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AI in practice

I build as well as advise

My approach to AI is not purely academic. I work hands-on with AI tools every day, and I bring that practical understanding into every adoption engagement. I am independent: I am not a partner or reseller for any AI vendor, and I do not sell licences or technical integration services.

What this means for you

Advice grounded in hands-on experience

When I advise organisations on AI adoption, I need to deeply understand at least one platform — not just what it can do, but how it behaves, where it falls short, and what it demands from the people and processes around it. Surface-level familiarity with many tools is not enough to give honest, practical advice.

This means I can help you think clearly about:

  • What AI tools can realistically do in your organisation — and what they cannot
  • How to structure AI adoption so it delivers value, not just novelty
  • What responsible AI use looks like in practice, not just in policy documents
  • How AI platforms connect to the governance and compliance requirements your organisation already has
My toolbox

Claude is my home base — by deliberate choice

I have chosen Anthropic’s Claude as my primary working tool and as the foundation for the Adoption Risk Radar. This is not a default — it is a deliberate decision based on how I work, what I advise on, and what I believe responsible AI adoption requires.

Built for responsible use

Claude is built with safety, honesty, and transparency as core principles. That matters when I help organisations in regulated industries navigate EU AI Act requirements: the advice I give rests on a platform whose design supports it.

A platform I can build with

The Adoption Risk Radar is built on the Claude API, and I use Claude Code for prototyping and automation. This hands-on experience means I understand the practical realities of working with AI — not just the theory.

Breadth in daily work

  • Claude.ai for advisory work, strategic analysis, and content development
  • Claude API for building the Adoption Risk Radar
  • Claude Code for technical prototyping
  • Model Context Protocol (MCP) for connecting AI to organisational tools and data
  • Anthropic Academy certifications: AI Fluency, Claude 101, Introduction to MCP, and Claude Code in Action

I also work with other AI tools where relevant, including Microsoft Copilot and Google NotebookLM. But depth beats breadth: Claude is the platform I know most deeply and use most consistently.