Hands-On Implementation

This is not a product demo. Participants run structured evaluations using tasks from their actual work, comparing outputs across tools in real time. Three rounds: baseline, improved prompt, and adversarial. The tool that wins on benchmarks often loses on your specific business tasks. The only reliable evaluation is running your own work.

Five integration patterns that cover the majority of high-value AI use cases: the smart template, the document processor, the classifier, the research synthesizer, and the workflow connector. Each with enough implementation detail that participants can apply them immediately, even when the specific tools look different from the examples.

Pure practice. Participants work on prompts for their actual use cases with immediate feedback from running outputs and iterating. Three rounds of hands-on work covering baseline, structured, and advanced techniques. Thirty minutes of practice produces more durable skill improvement than hours of theory.

Not plan an automation. Not design an automation. Build one. Participants choose from pre-prepared starting points matched to their context, configure it during the session, and run it against real data before leaving. An automation you understand imperfectly is more valuable than a perfect design you never execute.

Activity metrics tell you people are using the tool. Output quality metrics tell you the outputs are good enough. Outcome metrics tell you the business is actually getting the result you intended. We synthesize the measurement frameworks from across the program into a practical 30-60-90 day review cadence.

The most important deliverable of the entire program. Participants brainstorm, score, and prioritize their AI initiatives, then assign named owners, specific start dates, and measurable success criteria to each one. A backlog without names and dates is a wishlist. You leave with commitments.