Context & Background
To support the company’s pivot to an AI-first strategy, the organisation needed more than AI features — it needed product teams who could think, design, and deliver with AI as part of everyday work. I designed and led a 4-week Agentic AI leadership programme for 30 triad leaders across Product, Design, and Engineering, partnering with AI Academy to deliver hands-on capability building.
Teams worked on real veterinary use cases, built agentic workflows, and delivered prototypes — three of which became production features in the company’s first Clinical AI product release.
This wasn’t “AI training.” It was capability transfer — from zero to production in one release cycle.
The Challenge
The company couldn’t become AI-first if only a handful of people understood how to use AI. We needed 30 product leaders to become AI-capable fast enough to ship real AI features in the next release cycle — not in theory, but in production.
The challenge wasn’t awareness.
It was turning AI into applied capability inside real work, at real speed.
The programme had to be:
- Hands-on, not classroom
- Based on real customer workflows
- Designed for triads, not individuals
- Fast enough to change behaviour in one quarter
- Repeatable without external trainers
🧪 What We Did
- Trained 30 PM, Design, and Engineering leads together
- Used 20 live veterinary use cases as the training base
- Produced 16 agentic prototypes in 4 weeks
- 3 were shipped in the first Clinical AI product release
- PMs began using AI for synthesis, prioritisation, and roadmap debates
The shift wasn’t technical — it was behavioural. AI became part of how the organisation worked, not a side initiative.
Strategy & Implementation
The solution was a 4-week agentic AI capability sprint, blending teaching, co-building, and live application.
1️⃣ Week 1 — AI Fundamentals
How AI actually works, where it fails, what it accelerates, and where human judgment stays central.
2️⃣ Week 2 — Prompts, Personas & Reasoning Models
How to structure prompts, layer context, refine outputs, and build reusable prompt systems.
3️⃣ Week 3 — Agentic Workflow Building
Multi-step workflows using Make, system prompts, conditional logic, and structured outputs.
4️⃣ Week 4 — Production Application
Teams developed real prototypes based on 20 live veterinary use cases, with demo, scoring, and selection.
Results & Impact
- 30 leaders gained hands-on AI workflow and agentic design capability
- AI embedded into product discovery, documentation, and decision-making
- 3 prototypes became part of the AI product line that generated €2M ARR in 6 months
- The programme became a repeatable onboarding asset for future hires
Key Insights & Learnings
I architected the programme structure, selected AI Academy as the enablement partner, defined the use-case framework, coached triad leads throughout the sprint, and converted the output into a repeatable internal capability model.
The goal wasn’t training.
It was building an AI-enabled product organisation — not just AI-enabled products.
Success Metrics: - Leadership AI competency scores
- Team adoption rates post-training
- AI-powered workflow implementations
- Organizational velocity improvements