context-engineering

Context engineering manages what information an AI agent sees during software development, ensuring it adheres to project conventions and maintains focused task execution without drifting.

To fix context drift, apply systemic drift correction to identify and correct incorrect patterns, ensuring the agent respects boundaries and follows established project conventions.

Set up a new project by providing the relevant rules file and source code to curate context, which structures how the agent perceives information for focused execution.

Yes, context management handles conversation history and provides structured context, keeping AI agents focused on relevant information during specific software development tasks.

The best way to maintain conventions is curating context to define exactly what information an agent sees and how it is structured, preventing systemic drift in codebase maintenance.

Context management may be unnecessary for simple, isolated tasks where systemic drift is unlikely, but it is crucial for complex codebase maintenance requiring strict convention adherence.