AI Agent & Database Evolution - AI agents are challenging the traditional database model designed for human interaction [1] - The industry recognizes the need for databases to adapt to the requirements of AI agents, which differ significantly from human users [1] Agentic Postgres Features - TimescaleDB introduces Agentic Postgres, an agent-ready version of Postgres designed to address the challenges posed by AI agents [2] - Agentic Postgres enables instant database branching, facilitating parallel agent evaluations, safe experiments, migrations, and isolated testing with minimal cost and time [2] - It includes a built-in MCP server, offering schema guidance, best practices, and secure, structured access to Postgres for agents, aiding in informed migrations [3] - Hybrid search (vector search and BM25) is integrated, allowing agents to directly retrieve data within the database [3] - The database is memory-native, providing a persistent context for agent evolution [3] AI Agent Requirements - AI agents require the ability to branch endlessly, run multiple experiments concurrently, and operate within isolated, contextualized, and secure sandboxes [4]

Big moment for Postgres!AI agents broke the idea of what a database is supposed to do.Traditional databases were built for humans, and Agents broke that model.- They branch endlessly.- They run ten experiments at once.- They need isolation, context, memory, structured reasoning, and safe sandboxes.Letting agents touch production systems is terrifying because the old model of Postgres was never built for this kind of behavior.Agentic Postgres is an agent-ready version of Postgres by @TimescaleDB that solves ...