Agent Memory Is a Solved Problem. Agent Learning Is Not.
Karthik Ranganathan, Heather Downing
- When
- Thursday, July 23:20 PM – 3:40 PM · 20 min
- Where
- Expo Stage 1 NESan Francisco, CA · imported from ai.engineer's public schedule feed
About this session
The failures that break multi-agent systems are not reasoning failures, they are handoff failures. One agent works something out and the knowledge dies in its private context, because the only thing that crosses the boundary is output. Memory made each agent better in isolation and changed nothing about what the group knows. The missing primitive is supervised promotion: a deliberate decision about which private learning is worth sharing, moved into common knowledge with the reasoning attached, so trust survives the handoff. Today a human makes that call, and promoted knowledge resolves on read, in any tool, with no retrain or reindex. Those calls are also the training signal for what comes next: orchestrator agents, trained on what matters to the people they serve, that promote on their own. This talk covers how our collective knowledge grew as we approached memory promotion, including what the first build got wrong, and a live look at it working between humans and agents.
Speakers (2)
Co-founder and Co-CEO, Yugabyte
Karthik Ranganathan is co-founder and co-CEO of Yugabyte, the company behind YugabyteDB. He was one of the original database engineers at Facebook/Meta working on distributed databases including Cassandra and HBase.
Developer Advocate, Yugabyte
Heather Downing is a developer advocate and 7x Microsoft MVP focused on AI, data, security and C#/.NET. She has experience building enterprise voice, mobile and .NET applications and is active in developer-community speaking and mentorship.
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