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

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Register here: https://www.pingcap.com/event/the-memory-wall-why-ai-agents-fail/

Date: June 25, 2026
Time: 11:00 – 12:00 PM CEST

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.

Register here: https://www.pingcap.com/event/the-memory-wall-why-ai-agents-fail/

In this webinar, TiDB Principal Solutions Architect, Bernard Kavanagh, 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.

Register here: https://www.pingcap.com/event/the-memory-wall-why-ai-agents-fail/

What you’ll learn:

  • Zero-ETL reasoning: How to give agents access to live operational data without the synchronization headache.
  • The ACID advantage: Using database transactions to coordinate multiple agents without race conditions.
  • Episodic memory: How to store learned actions as vectors alongside production data to cut token usage.
  • Safe sandboxing: Using serverless branching to let agents test solutions before they reach production.

Register here: https://www.pingcap.com/event/the-memory-wall-why-ai-agents-fail/

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