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AI code generation

Appifex uses advanced AI models to transform your natural language descriptions into production-ready code.

How it works

  1. You describe what you want in plain English
  2. AI analyzes your requirements and plans the implementation
  3. Code generates - components, APIs, database schemas, styling
  4. Automatic deployment - your app goes live immediately

Writing effective prompts

Be specific about features

Good:

Create a fitness tracking app with:
- Daily workout logging
- Progress charts showing weekly trends
- Goal setting with reminders
- Social sharing of achievements

Less effective:

Make a fitness app

Include UI preferences

Build a minimalist note-taking app with:
- Clean white background
- Sans-serif typography
- Floating action button for new notes
- Card-based note display

Specify data relationships

Create a project management tool where:
- Users belong to organizations
- Projects have multiple tasks
- Tasks can be assigned to team members
- Comments are attached to tasks

Attach images for context

Upload up to 3 images (max 5MB each) to help AI understand your vision:

  • Mockups - Figma designs, sketches, wireframes
  • Screenshots - Existing apps you want to reference
  • Inspiration - UI patterns you like

Real-time progress tracking

As your app generates, you'll see:

EventWhat it means
ThinkingAI is planning the implementation
Tool callA file is being created or modified
Platform switchMoving between web/mobile/backend
DeploymentPushing to hosting platforms
CompleteYour app is ready

Iterating on your app

After initial generation, continue the conversation:

"Add dark mode support"
"Make the sidebar collapsible"
"Add pagination to the user list"

AI reads your existing code and makes targeted changes.

Model selection

Appifex uses multiple AI models optimized for different tasks:

  • Claude - Complex reasoning and architecture decisions
  • Gemini - Fast iteration and code generation

The platform automatically selects the best model, or you can choose manually.

Best practices

  1. Start with core features - Add complexity gradually
  2. One change at a time - Easier to review and iterate
  3. Review generated code - Use the editor to understand and customize
  4. Save your prompts - Good prompts are reusable patterns