Every job I've had has been the same job in disguise: go into a business, understand how it actually runs, and make it run better.
That's what product management is. Not writing software: working out which problem actually matters, scoping the work properly, and making sure what gets built is the thing the business needed, not the thing that was easiest to ask for. I did it for ten years: on the founding team of a £10m health business that was successfully acquired, ending as its Chief Product Officer, then at a $200m food-tech start-up with thousands of staff. I've seen how both start-ups and big organisations are run. At the health business, daily operations ran on a platform I scoped and delivered; getting the scope right cut food waste from 15% to 3%, which paid for the platform many times over.
I'm also a formally trained business analyst (Level 4). Process mapping, requirements, gap analysis: the qualification is, quite literally, the discipline of walking into an unfamiliar operation, finding where it leaks, and specifying the fix. That is the assessment you're buying.
And I don't stop at the recommendation. The quoting agent and the live AI nutritionist in the work above are my builds, end to end. When I say I'll fix it, I mean I'll build it, train your team on it, and hand it over running.
AI is moving businesses from human work to humans working alongside machines. I lead with the human side: I understand how your people actually do the work before I automate any of it, then I support them through the change. I look for efficiency, but efficiency is only half the job. The other half is moving your people onto the highest-value work only people can do, not replacing them with a tool.
"AI projects don't fail because the technology isn't good enough. They fail because nobody scoped the problem properly, the tool doesn't fit how people actually work, or nobody defined success before starting."
Ten years of product management is ten years of preventing exactly that.
