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Friday August 14, 2026 09:40 - 09:55 KST
I plugged 17 MCP servers into my agent, and the agent got worse: slower decisions, dumber questions, somehow forgetting how to use the same tool it had used five minutes earlier.

That's not an MCP problem, the protocol works. The problem is that MCP defines how a tool is invoked and exactly nothing else. Every invocation is a fresh ceremony of re-discover, re-parse, re-decide, re-handle, with no persistent artifact wrapping any of it. The agent has no memory of what worked, no feedback signal for what didn't, no surrounding context to anchor which tool, when, and why.

Stateless function calls in an inherently stateful problem.

This talk is about the layer above MCP, the one that turns a directory of well-formed tool calls into coherent agent behavior, call it a Skill, a context artifact, or whatever your stack calls it. I'll show what changes when you bolt one on top of MCP: tool-call frequency drops, accuracy climbs, dumb questions to the user disappear.

If your MCP integration demos beautifully but production doesn't, this is the talk for you.

(And if you haven't shipped an MCP server yet, congrats. You'll skip a few mistakes. The protocol is the easy part.)
Speakers
avatar for Baruch Sadogursky

Baruch Sadogursky

Member of DevRel Staff, Tessl AI
Baruch Sadogursky (@jbaruch) did Java before it had generics, DevOps before there was Docker, and DevRel before it had a name. He built DevRel at JFrog, co-authored "Liquid Software" and "DevOps Tools for Java Developers," and is a Java Champion, Microsoft MVP, and CNCF Ambassador... Read More →
Friday August 14, 2026 09:40 - 09:55 KST
Grand Ballroom 1 + 2

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