Want better AI outputs? Try context engineering.

Context engineering is emerging as a critical strategy for enhancing the functionality of AI-assisted development tools like GitHub Copilot by providing them with richer contextual information. Unlike prompt engineering, which focuses on phrasing, context engineering involves supplying relevant data in the appropriate format to improve AI outputs, as explained by Braintrust CEO Ankur Goyal. At GitHub Universe, Harald Kirschner, a principal product manager at Microsoft, highlighted three methods for applying context engineering: custom instructions, reusable prompts, and custom agents. Custom instructions allow developers to set coding conventions and standards that Copilot will automatically follow, while reusable prompts facilitate consistent execution of common tasks, and custom agents act as specialized AI assistants for specific responsibilities like API design or security analysis. By employing these techniques, developers can achieve more accurate, reliable, and consistent code generation, reducing the need for repetitive prompting and enhancing workflow efficiency.

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