You click "Build My App." Three minutes later, you have a working web application with user accounts, a database, and a live URL. But what actually happens in those 3 minutes?
This is a behind-the-scenes look at Metacloud's build pipeline — how we go from a text description to production code.
The Five Stages
Every Metacloud app goes through five stages, each visible in real-time on your project page:
- 📝 Describe — You tell us what you need
- 🧩 Plan — AI breaks your idea into buildable features
- 🔧 Build — Code is generated for each feature
- 🔍 Review — AI reviews its own code for quality
- 🚀 Deploy — Code is merged and your app goes live
Let's walk through each one.
Stage 1: Describe
You either pick a template (CRM, Invoicing, Help Desk, Project Tracker) or describe your own app in plain English. For example:
"A client portal for my accounting firm where customers upload documents, track deadlines, and message us."
The system creates a project, sets up a git repository, and queues the planning stage. This takes about 10 seconds.
Stage 2: Plan
This is where AI earns its keep. Your description gets analyzed and broken down into separate, buildable features — typically 3-5 per app.
For that accounting client portal, the breakdown might look like:
- app.py — Main application with authentication, navigation, and dashboard
- documents.py — Document upload, storage, and management
- deadlines.py — Deadline tracking with calendar view and reminders
- messaging.py — Client-firm messaging system
Each feature becomes a separate Flask Blueprint — a modular piece of the application that can be built and tested independently.
Why multi-file? Early on, we tried generating entire apps as a single file. It worked for simple apps, but anything beyond ~800 lines would get truncated mid-function. Splitting into Blueprints solved this completely — each file stays under 500 lines, and every feature gets built in full.
Stage 3: Build
Each feature is built one at a time. The AI generates complete, working Python code — not scaffolding, not pseudocode, but production-ready Flask routes with:
- Database models — SQLite tables with proper relationships
- HTML templates — Clean, responsive UI (inline in the Blueprint)
- Business logic — CRUD operations, filtering, search, pagination
- Authentication — Login, signup, team workspaces baked in
Each feature gets its own git branch. If something fails, it doesn't affect the others.
Stage 4: Review
Here's where it gets interesting: the AI reviews its own code. A separate review pass checks for:
- Import errors and missing dependencies
- SQL injection vulnerabilities
- Broken route definitions
- Template rendering issues
- Missing error handling
If the review finds issues, the code goes back to the Build stage with specific fix instructions. Most features pass on the first try — our multi-file architecture reduced review rejections from ~90% to under 5%.
Stage 5: Deploy
Once approved, each feature branch merges into main. When all features are merged, your app starts automatically on its own subdomain: your-app.metacloud.io.
The deployed app runs as a real Flask application with:
- Its own SQLite database
- HTTPS via Cloudflare
- User authentication ready to go
- Full source code you can download anytime
What Makes This Different
Most "AI app builders" generate code and hand you a zip file. Or they build on a proprietary platform where you can't see or own the code.
Metacloud is different:
- Real code, not a black box — every line is visible in the Source tab, with full git history
- Standard technology — Flask, Python, SQLite. No vendor lock-in.
- Instant deployment — your app is live the moment it's built
- Iterate naturally — describe changes, and the pipeline runs again
Try It Yourself
Pick a template or describe your own app — it's free to try, and you'll see every stage happen in real time.