Additionally, the author provides practical tips to solve common documentation-related issues with LLMs. These include avoiding storing docs in files, writing text descriptions for images, providing OpenAPI specs for REST APIs, including example requests and responses in API descriptions, defining specific acronyms and terms, and including necessary imports in code examples. The author concludes by emphasizing that these guidelines can significantly enhance the usefulness of technical documentation for LLMs, thereby improving the developer experience.
Key takeaways:
- Large Language Models (LLMs) can be trained on technical documentation to improve developer experience, and a clear hierarchy of headings and subheadings helps LLMs understand the relationships between different sections of the documentation.
- Segmenting documentation by sub-products and maintaining separate documentation for each can significantly improve the LLM's understanding of the context and the user's intent.
- Troubleshooting sections formatted as Q&A and self-contained example code snippets are effective sources for LLMs as they mirror the questions users often ask and provide practical examples.
- Building a community forum can serve as a source for both developers and LLMs to get help on undocumented topics, and practical tips such as avoiding storing docs in files, writing text descriptions for images, and defining specific acronyms can significantly improve LLMs' ability to understand and accurately respond to user queries.