AI Adoption & Implementation Lead
I turn operational constraints into AI-supported ways of working that people can validate, own and use.
Background
I spent 14 years in software delivery before focusing on the gap between AI deployment and real adoption. I shape the intervention with the people who own the work, then test whether the evidence supports scaling it.
Selected work
The graphic below shows what enters each workflow, where AI is used, who validates the output and what changed.
Product delivery
From conversations to a decision the Product Manager can act on.
Engineering
From repository changes to technical context people can trust.
Use AI only when the case survives validation
Implementation support
AI voice and text assistant
Ask about my work, the evidence behind it, my services or professional background.
Applies Carl Jacobi's inversion principle to AI prompt engineering. Instead of prompting directly toward a goal, the opposite is prompted first, surfacing failure modes and hidden variables, then refined into a precise, effective prompt. Demonstrated in training and delivery contexts.
Explores how Emotional Intelligence (EI) and AI work together in fast-paced Agile environments. Covers conflict resolution, adaptive leadership, and team performance through case studies, arguing that EI is the distinctively human complement to AI's analytical power.
Examines how AI integration into family life is transforming the parental role. Proposes a "parental emotional mediation" framework, adapting Goleman's emotional intelligence theory to the digital age, with practical tools like the "candy test" and "emotional traffic light."