Six Rules I Learned From a Year of Working With AI
Every post so far has been a story. This one is different.
People have started asking me a plainer question: okay, but how do you actually talk to it? Not the drama, just the method. So here it is — the six rules I actually learned, plus the real conversations behind them, mistakes included.
This isn’t a technique. It’s closer to an attitude, hammered into shape over a year of getting things wrong.
The six rules
1. Don’t take “it can’t be done” at face value. AI states limits with total confidence, and sometimes it’s simply wrong. Ask again. Ask differently. My biggest breakthrough came from a place AI had already declared impossible.
2. Ask for one thing at a time. Stack too many requests into one prompt and everything tangles. Break it small, get one piece working, then move to the next. It feels slower. It isn’t.
3. Make a copy before you let it touch anything. AI breaking something that used to work is more common than you’d think. Copy first. If it goes wrong, you have somewhere to go back to.
4. Write down what worked. Tell the AI the pattern that succeeded and it stops repeating the same mistake. Failures are worth keeping too — a list of dead ends is still an asset.
5. Keep the process simple. The same result through a tangled process costs more every time — more time, more money, more chances to break. Simple is cheaper and faster, almost always.
6. Say “I don’t know” out loud. Don’t perform expertise you don’t have. “I have no idea what this is, explain from zero” gets you a better answer than pretending you followed the first one.
What asking actually sounded like
No secret phrasing. Just plain description of what I wanted, admitting up front that I didn’t know the technical words for any of it.
“I want this cell to turn red if it’s bigger than that cell, but I don’t know any code. Explain from the start.”
“I want one button. Press it, and the scattered rows line up by date. Is that possible?”
“This screen gets slow when a lot of people use it at once. Walk me through why, and whether there’s a fix.”
That’s the whole trick. Say what you don’t know, describe what you want in ordinary words, and the AI meets you where you are.
Where AI actually got it wrong
Trust it. Just not blindly. These are real ones.
The fake limit. When an internal tool I’d built slowed to a crawl under real traffic, AI told me flatly: that’s just the limit of the server, nothing to be done. I couldn’t accept that answer, so I kept pushing on it, night after night. The real cause was somewhere else entirely — the tool re-fetched everything from scratch on every click instead of remembering what it just loaded. Fix that one thing, and the “hardware limit” evaporated. The limit wasn’t the server. It was not questioning the AI’s confidence.
The outdated screen. Setting up outside access for the first time, the steps AI described kept not matching what was actually on my screen. Its knowledge had a cutoff date, and the interface had moved on since. The fix was just telling it back: “here’s what I’m actually seeing now” — and it adjusted from there.
The thing it deleted. Early on, asking for one small fix would sometimes wipe out something else that had been working fine. That’s exactly why rule three exists. Even now, with much better tools, I still make the copy first. Old habit, still worth it.
The one-line version
Say what you don’t know honestly — but question “it can’t be done” one more time. And always make a copy before you touch anything.
Those three lines cost me the most, across an entire year, to actually learn.
A month from now, none of this will feel dramatic. You’ll just have one small tool sitting there that you built. That’s exactly where I started too — one small thing, which quietly turned into twenty-two.
Your first one is next. Go find the annoying thing.
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