Building the Memory Layer for AI Agents

​A hands-on workshop on agent memory, databases, and the tools that make AI agents persistent and reliable.
AI agents can reason and take action, but without memory, they lose context between interactions. In this workshop, we’ll explore how memory works in agentic applications and how to build the data layer that keeps agents informed across sessions.

What we'll cover:
🧠 Understanding Agent Memory
Explore different types of memory, including short-term, semantic, episodic, and procedural memory, and when to use each.

📝 The Agent Memory Landscape
Explore how tools and frameworks such as Mem0, Meko, and other agent memory solutions approach persistent memory, retrieval, context, and knowledge for AI agents.

​🗄️ Memory and Databases
Look at what agents actually need to store, retrieve, update, and manage as they interact with users and other agents, and why the database underneath matters.

⚡️ Meko
See how Meko provides a data layer for persistent agent memory, knowledge, and observability.

🌏 YugabyteDB
Explore how a distributed SQL database can support the state, memory, and data needs of agentic applications.

Who is this for?
Developers, AI engineers, data engineers, and anyone building or experimenting with AI agents.
You don't need to be an expert in agent memory or databases. Come with your laptop, questions, and ideas. We'll learn by building together.

​Details:
📅 Saturday, Oct 24th
🕙 10:00 AM – 2:00 PM
📍 TBA

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