Stack Internal has launched a new AI-native knowledge platform designed to transform distributed organizational data into "decision-grade" knowledge for both human teams and AI agents. To combat information silos and stale data, the platform implements automatic ingestion of content from sources such as Stack Internal community, Google Docs, and Slack. This process involves slicing, storing, and evaluating raw data for reliability and authority. A key technical advancement is the treatment of AI agents as "first-class citizens," providing them with permission-aware, identity-aware access to ensure compliance and prevent data leakage. For human users, a new chat interface introduces response-level confidence labels and provenance cards to verify information origins. Developers can integrate these capabilities into existing workflows via API and Model Context Protocol (MCP) server integrations. Additionally, the release includes Swagger API (v3) endpoints, enabling engineering leaders to monitor knowledge consumption through precise metrics, such as internal API usage volumes and V2 versus V3 adoption rates. These features aim to create a persistent, durable knowledge layer that mitigates the risks of agents executing tasks based on conflicting or historical misinformation.