Aug: Agentic on K8s + swag

Name: Aug: Agentic on K8s + swag
Start: 2026-08-04T22:00:00.000Z
End: 2026-08-05T01:00:00.000Z
Location: 90 Broadway, Cambridge, MA, Cambridge

90 Broadway, Cambridge, MA, Cambridge, 90 BroadwayTuesday, Aug 4 · 6:00 PM

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Free

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3% Flock fee · You keep 97%

Doors 6:00 PM

The Story

[Komodor](https://komodor.com/) is sponsoring food & bev this time - thank you **Komodor!!** As usual: 1. **RSVP's close 48 hrs before the event**. Please make it easy on us by RSVP'ing only if you intend to show up. 2. **Don't be late!** You'll get locked out, and that's no fun! === **Agenda** 6:00 pm: food / drinks / networking 6:20 pm: Talk #1: **Building Agentic AI** with [Mickael Alliel](https://www.linkedin.com/in/mickaelalliel/) 7:00 pm: Who is hiring? Who is looking? 7:10 pm: Talk #2: TBD 7:50 pm: Talk #3: **Build an AI agent, win a prize** with [Harout Parseghian](https://www.linkedin.com/in/haroutparseghian/) 8:30 pm: Finish **Speakers & topics** **1\. How to Build Quality\-Driven Agentic AI in Noisy Big Data Environments**, [Mickael Alliel](https://www.linkedin.com/in/mickaelalliel/), Komodor Building reliable agentic AI systems in production environments presents unique challenges when dealing with massive, noisy datasets. This talk shares hard-won lessons from developing Klaudia, Komodor's AI agent that processes millions of Kubernetes events daily to deliver autonomous troubleshooting with 95%+ accuracy. The fundamental challenge isn't LLM capability—it's building systems that maintain reliability when 90% of your data is noise. We'll explore why most agentic AI fails in production: hallucinations masquerading as insights, inability to validate reasoning chains, and the brittle nature of RAG systems when dealing with complex, interconnected failure modes. This session covers practical know-how learned through painful production iterations: how to build validation frameworks that catch LLM errors before they reach users, architectural patterns for constraining problem spaces without losing effectiveness, and techniques for creating evidence-based reasoning that can be audited and improved systematically. You'll learn specific strategies for LLM validation in high-stakes environments, including confidence scoring systems, multi-agent verificati