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Domino Data Lab empowers the largest AI-driven enterprises to build and operate AI at scale. Domino’s Enterprise AI Platform provides an integrated experience encompassing model development, MLOps, collaboration, and governance. With Domino, global enterprises can develop better medicines, grow more productive crops, develop more competitive products, and more. Founded in 2013, Domino is backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and other leading investors.

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Tech Hour

Agents 101: Build and deploy your first agent

Join us Dec 9th at 1 pm ET/10 am PT for a fast-paced live build as we build an enterprise-ready AI agent from scratch in real time.

This is not a slide deck presentation or a typical demo. We will start with an idea and build our way to a working agent using common tools (e.g., Claude Code) and skills. Watch the agent take shape in real time within a Domino workspace utilizing built-in tracing, and then see it come to life as we wire it up.

Along the way, we will share the practical techniques that make agents work for real teams, including prompting patterns, tool and skill setup, and testing and iteration strategies that turn a simple idea into an agent that solves real problems.

We will wrap up by deploying the agent, adjusting autoscaling, and configuring role-based access control, showing how Domino enables fast iteration while providing the tools needed for a scalable, governance-ready AI agent.

Bring your favorite IDE and build along with us.

Featured Speaker

Danny Stout

Director of Product Marketing

Danny W. Stout, Ph.D., is Product Marketing Director at Domino Data Lab and a data science and analytics leader with over two decades of experience. He held senior analytics and AI leadership roles across global organizations including Ernst & Young, Takeda, TIBCO, Quest, and Dell, spanning forecasting, pricing, analytics strategy, and data science consulting. His work emphasizes effectiveness over scale, focusing on governance, team alignment, and measurable outcomes as the determinants of successful AI adoption. Based in Charlton, MA, Danny holds a Ph.D. and combines technical leadership with practical insights that help organizations scale data science responsibly and effectively.