Across the course, you'll practise the role of an AI-Native Value Architect twice over: first by building a working AI solution yourself, then by guiding a realistic initiative from early signals through to delivery decisions.
On day one you build an AI Risk Council: four agents working together, three specialists arguing their corner and a supervisor reconciling them into a single verdict. You will feel the disagreement between them, which is the point.
From there you work a case study through the full lifecycle, the kind of initiative organisations are dealing with right now: stuck between proof of concept and production. You'll align the people who matter, shape the solution approach, and build a roadmap that survives contact with delivery.
You'll work on:
- building a working multi-agent AI solution, with no coding required
- clarifying the real problem an AI initiative is trying to solve, before solutioning begins
- aligning stakeholders on value, risk, and intent
- framing discovery so teams focus on what actually matters
- shaping a viable AI solution approach, including data, operations, and risk considerations
- guiding delivery decisions as constraints and AI capability shift
- defining what success looks like and how learning is carried forward
Throughout the course, you'll use AI to support your thinking and facilitation, helping generate better questions, test options, and synthesise insights, while keeping human judgement and accountability front and centre.
You won't be training models or writing code.
You will build something that works, and you will practise leading the work that turns AI activity into outcomes.