almoApproach
I start by training your team. That is also how I learn your business.
Most engagements open with a discovery phase you pay for and get nothing out of. Mine opens with a day your team gets value from, while I work out what's expensive to get wrong.
The triage
Three buckets, sorted by consequence
Annoying is not the same as expensive. I sort on what it costs you when the answer is confidently wrong.
01
Contained, low consequence
Your team owns it.
Work where a mistake is cheap and stays where it happened: drafting, summarising, first-pass research, the reformatting that eats an afternoon. You don't need me for this — paying a consultant to hold it forever is how AI budgets disappear.
You need your own people fluent enough to do it themselves, and to spot when a tool is confidently wrong. So this bucket is where I start: I train your team on it, then get out of the way.
02
High consequence
I own it.
Work where being wrong is expensive, hard to reverse, or lands in front of a customer or a regulator. Non-deterministic tools don't belong here without proof.
I build it, test it against the cases that carry that cost, and show you the evidence before anyone depends on the output — then maintain it as your processes and the models change. You can take ownership whenever you want it.
03
Not worth automating
Left alone, on purpose.
Work where the automation would cost more than the problem, break something that currently works, or replace judgement that's the actual value of the job.
This bucket is why the other two can be trusted: every hour spent automating something in here produces nothing, and it's where most wasted AI spend goes. I'm paid the same either way, which is the point.
In practice
How an engagement runs
First
The training day
Pitched to land with executives and analysts alike. They leave with real output from your own tools, and I learn how the work actually runs.
Out of that
The three buckets, in writing
The sort comes from the people doing the work, not the people describing it. You get all three, including the one I'm not charging you to build.
Then
I take bucket two
I build it, test it against the cases where being wrong costs you, and show you the evidence up front.
Whenever you want
You take it back
Everything I build is yours to own, in your systems, with no lock-in.
The part everyone skips
AI isn't a technology problem, it's a human one.
Frightened people don't experiment, and they won't tell you which parts of their job swallow most of their week — so you automate the visible trivia and land back where you started.
That's why training comes first, and why it has to reach every tier: mandates nobody follows from the top, private workarounds nobody's checked from the bottom.
There's a measured price too: people whose AI-generated work colleagues have to unpick get rated as less capable and less trustworthy.
Still not sure which bucket your work falls into?
There's no deck and no obligation. You leave with my read on where AI is worth your money, including "you don't need this yet" if that's the truth.