GPT Engineer generates entire codebases from natural language descriptions. Describe your app, get working code.
Quick Deploy
```bash # Install pip install gpt-engineer
# Set your OpenAI key export OPENAI_API_KEY=your-key
# Create a project mkdir my-project && cd my-project echo "Create a todo app with React and local storage" > prompt
# Generate! gpte ```
Use Cases
Rapid Prototyping: Go from idea to working prototype in minutes.
Learning: See how experienced developers would structure code.
Boilerplate Generation: Skip the boring setup, get to the interesting parts.
MVP Development: Build minimum viable products fast.
Code Examples: Generate examples for documentation.
Hackathons: Ship faster than everyone else.
Example Prompts
``` Create a REST API with Flask that manages a book library. Include CRUD operations and SQLite database.
Build a CLI tool that converts markdown to HTML. Support custom CSS themes.
Make a Chrome extension that tracks time spent on websites. Show daily/weekly reports. ```
How It Works
1. You describe what you want 2. AI asks clarifying questions 3. Generates file structure 4. Writes all the code 5. You can iterate and refine
Pro Tips
- Be specific about tech stack - Mention edge cases you care about - Review generated code before running - Use for learning, not production (yet)
Limitations
- Complex apps need iteration - May not follow all best practices - Requires API credits - Better for greenfield projects