just need serverless PostgreSQL under a framework like Next.js.
- AI workloads: RunPod (or a hosted API). Only rent GPUs when your product genuinely needs its own inference; start with API calls.
- Code: Claude + Cursor + Codex. Claude for architecture and features, Cursor for in-editor speed, Codex for parallel scoped tasks.
The process that keeps you out of trouble
- Design the system, not screens. Tokens, components, states — your future codebase mirrors it.
- Write the data model down before any code. Tables, fields, relations. Have AI implement it, never invent it.
- Build vertical slices. One complete flow (sign up → do the core thing → see result) before any secondary feature.
- Deploy from day one. A URL that updates daily beats a demo that's "almost ready" for a month.
- Instrument everything. Funnel events from the first deploy — sign_up, activation, purchase. You're a designer; the funnel is your canvas.
The traps that kill designer-built products
- Over-scoping — shipping five mediocre features instead of one excellent flow.
- Improvised schemas — letting AI freestyle the database, then paying for it in every later feature.
- No SEO from day one — metadata, sitemap, structured data and an llms.txt cost an afternoon and compound forever.
- Skipping review — merging AI code you didn't read. You don't have to write it; you do have to understand it.
Start smaller than you think
My second product, Yaptım mı? — an ADHD-friendly task tracker on the App Store — is deliberately tiny: one question, "did I do it?", done extremely well. A small product you actually ship teaches you more than an ambitious one you abandon. Then apply the lessons to the bigger swing, like ChartPilot.
FAQ
What stack should a designer use for their first product?
Next.js on Vercel with Supabase (auth + PostgreSQL + storage), built with Claude and Cursor. It's managed end-to-end, cheap at small scale, and every piece has excellent documentation for AI tools to work with.
Supabase or Neon — which one?
Supabase when you want a batteries-included backend (auth, database, storage, realtime). Neon when you only need serverless PostgreSQL and are handling auth in your framework. For a first product, Supabase usually wins.
Do I need a backend developer?
Not for an MVP on a managed stack. You need discipline: a deliberate data model, small deploy loops and code review. For heavy infrastructure, compliance or scale, bring in specialists later.
