Agentic AI stoot retrieval-systemen tegen grenzen aan, context architecture biedt uitweg

Enterprise AI systems are shifting toward context architecture as traditional retrieval methods struggle to handle the demands of autonomous agents. Redis and other platforms are addressing a fundamental problem: AI agents fail not due to model limitations, but because underlying data is fragmented, outdated, and poorly organized for machine processing.