More than thirty years in.
Still genuinely interested.

Three decades of enterprise L&D. Not a career by accident.

I started in learning and development in 1993. Since then I've designed and delivered capability programmes for some of the UK's largest organisations — across financial services, healthcare, retail, and the public sector.

The work has always been the same at its core: figure out what an organisation actually needs people to be able to do, then build something that makes that happen. Not a course. Not a completion rate. Capability that holds up on Monday morning.

Clients have included Oracle, Capita, and Amey. The work has ranged from individual leadership programmes to organisation-wide learning transformations. The thread running through all of it is a commitment to honest diagnosis before any kind of solution.

Mostly self-taught. Entirely hands-on.

Two years ago I made a decision: instead of learning about AI from the outside, I would learn by building. I've taken courses — but the real education has been the work itself. Real systems, real problems, documented with unusual rigour.

That number — 3.7 million words — sounds extraordinary until you understand what it represents: every architectural decision reasoned through in dialogue, every bug diagnosed out loud, every design choice tested against a thinking partner before a line of code was written. It's not chat. It's a working method.

This matters for the work I do with organisations. When I talk about what AI can and can't do, what it costs to implement well, what the realistic capability gap looks like — I'm drawing on direct experience, not vendor briefings or LinkedIn hot takes.

The PRLM — a persistent memory architecture giving an AI system genuine continuity across sessions — is one example. CoVey, an intelligent CV builder built on verified real experience, is another. The NHS Snakes and Ladders simulator is a third. Each one built to solve a real problem. Each one documented in the work section.

Strength through deserved confidence.

The tagline isn't decorative. It's a position on what learning is actually for.

Most AI training — and most L&D, if we're honest — optimises for confidence without earning it.

The evidence?

• A two-hour workshop.
• A completion certificate.
• A delegate who feels good but can't do anything different on Tuesday.

Deserved confidence is harder to produce and more durable when you have it. It comes from actually doing something difficult, with support, until you can do it without the support.

What that requires:

• Honest diagnosis of what's stopping people.
• Content built around real obstacles, not imagined ones.

That's what I build. It's slower to sell than a course catalogue. But it's what actually works.

Based in Long Eaton, Nottinghamshire. Curious by disposition.

I'm a reader, a thinker, and — in the last two years — an unlikely software developer. I have a tendency to document things obsessively, which turns out to be useful when you're building AI systems that need to remember what happened last week.

I work independently. No associates, no subcontractors, no account managers. When you work with me, you work with me. That's a constraint and a feature simultaneously.

I'm not trying to build an agency. I'm trying to do good work with organisations that take capability seriously. If that sounds like you, the contact page is the right next step.