Prompting GitHub Copilot Chat to become your personal AI assistant for accessibility

Large Language Models (LLMs) like GitHub Copilot can be guided to produce more accurate outputs through prompt engineering, which involves crafting specific prompts to elicit desired responses. GitHub Copilot Chat enhances the code completion capabilities of GitHub Copilot by providing a chat interface that allows developers to interact more directly with the LLM, using contextual information from code and additional prompts to improve results. This blog focuses on using GitHub Copilot Chat to improve accessibility in coding practices, offering foundational prompts and examples to guide developers in writing code that meets WCAG 2.1 accessibility standards. It emphasizes the importance of developers acting as lead developers who verify and refine suggestions made by GitHub Copilot Chat, particularly when it comes to ensuring accessibility and usability in code. While GitHub Copilot Chat is a valuable tool for learning and improving code, it is crucial for developers to work alongside qualified accessibility experts and conduct proper code reviews to ensure that all suggestions meet necessary standards.