context-engineering

To stop AI agents from ignoring project guidelines, you must optimize AI context by curating information and defining persistent rules files. This enforces project-specific boundaries, preventing the agent from generating incorrect code.

Context engineering is the process of hierarchically structuring and curating information provided to AI agents. You need it to address context starvation, flooding, and staleness, ensuring high output quality and relevance.

Structure AI context through hierarchical organization and explicit communication patterns. This manages information overload, helps agents avoid hallucinations, and maintains focus by delivering the right information at the right time.

Yes, you can set up persistent rules files to enforce coding conventions. By defining and loading these project-specific rules, you establish strict boundaries and explicit patterns that the AI agent must follow during code generation.

The best way to re-establish proper context is to use a framework that curates conversation history and project rules. This addresses context confusion by explicitly guiding the agent back to established constraints and conventions.