What It Really Takes to Build AI Agents

Name: What It Really Takes to Build AI Agents
Start: 2026-06-23

The AI: ROI Conference

Most companies experimenting with AI agents can get to something workable, far fewer know how to turn that momentum into something durable, governed, and genuinely useful. The leader’s prerogative in 2026 is closing that gap.

Chris Van Dyke

Founder, SplittingAtom Labs

Michael Domanic

Head of AI, Section

What separates durable business capability from expensive demos

Join Section’s Head of AI, Michael Domanic, and Cloudera’s Product Lead for AI Platform, Chris Van Dyke, on June 23 from 1 - 2 pm ET as they unpack the governance, strategy, and operational rigor required to scale AI agents to production. They’ll cover questions like:

What does a strong foundation for agent memory, identity, and oversight actually look like?
How do you design AI agents that actually help get work done?
How do you scale a successful AI experiment into something an entire company can use?
What governance considerations matter most around oversight, autonomy, risk, and accountability?
How do you measure whether an AI agent is creating real business value?

They’re taking your questions, too. RSVP for free and start building for real adoption, measurable value, and long-term advantage.

Meet your speakers

Chris Van Dyke

Founder, SplittingAtom Labs

Chris Van Dyke is the Founder of SplittingAtom Labs, a skunkworks for applied AI building data infrastructure, autonomous engineering tools, and personal agents for enterprise and personal use. He recently joined Teradata, where he leads the development of their Agent Harness. Previously, he served as Product Lead for AI Platform at Cloudera, helping enterprises bring data and AI together, and before that held senior ML/AI engineering roles at Microsoft.

Michael Domanic

Head of AI, Section

Michael Domanic leads AI transformation at Section, overseeing generative AI strategy and governance. Previously the Head of AI at UserTesting, he has driven adoption programs that scaled AI tools to widespread weekly use and enabled employees to build hundreds of custom GPTs for internal workflows. He also partners with product leadership on AI-forward roadmap and customer-facing applications.

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