Hands-on Agentic AI for Leaders

Audit your recurring work to surface high-value workflow candidates — the ones where AI moves the business.

Take any workflow through analyze, deconstruct, design, build, test, run, improve — to ship it reliably.

You'll leave with a proven, repeatable methodology you can apply to every workflow you build — long after the cohort ends.

Distinguish the four types of context your AI needs — instructions, memory, files, and systems of record — and where each is kept.

Save every skill, prompt, agent, and context file you build to a GitHub repository — version-controlled and portable.

Build a knowledge graph your AI reads before it answers and updates after, so no conversation starts from zero.

Package your repeatable expertise — research, writing, analysis, decisions — as Agent Skills any AI can execute consistently.

Test your skills on real cases and compare versions side by side, so you refine with data, not intuition.

Leave with a portfolio of tested skills running on Claude, ChatGPT, M365 Copilot, or Gemini Enterprise.

Build workflows with fixed steps that run reliably without you, then schedule them to run on their own.

Build workflows you collaborate with at key steps, keeping quality control on high-stakes work.

Leave Week 2 with two working workflows: one you compose by hand, one you design, build, and test with the framework.

Build single-agent workflows on Claude, ChatGPT, M365 Copilot, and Google Gemini Enterprise for your highest-value use cases.

Build multi-agent systems where specialized agents hand off work to complete complex, multi-step workflows.

Shift from doing the work to designing the systems that do it for you.

Start your AI Registry in Week 1 and register every workflow you build, capturing how your business actually runs.

Link each workflow to the skills, prompts, and agents it uses, so anyone on your team can find and reuse them.

Leave with one place to see, share, and maintain every AI workflow your business runs.