The Art of Giving Orders to Machines

June 10, 2025

In partnership with

You sit at your computer, staring at a blank prompt box. The cursor blinks. Waiting. You type: "Write me a good email."

The AI spits back something generic. Corporate speak. Lifeless.

You try again: "Write me a compelling email that converts." Better. But still not right.

You're not alone. Every founder, every startup, every company trying to build with AI hits this same wall.

The technology is incredible. The results are... inconsistent.

Here's what nobody tells you: prompting an AI isn't coding. It's management.

Think about it. When you hire someone new, you don't just say "do good work." You give them context. You explain the role.

You break down the steps. You show them examples of what great looks like. Same with AI. The best companies aren't just using better models.

They're having better conversations. Take customer support. Bad prompt: "Answer customer questions." Good prompt: "You're a customer service manager.

Your job is to solve problems quickly while making customers feel heard. Here's how to think through each case..."

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The difference? Six pages of detailed instructions. Role definition. Step-by-step processes. Specific examples. Escape hatches for when things go wrong. It's not about being smarter. It's about being clearer.

The companies winning with AI aren't the ones with the best engineers. They're the ones who understand their customers so deeply they can teach a machine to think like them. They sit with the tractor sales manager in Nebraska.

They watch the FBI agent process cases. They learn the weird, specific ways real people actually work. Then they come back and encode that knowledge into prompts that work. The secret isn't in the technology. It's in the translation.

From human insight to machine instruction. From watching someone work to teaching software how to work. The future belongs to companies who can bridge that gap. Who can turn messy, human workflows into precise, digital processes.

The tools feel primitive right now. Like coding in 1995. But that's exactly why the opportunity is so big.

We're not just writing prompts. We're writing the future of work.