How I got here

I'm fifty. The working part of that is a bit over thirty years.

Melbourne first. University, business and marketing. Then a few years chasing music and DJing, until enough people around me suggested I get a real job that I eventually did.

Then about ten years in corporate, starting somewhere near the bottom. I felt like a number, and I was one. The thing that changed it was getting passed over for a role I wanted. Not the rejection. The reason. I was told I didn't have the confidence for it, and that landed harder than the no did.

That sent me into Tony Robbins material first, then into formal NLP training, then into coaching other people through the same thing.

Watching someone arrive at their own realisation, rather than being handed mine, is still the part of this work I like most.

Digital marketing came next. Ten years of it, mostly allied health and professional services, mostly Meta advertising.

None of it was a plan. Each move happened because the same thing kept turning up and I eventually paid attention.

Why I waited

I didn't write anything about AI for two and a half years.

That was deliberate. For most of that stretch, what existed could hold a conversation and not much else. Impressive to watch. Not something I'd put in front of a business with a payroll to meet.

My rule is simple. Wait until a technology is mature enough to make a real difference, then move fast. Never at the expense of how the business is actually structured.

That point arrived. Systems that run a whole process unattended, hold your context permanently and take correction in conversation are real now.  I run them in my own business before I put them in anyone else's. My weekly
client reporting was the first process I handed over, and it's the one I'll show you.

What I do now

I install AI coworkers into Australian service businesses with five to fifty staff, and I train the people who have to work alongside them.

The training isn't an add on. Implementations rarely fail on capability.  They fail on adoption. Someone gets a bad answer in week two, quietly stops using it, and by month three the whole thing has gone quiet. Teaching your team how to talk to it, and how to correct it when it's wrong, is why it's still running next year.

The four rungs on the homepage explain where most of the businesses I meet actually sit, and what climbing one looks like.

On being straight with you

I'm upfront with clients, including when it's uncomfortable. Not "perhaps".  If something's gone wrong on my side, you'll hear it from me before you hear it from anywhere else.

Concealment always ends in finger pointing, and it takes the relationship with it. I'd rather have the awkward conversation early.

The rest of it

If you run an allied health clinic, you'll notice two of those pointing at you. Clinicly AI is productised and sits close to your marketing. Defined services, allied health only, patient communications and lead follow-up.  Lumsden AI is bespoke and operational. Any service business, whole of business process mapping, coworkers running unattended across departments.
Plenty of clinics end up using both, and that's fine.

The business owners I sit down with rarely need another tool. They need one thing to
stop landing on their desk. Which one would you pick?