Why more context can make your coding agents worse

Coding agents perform worse when given excessive context because they cannot distinguish relevant information from noise, leading to context drift, inefficient token usage, and unreliable outputs. Rather than investing in more capable agents, IT leaders should prioritize building knowledge graphs that automatically scope and deliver only task-relevant context—including requirements, current decisions, and related history—ensuring agents work from accurate, up-to-date system records. This approach dramatically improves output quality and cost efficiency while making the system of record a living asset that serves both human teams and AI agents.