Context Engineering Tips 1) Be precise: vague requests lead to vague answers. The more specific you are, the better your results will be 2) Provide relevant code: share the specific files, folders, or code snippets that are central to your request 3) Include design documents: paste or attach sections from relevant design docs to give the AI the bigger picture 4) Share full error logs: for debugging, always provide the complete error message and any relevant logs or stack traces 5) Show database schemas: when working with databases, a screenshot of the schema helps the AI generate accurate code for data interaction 6) Use PR feedback: comments from a pull request make for context-rich prompts 7) Give examples: show an example of what you want the final output to look like 8) State your constraints: clearly list any requirements, such as libraries to use, patterns to follow, or things to avoid. Prompt engineering was about cleverly phrasing a question; context engineering is about constructing an entire information environment so the AI can solve the problem reliably. https://www.oreilly.com/radar/context-engineering-bringing-engineering-discipline-to-prompts-part-1/