What Hundreds of Hours of AI Training Actually Taught Me

Over the past two years I've put hundreds and hundreds of hours into formal AI training. Accelerators, masterminds, certification sprints, cohorts. The full list is on my credentials page. I paid for all of it, showed up for all of it, and did the reps while running a 25-person company.

People ask if it was worth it. Yes. But not for the reasons you'd guess.

Lesson 1: The Tools Are Temporary. The Patterns Aren't.

A tool I learned in month one was replaced by something better before month three. That kept happening. If the training had only taught tools, it would already be worthless.

What survived every tool change was the same handful of patterns. Break the work into steps a machine can verify. Give the model everything it needs to know before asking for output. Check the work. Keep a human on the calls that matter.

The pattern is the same every time. The logo on the tool is not.

Lesson 2: Context Beats Cleverness

Everyone starts out obsessed with prompt wording, hunting for magic phrases. The real gains came from somewhere else entirely: what the AI knows about your business before you ask it anything.

Our agents work because they read our canon. Our pricing. Our voice. How our client base is structured. What our rules are. A clever prompt with no context is a party trick. A plain prompt with deep context is an employee.

That flipped how I spend my time. I write less prompt and more documentation. The documentation compounds.

Lesson 3: Agents Need Rails, Not Leashes

The difference between a demo and production is what happens when the agent is wrong. And it will be wrong.

So everything we run has rails. Verification steps. Quality gates that block bad output instead of hoping someone catches it. Kill switches. A human between the agent and anything that leaves the building.

I learned this by breaking things, which is the expensive way. Learn it from this paragraph instead.

Lesson 4: The Last 20% Is Plumbing

Here's what the course sales page won't tell you: the demo is the easy part. Real automation is auth tokens, scheduling, error handling, and the job that silently stops running at 6 a.m. on a Tuesday.

Nobody teaches that part in a webinar. You learn it by shipping something, watching it fail quietly, and building the alarm that catches it next time. Production scars are the actual curriculum.

What This Means If You're an Operator

You don't need hundreds of hours to start. You need one real problem and the stubbornness to automate it end to end.

My operating principle has always been simple: figure it out. The training gave me vocabulary and shortcuts. The figuring is still the job.

The window here favors operators, not technologists. The people who know the work can now build the thing. That's new, and most of my industry hasn't noticed yet.

Questions I Get Asked

Is formal AI training worth it for business operators?

Yes, if you do the reps. The certificates matter less than the hours spent building. Training buys you vocabulary and shortcuts; the value shows up when you point what you learned at your own workflows.

How many hours of AI training do you need to get started?

Far fewer than I put in. You need one real problem from your own business and enough tool fluency to automate it end to end. Start there and let the problem pull the learning.

What should operators learn first, prompting or automation tools?

Neither, exactly. Start by documenting how your business actually works: pricing, rules, voice, structure. That context is what makes any prompt or automation tool produce work you can use.

I write about what I'm building at Axiom and here on this site. If you're deciding whether to invest your own hours, ask me what I'd skip. The list is long.