Learn how to identify where AI creates real operational leverage—reducing cycle time, improving quality, and eliminating repetitive coordination work. Map day-to-day operational pain into workflows that take advantage of today’s AI capabilities.

Learn to confidently navigate the modern AI tool ecosystem as an operator. Get a fast-paced crash course on today’s most popular tools—n8n, Lovable, Manus, Claude Code, and Cursor. Learn to choose the right tool for the job and move fast without getting lost in tool churn.

Learn to prototype operational systems quickly by combining lightweight scripting with AI-powered tools. Build glue-code utilities and simple dashboards for transforming data, generating reports, and automating analysis—without needing to become a full-time engineer.

Learn how to design LLM-powered workflows that plug into the tools your teams already use—Slack, email, docs, spreadsheets, CRMs, and ticketing systems—and produce structured outputs that drive real action. Build workflows for routing, drafting, extraction, classification, and operational decision support.

Learn more advanced patterns for prompts and context that make operational workflows consistent and reliable. Understand how to reduce variability, limit hallucinations, and design repeatable outputs—so your automations behave predictably across messy real-world inputs.

Learn how to connect LLMs to real tools and services so they can take action—not just generate text. Understand tool calling at a practical level, then use MCP-style integrations to define tool schemas, route execution, and connect models to the services that run operations.

Learn how to evolve from static workflows into agentic systems that can plan, choose actions, and complete multi-step tasks. Design agents that run bounded loops—plan, act, verify, retry—while maintaining control over memory, state, and escalation.

Learn how advanced teams deploy autonomous agents at scale. Explore patterns for supervision, multi-step delegation, and “AI org charts” that coordinate specialist agents—so you can increase throughput while maintaining clear ownership, oversight, and accountability.

Apply the concepts and techniques covered throughout the program to design, build, and deploy a substantial AI operations solution. Work independently or in small teams to implement a production-ready workflow or agent with measurable outcomes, clear constraints, and real integrations.

Showcase your work to the community. Present your capstone, demonstrate it end-to-end, and receive feedback from peers and instructors in our final demo day celebration—highlighting impact and a practical path to adoption inside real teams.