Google Cloud's Knowledge Catalog is enhancing its context engine for agents with new preview features. Self-learning context enrichment analyzes agent and user interactions to automatically identify and update missing or outdated business context. Knowledge Studio provides a visual context graph and conversational exploration for managing this context. This addresses the challenge of manually curating context as the number of agents scales. Gemini-powered enrichment extracts verified definitions from various business documents and code repositories. These definitions are then organized into governed, reusable context sets for agents. This improves agent accuracy, reduces latency, and token usage significantly. Enrichment capabilities connect to both structured and unstructured data sources. Proposed context updates are presented with source citations and confidence scores for review. User and agent interactions pinpoint areas where agents struggle, enabling automatic fixes. Automation can be configured with confidence score thresholds for auto-publishing changes. Context sets allow for curated, domain-specific subsets of the broader context graph. These sets enforce data governance and fine-grained access control. Knowledge Studio transforms Knowledge Catalog into an interactive command center for context management. It offers visual navigation, conversational exploration, and version control for changes. These new features aim to keep context current and improve agent performance across organizations.