I spent 15 years in manufacturing. Here is why that made me a better AI builder.

In early 2026, I sat in a room at the ANCHR AI Native Bootcamp and built an AI agent that automates job search from end to end. A few weeks later, I built this website using Claude Code, with no prior coding background.

Both of those things would have seemed implausible to me five years ago. And yet the path that led there was not a sudden leap. It was a direct line from fifteen years of work I had already done.

The long way round

I started in manufacturing operations: sales, supplier quality, lean manufacturing. Years on factory floors running root cause analysis, chasing on-time delivery, and learning why the same problem kept appearing on the third shift but never the first.

From there: digital transformation consulting. More than 100 assessments across 13 sectors, delivering change management programmes for some of the world’s largest industrial organisations. Teaching people not just what Industry 4.0 means in theory, but what it means for the person running a specific machine in a specific plant who has been doing it the same way for twenty years.

None of that looks like an AI career on paper. But it turned out to be exactly the right preparation for one.

What experience actually gives you

When I built JobPilot, I was not starting from zero. I had spent years understanding how hiring decisions are made, what makes a candidate stand out, where the process breaks down for applicants who are technically qualified but not getting through. I could describe the job search workflow in enough detail to build an agent that worked on the first day.

When I built this website, I was not starting from zero either. I had a clear picture of what the site needed to do, who it was for, and what credible professional services design looks like. The AI tool handled the code. I handled the judgement.

This is the pattern I keep seeing. The people who build the most useful AI tools are the ones who bring the deepest understanding of the problem. The tool provides leverage. The expertise provides direction.

The fear that experience is a liability

There is a version of the AI conversation that frames experience as a disadvantage. The argument goes that the AI age rewards people who are not weighed down by how things have always been done — that the younger and more technically fluent, the better positioned.

I do not think that is right. Or rather, it is only true if your experience has made you rigid rather than deep.

The people who struggle with AI adoption are not the ones who have too much experience. They are the ones who cannot describe their workflows in precise terms, who have always relied on intuition rather than articulation, who cannot separate what they do from why they do it. Those people find AI tools frustrating because the tool cannot read their minds.

The people who thrive are the ones who can say: here is exactly how this process works, here is where it breaks down, here is what a better version would look like. Those people give the AI enough to work with. And the AI gives them back scale they could not achieve alone.

What the pivot actually looked like

I want to be honest about the career reinvention framing, because I think it is slightly misleading.

I did not leave digital transformation and change management. I am still in it. What changed is that I can now do it with a new set of tools, and I can help others do the same. The RISE by BCG programme I completed in 2025 sharpened the strategic framing. The AI Native Bootcamp gave me the building capability. But the foundation — fifteen years of understanding how organisations change, and why they resist, and what makes the difference between transformation that sticks and transformation that fades — that part did not change at all.

That foundation is what I bring into every AI conversation. And it turns out to matter more than the technical fluency.

What this means for where you are now

If you are in the middle of a career that looks nothing like tech, and you are wondering whether the AI wave is passing you by, I would push back on that framing.

Your domain knowledge is not a limitation. It is the raw material. The question is whether you know how to use it, and whether you are willing to learn the tools that let you point it in new directions.

The tools exist. The expertise you have built is the starting point. The gap between those two things is smaller than most people think.