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@@ -214,7 +214,7 @@ Here are the steps GPT Pilot takes to create an app:
- **Works at scale** - GPT Pilot isn't meant to create simple apps but rather so it can work at any scale. It has mechanisms that filter out the code, so in each LLM conversation, it doesn't need to store the entire codebase in context, but it shows the LLM only the relevant code for the current task it's working on. Once an app is finished, you can continue working on it by writing instructions on what feature you want to add.
# 🍻 Contributing
If you are interested in contributing to GPT Pilot, I would be more than happy to have you on board and also help you get started. Feel free to ping [zvonimir@pythagora.ai](mailto:zvonimir@pythagora.ai), and I'll help you get started.
If you are interested in contributing to GPT Pilot, join [our Discord server](https://discord.gg/HaqXugmxr9), check out open [GitHub issues](https://github.com/Pythagora-io/gpt-pilot/issues), and see if anything interests you. We would be happy to get help in resolving any of those. The best place to start is by reviewing blog posts mentioned above to understand how the architecture works before diving into the codebase.
## 🖥 Development
Other than the research, GPT Pilot needs to be debugged to work in different scenarios. For example, we realized that the quality of the code generated is very sensitive to the size of the development task. When the task is too broad, the code has too many bugs that are hard to fix, but when the development task is too narrow, GPT also seems to struggle in getting the task implemented into the existing code.