Founder of Future Proof My Business. I evaluated AI for government and military organizations before I ever pointed it at a small business.
Years spent deciding whether high-stakes AI systems could actually be trusted to run without constant supervision. That's the same standard I hold every business I evaluate to now — including, eventually, my own.
Taylor has a technical background, spending years evaluating artificial intelligence systems inside government and military organizations — the kind of work where you redesign how a massive, rigid system actually functions, not just what it says on paper, and where getting the assessment wrong has real consequences. That work required a specific discipline: never trust a system's paperwork, only what it actually does under pressure.
She left to start her own business and apply that discipline somewhere with lower stakes. It turned out the discipline was the easy part to bring. Applying it to her own operation was the part nobody warns you about.
I spent years evaluating other people's AI. Then I built a business that needed the same scrutiny.
What was Taylor's background before Future Proof My Business?My job was to look at an AI system someone wanted to deploy inside a government or military organization and figure out whether it actually did what it claimed, where it would fail quietly, and what happened to the people relying on it when it did. Technical work, high stakes, zero tolerance for "it's probably fine."
Then I started my own company, and somehow none of that scrutiny made it to my own desk. Within two years I was the only person who knew how pricing worked, which client relationships needed a personal call, and where every process actually lived — which was almost entirely in my head.
I had spent years evaluating whether other people's systems could be trusted to run without constant supervision. I hadn't asked the same question about my own.
What forced the issue was a two-week consulting engagement that pulled me away and required me to hand my own business to someone else to run. Watching them try to operate it from my notes was the clearest diagnostic I'd ever run — on anything.
"I'd spent years asking whether other people's AI could be trusted to run without constant supervision. I'd never turned that question on my own business. Once I did, the answer was clear: no."
So I did to my own company what I used to do to a system under evaluation: mapped it, and instead of just looking for where I was personally filling a gap, I zeroed in on the high-volume, repetitive, monotonous work — the parts of the business running on pattern, not judgment — and started automating those.
AI turned out to be one tool in the redesign — not the redesign itself.
What did Taylor actually do about it?Once the business was mapped, most of what I found didn't need anything exotic — a shared document instead of my memory, a clear rule instead of my judgment call. But a specific slice of it was high-volume, repetitive work — the kind of pattern-based task that AI is actually good at: sorting incoming requests, drafting first-pass responses, flagging what needed a human.
The difference was sequence. I didn't start with "where should I add AI." I started with the system, found where the repetitive work actually lived, and only then asked which of it a tool could take off my plate. Most consultants sell that process backwards.
I mentioned what I'd found to another owner at an industry event — the same evaluation I used to run on government AI systems, applied to a business instead. She asked me to run it on hers. Word got around from there: her supplier, then a competitor of his, then people neither of us had ever met.
I still don't sell AI first, and most of what I do for a business in the first month has nothing to do with it. What I sell is the same evaluation discipline I built vetting AI systems before high-stakes deployment — applied by someone who isn't too close to the business to see what it's actually dependent on.
205 businesses later, the pattern holds. Different industries, different sizes, almost always the same handful of fragile points holding everything up.
To help small business owners build operations that don't depend on any one person — including them — so the business can grow without slowly consuming the life of the person who started it.
Not a bigger business for its own sake. A business that can survive a bad week.
A few things I'll say out loud that most consultants won't.
Most businesses don't have an AI problem. They have a basics problem.
By the time we've fixed how information moves through a business, "should we use AI for this" usually has an obvious, much smaller answer than anyone expected.
Modernizing isn't about adding tools. It's about removing dependencies.
A business that needs six new subscriptions to function isn't more modern — it's just fragile in a different, more expensive way.
If a consultant leads with the tool, they're selling themselves, not fixing your business.
The audit comes first because it has to. Anyone who skips it is guessing, and you're the one who pays for the guess.
You don't need to be the hero of your own business.
Being indispensable feels like value until the day you need a week off and find out it's actually a cage.
This doesn't take as long as you think.
Mapping my own business properly took a few weeks, not a year. Most owners overestimate the cost of starting and underestimate the cost of waiting.
If your business can't survive a bad week, you're exactly where I started.
Watching someone else try to run my business from my own notes didn't mean I'd built something worthless. It meant I'd built something fragile — the same mistake I used to find in organizations far bigger than mine, and fragile is fixable once someone actually maps it out.
If that's where you are right now, you're not behind. You're at the beginning of a problem that already has an answer.