How I work.

I work on the software people have to use to do their jobs. I sit with them, find where it breaks, and change what has to change in and around the product so the money comes back.

A team of four at a glass wall where a day-in-the-life canvas and a persona sheet are taped up, two of them pointing at the same step. — A working session at the wall.

Where you might be.

You’re replacing a system people have used for years.

The best time to call. How the work gets done is still open to change, and the people who do it can tell you where the old one broke.

You’re building something new, and AI is part of it from the start.

The cheapest time to find out. Nothing exists yet, so nothing has to be undone. What the people it’s for actually need gets answered before the first screen is drawn.

You’ve been told to do something with AI, and nobody can say where.

The most common call. Start with the working session. Bring one of your biggest problems and the people who’ll have to live with the answer, and ninety minutes later you have one direction and a straight answer on the money.

It launched, and the workarounds have started.

Still worth the call. I can help, and I’ll say plainly what can still change and what is now fixed by the budget and the deadline. The earlier you call, the more of the value survives.

Three ways to work with me.

Each one leads to the next, and the first counts in full toward the second.

Find out whether the money comes back before you spend it.

A working session, ninety minutes.

Start with the working session. Bring up to six people and one of your biggest problems, and you leave with one AI idea the whole team agrees on and a straight answer on whether to spend money on it. If you go on within 45 days, it counts in full toward the next step.

Book a working session What happens in the ninety minutes

The single highest-value place to put AI, and what it’s worth.

AI Opportunity Mapping, half a day to two days.

If it’s worth going further, we map where AI pays, with your leadership team, across the customer journey, the service behind it and the workflows that decide the outcome. You walk out with a written brief that names the place, why, and the rough value and cost.

Proof that it works, before the money is spent.

Build the Proof, four to five weeks, then as needed.

If the brief says build, we prove it first, with a few real people doing their real work on the chosen bet. You walk out with a tested concept, the return case, and a plain go, pivot or stop.

For a bigger question there is a three-month residency as your senior AI experience lead, or a standing advisory seat, for as far as you want to go. I share fees when we talk.

Whether the money comes back is decided by the technology the people who have to use it.

Surveys and dashboards describe the problem and move nothing. So I sit with the people who do the work while they do it, then put what I see next to the numbers your systems already collect. One says what is happening. The other says why.

Before anything is built, a few of those people do their real work with the concept, and we measure what changed. That is the proof, and it comes before the money is spent.

The product is never the whole of it. It sits inside a service, the process before and after it, the handoffs between people and teams, who does what, the training. Change the software without those and the software gets worked around.

I call this way of looking at it Workflow Economics. The return on AI depends on what people do differently once it’s there, so that is what I map, test and measure.