Day 1

Learn how to take agentic applications from lab experiments to production-grade deployments using AWS Copilot. This workshop shows how to automate infrastructure provisioning, CI/CD pipelines, and integrate standards like the Model Context Protocol (MCP) to extend agents beyond chat into real-world tasks.

By the end, you’ll know how to create resilient, scalable, and context-aware AI agents that can truly operate in enterprise environments, while freeing developers to focus on logic instead of infrastructure firefighting.

As organizations move from standalone LLM applications to complex, agentic AI workflows, LLMOps becomes the critical backbone enabling scale, reliability, and trust. This session explores how to design robust LLMOps frameworks to build, monitor, and govern multi-agent systems in production. It will cover practical approaches to orchestration, observability, evaluation, cost control, and risk management, along with governance strategies to ensure compliance, safety, and responsible AI at scale. Attendees will leave with actionable insights to operationalize agentic AI systems that are resilient, transparent, and enterprise-ready.