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Issue #4: The Single Source of Truth

by Chris Hess
Oct 27, 2026
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Polished Perspectives

Issue #4 · October 27, 2026

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Issue #4 of Stop Being the System. Last time we talked about why you have to see what's going on before you try to grow it. This time we're going to address why a single source of truth starts with agreeing on what the words mean.

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Command Center

Same word, two numbers

I once worked with a company where marketing and sales kept reporting different lead numbers. Marketing generated leads and sales closed them, and the two counts never matched.

People had theories. Marketing was overcounting, with duplicates and the like. Sales was “lowballing” the number to pad their close rate.

Neither was true. Marketing counted anyone who gave us their email. Sales counted a lead once they'd had a meeting with them. Same word, two different things, and nobody had noticed.

It took someone in operations stepping back to see it.

A single source of truth isn't just one dashboard. It's one agreed definition of what counts.

Try this this week

Pick one number your team argues about. Ask two people who use it to write down, in one sentence, what counts. If the sentences don't match, you've found the problem.

 

AI Corner

Why AI doesn't actually think

When you ask AI a question, it feels like it's thinking it over. It isn't, at least not the way you do.

What it's doing is predicting. It looks at everything in front of it (that's the we learned about context, from last week) and works out what text is most likely to come next, one small piece at a time. It learned those patterns from a huge amount of writing.

That's why it can sound completely sure of itself and still be wrong. It's producing what sounds right. It isn't checking whether it is.

It's also why it's so good at drafting, summarizing and spotting patterns. Those are all pattern jobs.

So let it draft, but you decide.

 

Experiments Lab Notes

Talk it out first

Story time!

When I first heard about ChatGPT, I got excited about an idea. I built a site called Short Stories by AI, where a new children's story was written every day. It picked random pieces, like an elephant, or three friends on an adventure, and wrote a story from them.

After a few weeks, most of the stories had the same structure. The only way to get a different story was to give it more than a few words to work with. Once I did, the stories got better.

It works the same way in business. Everyone complains about AI slop but usually it just needs more context. I have a tool I built where you record answers to relevant questions out loud. It transcribes what you said and writes an article in your voice, from your words. A two, three or five minute thought becomes a solid article, post or story, because you're handing the AI real context about you and what you're answering.

This week's experiment: ask AI for a short post on something you know well, using one line. Then talk about the same thing for three minutes. Dictate it on your phone or use a tool like Wispr Flow, paste in the text, and ask for the same post. Compare the two.

 

Book Note

Traction

“Numbers cut through murky subjective communication between manager and direct reports.
Traction - Gino Wickman

Everyone has a number, and numbers settle what opinions can't. That only works if everyone is counting the same thing.

 

What I'm Working On

One dashboard, two different insides

AI makes building software way easier. But if you're not careful, you get something you didn't expect.

A while ago, I built a dashboard for a client by starting with nothing and building it out piece by piece, talking it through with AI. It worked really well, so I offered the same thing to another client.

For the second one, I took a shortcut. I took screenshots of the first and asked AI to build it the same way we built the other one. It turns out I knew what that meant and it decided it knew so it started working. The problem was I'd given it the output, not the context, so it built its own version behind the scenes that looked the same.

Both clients were happy, because on the front end it did exactly what they asked for. Underneath, the two handled sync and data manipulation very differently. When I tried to fix things I kept running into issues I'd never had on the other dashboard. I ended up rewriting most of the second one.

If you're going to build something more than once, give AI the steps, not just the result. The way I build dashboards now looks nothing like my first few. Don't be scared to try. Just don't expect the best version the first time.

 

Thanks for reading. Hit reply and tell me which section was most useful. I read every reply.

-- Chris-- Chris
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