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GitHub - Pythagora-io/gpt-pilot: Dev tool that writes scalable apps from scratch while the developer oversees the implementation

Oct 05, 2023 - github.com
GPT Pilot is a developer tool that leverages AI to increase productivity by up to 20 times. The tool allows developers to specify the type of app they want to build, and then GPT Pilot asks clarifying questions, creates the product and technical requirements, sets up the environment, and starts coding the app step by step. The developer oversees the process, reviewing each task completed by the AI and providing assistance when needed. The goal of GPT Pilot is to utilize GPT-4 to generate fully working, production-ready apps while the developer oversees the implementation.

The tool is designed to write most of the code for an app, with the developer needed for the remaining 5%. It also includes features such as requirements, how to start using gpt-pilot, other arguments, examples, main pillars of GPT Pilot, how GPT Pilot works, and how it differs from other similar tools. The tool is open source and the developers welcome contributions and suggestions for improvement.

Key takeaways:

  • GPT Pilot is a development tool that uses AI to help developers build apps 20x faster. It creates the product and technical requirements, sets up the environment, and starts coding the app step by step, while the developer oversees the process.
  • The tool is designed to write most of the code for an app (around 95%), with the developer needed for the remaining 5%. The goal is to research how much GPT-4 can be utilized to generate fully working, production-ready apps.
  • GPT Pilot works by asking the developer for the type of app they want to build, then it asks clarifying questions, creates the requirements, sets up the environment, and starts coding the app step by step. The developer is asked to review each task it finishes or to help when it gets stuck.
  • The tool is different from similar tools as it works with the developer to create a fully working production-ready app, it codes the app step by step just like a developer would in real life, and it works at any scale, with mechanisms that filter out the code so in each LLM conversation, it doesn't need to store the entire codebase in context.
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