The framework is Dharmesh Shah's. The part where I tried it in my own business, that's the story.
Here's something that changed how I work this week, and I think it can change yours. Dharmesh Shah, the co-founder of HubSpot, writes a newsletter called simple.ai. This week's issue was titled "How to Write Your First AI Loop." I read it twice.
The line that stopped me came from Boris Cherny, the engineer who created Claude Code:
"I don't prompt Claude anymore. I write loops, and the loops do the work. My job is to write loops."Boris Cherny, quoted in Dharmesh Shah's newsletter
Most of us use AI like a vending machine. Type a request, get an answer, type the next one. That's prompting. A loop is different, and the whole framework here is Dharmesh's. A loop has three parts.
His sharpest point: there's a loop that runs and a loop that learns. A loop that runs does the same thing every day. A loop that learns has a feedback signal wired in, so it gets better every time. Aim for that one.
Here's where I come in. I'm not a developer. I think in outcomes, not code. So when I read this, my first thought wasn't "nice theory." It was: could I actually build loops for my own businesses? My recruiting firm, my sales-training startup, this show. Real work, today, not someday.
So I sat down with Claude and gave it one instruction. No code, just plain English.
That was the whole thing. Read this. Apply it to me. Five per business.
Twenty loops. Five for each of my four businesses. A loop to find and score candidates. A loop to keep my content on-message. A loop to turn every episode into something AI engines will actually quote. Each one had that same shape: a goal, a way to grade itself, and a line where I still decide.
Then I did the part most people skip. I picked one and actually ran it. I chose a loop to reach back out to deals that had gone quiet. I won't get into the names. Here's the part that got me.
The loop drafted the messages. But I'd given it a boundary: check my real email history before anything is final. And when it did that, it caught that its own first drafts were wrong. It had assumed a backstory that didn't match what actually happened with those people. So it rewrote them, accurately, before I ever saw a bad version.
That's the whole point. The loop didn't just do the work. It checked itself against reality and fixed its own mistake. The judgment, "verify before it's ready," that part was mine. The loop carried it out.
Here's the one that really shows it off, because you can watch every single pass. I run a loop to write the title and hook for each piece of the show. Same three parts, and the feedback signal is baked right in.
The five-point rule it grades against: leads with viewer value, one clear promise, curiosity without clickbait, under about 60 characters, and it kills my banned framing ("watch what I built / I tried / my…"). That last rule is the feedback signal. It's what makes this a loop that learns my taste, not just one that runs.
The juicy part is watching a weak title climb to a strong one. Three real ones from this very episode:
Same shape as the first loop: it does the cranking, the judgment stays mine. It generated, scored itself against my rule, rewrote everything under 9, and handed me ten finished titles to choose from. See all ten title loops, scored and rewritten →
Take one thing you already use AI for. Drafting emails, prepping for a meeting, summarizing a call. Write down three things.
That's a loop. The keystroke work goes away. The judgment work stays with you. That's the good news.
Again, the framework is Dharmesh Shah's, from his simple.ai newsletter "How to Write Your First AI Loop." Go read it. Then come build one. I did, and I'm not a developer.