The Memory Wall: Why AI Agents Fail (and How to Fix Them)

May 19, 202609:45 am - 10:15 am
Stage 3

Description

Today's AI agents run on duct tape: separate systems for transactions, analytics, and vectors, stitched together with brittle ETL pipelines and growing engineering overhead. That approach won't survive the next wave of agentic AI, where enterprises need to support millions of concurrent agents, each with persistent memory, real-time data access, and consistent state. This session introduces the architecture that supports millions of agents: a converged distributed SQL platform that unifies OLTP, real-time analytics, and native vector search in a single ACID-compliant system, handling relational, vector, and full-text demands in one query layer. We'll walk through the Decide-Validate-Remember loop that production teams use to reduce token costs through persistent context and scale multi-agent workflows without state drift.
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TiDB, powered by PingCAP

TiDB, powered by PingCAP, is the distributed SQL database for AI agents. Create thousands of database branches in milliseconds, run OLTP + OLAP + vector in one engine, and scale elastically without...