Three memberships. One path from AI-curious to AI-leader.

Why AI is changing experienced IT professionals; the Six Capabilities of the AI Leadership Framework; AI readiness; a self leadership system for goals and execution; the GMH portal and community.

Output: AI Readiness Assessment and personal roadmap draft

A mental model for modern AI, what AI can actually do, the AI tool landscape, a formula for finding AI opportunities, and your first opportunity challenge.

Output: Your first AI Opportunity Statement

Prompting and context engineering, AI as a daily leverage tool, going from prompt to working application, an AI career path, and a 90 day transformation roadmap.

Output: Your 90 day AI Transformation Roadmap

AI mental models: LLMs, context, tokens, reasoning, hallucination, multimodal AI, and prompt and context engineering.

Output: Personal AI Fluency glossary and reusable prompt workflow

AI across research, meetings, email, documentation, analysis, and planning; design a Trigger, AI, Human, AI, Output workflow.

Output: One recurring work task redesigned as an AI workflow

General AI, search, coding, productivity, automation, design, and enterprise AI; the Problem, Capability, Tool, Workflow selection method.

Output: Your personal AI Stack

Problem discovery with 5 Whys, JTBD, pain versus symptom, and AI opportunity mapping.

Output: A completed Opportunity Canvas

The anatomy of an AI application: User, App, Model, Data, Tools, Output; a conceptual look at RAG and agents.

Output: An AI Solution Blueprint for a validated opportunity

Bootcamp Day 1

Output: AI Readiness Assessment and Personal Roadmap draft

Bootcamp Day 2

Output: First AI Opportunity Statement

Bootcamp Day 3

Output: 90 Day AI Transformation Roadmap

AI Fluency Blueprint

Output: Personal AI Fluency glossary and reusable prompt workflow

AI Leverage Formula

Output: A recurring task redesigned as an AI workflow

AI Tools System

Output: Personal AI Stack

AI Opportunity Blueprint

Output: Completed Opportunity Canvas

AI Strategy Formula

Output: AI Solution Blueprint

Package your Opportunity Statement, Opportunity Canvas, and Solution Blueprint and present them live.

Output: A portfolio ready AI Opportunity Case

Application architecture, models, APIs, and structured outputs.

Output: A working AI application

Problem, User, Workflow, plus AI product and UX design.

Output: An AI application built around a real user workflow

GPT, Claude, Gemini, open and multimodal models; select by quality, cost, latency, and capability.

Output: A model selection for a business scenario

RAG fundamentals, embeddings, retrieval, and vector databases.

Output: A working RAG based application

What an agent is, and tools, memory, and actions.

Output: An agent capable of using tools and taking actions

Agentic workflows, tool calling, MCP, and orchestration.

Output: An agentic workflow connected to a real, multi step process

AI assisted development and the vibe engineering workflow.

Output: An enterprise style application built with AI assisted development

Data and knowledge readiness, data quality, and golden data.

Output: A data readiness assessment for an AI solution

Human evaluation, LLM as judge, golden datasets, and quality metrics.

Output: An evaluation framework for an AI system

AI interaction design and human in the loop UX.

Output: An AI experience with control, feedback, explainability, and escalation

Identify a real problem, design the workflow, build an AI application, add RAG and an agent or automation where they fit, evaluate it, document the architecture, and demo the working solution.

Output: A demonstrated working AI system

The AI Leader role and an AI leadership operating model.

Output: A personal AI leadership plan

AI opportunity discovery and impact times feasibility prioritization.

Output: An AI opportunity portfolio

AI product discovery, an AI PRD, and product strategy.

Output: A product direction and roadmap for a validated AI opportunity

Building an AI business case, ROI, and value creation.

Output: An AI business case

Tokens, inference, embeddings, APIs, and unit economics; prove value in the AI Initiative Blueprint.

Output: An AI ROI model

The AI delivery lifecycle: POC to Pilot to MVP to Production.

Output: An AI initiative delivery plan

Responsible AI: bias, fairness, privacy, security, governance policy, and risk.

Output: An AI governance framework

Stakeholder leadership, change, and adoption.

Output: An AI adoption plan

Moving from POC to production and enterprise AI scaling.

Output: An AI scale plan

The full initiative from opportunity through business case, product, architecture, and build.

Output: An AI leadership simulation

Problem and user, opportunity, business case, product strategy and PRD, architecture, data, model and evaluation strategy, governance, human in the loop design, delivery roadmap, adoption, economics, and success metrics.

Output: A complete initiative plan presented to a panel