Choose Your AI Stack
- Frontend: Use an AI no-code release like Lovable or Bolt.new to generate UI components (React, Tailwind) and integrate basic flows (auth, data fetching) from prompts.
According to one comparison:
“Lovable … full stack app creation from natural language”

- Backend: Use Cursor AI an AI-powered IDE based on VS Code with auto-complete, chat prompts, debugging, and project-wide context. Perfect for writing/refining server logic.

Outline Your Architecture
1. Prompt Lovable/Bolt.new
Ask for "a React frontend with Tailwind, Supabase as backend, and authentication flow"
Export code (to GitHub or ZIP)
2. Refine via Cursor AI
Import the generated codebase into Cursor
Prompt Cursor to improve structure:
“Refactor authentication code, add Joi validation”
Cursor can generate tests, APIs, fix bugs, etc.
A Reddit user who did this shared:
“I did a full AWS thing… Except some minor tweaks here and there it was all Cursor and Claude.”

Step 3: Manage AI Workflow
- AI thrives with short, focused prompts: feed it ERROR logs or specific chunks, not the whole app

- Maintain context: keep docs, ER diagrams, project folder structure up-to-date so Cursor understands your codebase

- Use hybrid flow: prompt AI to scaffold, then refine manually; don’t simply trust its first output

Step 4: Build & Refine Iteratively
- Prototype fast: Leverage AI for scaffolding (frontend + backend)
arguxlabs.com+8joshsorenson.com+8reddit.com+8
- Fine-tune features with Cursor: validation, performance, bug fixes
- Keep user interface polished: one user said
“I took the code it produced and loaded it up in Cursor, and Cursor has done a great job adding to it since then.”

Example Tech Flow
1. Prompt Lovable/Bolt.new: “Create a TODO app with auth + Supabase DB”
2. Export code → open in Cursor
3. Cursor: “Add API endpoint /todos/create with validation and tests”
4. Cursor: “Refactor UI for mobile responsiveness”
5. Host frontend via Vercel, backend on Supabase or serverless

my tip
- You still need to oversee: AI suggests; you validate
- Use modular AI cycles: prompt, review, refine
-Balance control: don’t over-guide the AI—adapt to its patterns
- Avoid context overload: reset chats, maintain clean project docs

TL;DR
• Frontend: Lovable/Bolt.new to generate UI scaffolding
• Backend: Cursor AI to create, debug, and refine logic and APIs
• Workflow: prompt → export → refine → deployment

AI is your co pilot you stay in the driver’s seat
You can build a robust technical company using just these AI tools but it works best if you're guiding, cleaning up, and iterating. AI accelerates your work, but doesn’t replace the human in the loop