context-engineering

Agent hallucinations often occur because the context is poorly curated. Context engineering solves this by deliberately structuring what the agent sees, from persistent rules files to transient error outputs, maximizing accuracy and minimizing distractions.

Structure context using a layered approach: load rules files first, then specs and architecture docs, relevant source files, error outputs, and finally conversation history. This hierarchical loading ensures the agent prioritizes persistent constraints over transient data.

To recover degraded agent output, apply hierarchical context loading by re-establishing the layered rules-file approach. Reload project-wide rules and feature-specific specs to realign the agent's focus before continuing the task.

When switching between codebase areas, reload context starting with Level 1 rules files and Level 2 feature specs. This persistent context loading resets the agent's focus boundaries and prevents cross-task data contamination.

Context engineering applies to any AI coding agent by utilizing layered rules file approaches like CLAUDE.md or equivalent project configuration files. It establishes data handling boundaries to manage what information the agent processes.