This document is a compilation of best practices for AI-Native development, curated by our community. Discover useful tips and tricks for leveraging tools to improve your AI development process.
Welcome to the AI Native Development Guide! This is a community document run by the AI Native Development Community. In this document, we have compiled best practices for AI Native development using tools like GitHub Copilot in a specific format, so you can easily understand, evaluate, and apply them to your situation. Some are grouped together and named as patterns. We would be thrilled if you could give our GitHub repository a star or contribute in any way, no matter how small. Let's work together to pave the way for AI Native Development!
Some of these patterns have been tried and proven effective in individual environments, but others are idea-based and have not yet been tested for effectiveness in actual team environments. Please feel free to leave comments on GitHub Issues. We look forward to various discussions and the sharing of knowledge about AI Native development.
In this introduction, we will explain what AI Native development is and what patterns are. If you are already practicing AI Native development in your company and would like to contribute your experience to this document, we welcome your contribution!
Currently we support the following languages: English 🇺🇸, German 🇩🇪, Spanish 🇪🇸, French 🇫🇷, Italian 🇮🇹, Japanese 🇯🇵, Portuguese 🇵🇹, and Chinese 🇨🇳.
This "AI Native Development Guide" document is not yet in its final version, and there may be broken links, typos, and other errors. Your help in improving it is much appreciated. Please see how you can contribute to this document.
AI Native development is a approach to accelerating software development by incorporating a development process and culture that is based on collaboration with AI. In AI Native development, AI technologies such as GitHub Copilot and ChatGPT are used to significantly streamline traditional software development processes and create innovative solutions.
On the other hand, it is necessary to mention that the development style changes significantly from traditional methods with the introduction of AI Native development. While many benefits can be gained from using AI technologies, developers and teams need to be aware of the following points in order to adapt to these changes.
By incorporating AI appropriately into development, developers and teams can improve the quality and efficiency of their products/projects. We hope this guide will serve as a starting point for you to enter the world of AI Native development.
Patterns are a way of describing repeatable solutions to problems within a specific context. In AI Native development, patterns provide ideas for how developers and teams can use AI to achieve rapid product development. Patterns are divided into main sections such as title, problem description, context, influencing factors, and solutions. The pattern format is useful for describing proven solutions but can also be used when brainstorming new solutions for patterns that have not yet been established. This is because the structure of the patterns provides a framework for thinking about problems in a structured way.
Many patterns are still in their infancy at this stage. We encourage you to try them out and provide feedback. Also, if you discover a new pattern, please let us know via GitHub Issues. We look forward to your contributions!
AI Native Development Guideline is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.