Shared Memory for AI Coding Agents:
A Live Build with Meko

Learn How to Build a Shared Context Layer for AI Agents and Humans

While your coding agent remembers your projects, other agents are working on it don’t. This leads to a disconnect, where each agent is working in a silo, delivering context that doesn’t align and answers you cannot trust.

Meko is built to support shared memory, knowledge, and decision tracing, enabling agents to learn together.

In this webinar, we’ll build a shared contact layer live using two Python agents: A research agent records decisions and the reasons for them. A second agent, in a fresh process with no prior context, retrieves them.

Why Watch?

Join Heather Downing, Developer Advocate at Yugabyte, as we explore how to share contacts across agents and tools using Meko: decisions made in your terminal, retrievable by the agent reviewing the pull request, with your team controlling what becomes shared knowledge.

Sign up for a free Meko account to follow along. No prior experience required. You leave with a runnable repo and a Docker option to try it on your own project.

What You'll Learn

• When to use agent-scoped memory vs a shared knowledge base
• How to make your code, not the model, decide what gets persisted
• How to promote an agent's learning into team-wide knowledge
• How to trace every memory read and write

Register now and join live on September 22, 2026, to explore the shared memory for AI coding agents.