context-engineering

To provide structured context for AI agents, you curate rules files, specs, source files, and error outputs into a comprehensive context hierarchy, ensuring the agent has the precise information needed to generate focused code without hallucinations.

Context engineering is the process of curating and structuring information for AI agents. You need it when initiating new coding sessions, troubleshooting output quality, or setting up projects for AI-assisted development to prevent hallucinations and maintain focus.

AI agents hallucinate or lose focus during code generation when they lack properly structured context. Curating a specific context hierarchy from rules files to conversation history ensures all relevant information is accessible, improving output relevance.

To set up project context for AI-assisted development, you load curated rules files, specifications, and source files into the AI agent's environment, establishing a customizable context hierarchy that guides precise and focused output generation.

For AI agent context management, you need to prepare curated rules files, project specifications, source files, and error outputs. These inputs provide the comprehensive context required to enhance the quality and relevance of agent outputs.