Why Context Matters When Using AI for Programming

AI is an incredible tool for generating and fixing code, but it’s only as good as the context it’s given. When asking an AI to generate a function or fix one, the surrounding components of the system—such as data structures, APIs, dependencies, and external functions—are crucial to producing a correct solution.

Without this context, AI has to make assumptions, leading to code that might look correct but fails when integrated. For example, if a function processes user input but the structure of that input isn’t provided, the AI might generate logic that doesn’t align with the actual data. Similarly, if a function depends on global state or API calls that aren’t included in the request, the AI won’t be able to account for them properly.

Always provide relevant surrounding code and details. The more context AI has, the more accurate and useful its response will be—turning it from a guesswork generator into a true coding assistant.