Structured Thinking

Responsibly integrating AI systems doesn’t mean leaving tools to learn “on their own” and at the expense of potential clients. It means understanding and identifying where the decision layers exist and how to intentionally direct, evaluate, and oversee them. The goal isn't to create a system that can never drift. The goal is to understand where drift can occur, establish appropriate guardrails, and maintain enough human oversight to recognize and correct it when it does.

The goal is not simply to give someone a governance checklist, but to develop a user whose evaluation behaviors become a natural part of AI interaction because they understand why those behaviors are necessary.

AI may have much of the internet, but it doesn’t have you. The value of service businesses, and usually entrepreneurs in general, has always been the knowledge, experience, and judgment learned over the years of the people behind the service. That’s the real value the client is paying for.

A bread machine can make bread, but it cannot teach someone how to bake. The same principle applies to AI. Why true AI literacy has less to do with mastering tools and more to do with mastering how you think.

The problem with the race to get to the result is that it cuts out all the intentional interaction needed with AI to learn how to evaluate those results. Workflows should be something that develop naturally — not something forced. Users running similar scenarios through AI multiple times begin to recognize patterns and effects that different interactions have on outputs. This is essential to what we call ‘operational literacy with AI.’

Making quality, intentional training available for the workforce is no longer a luxury we can afford to ignore. Asking members of your organization or team for all the “cool” workflows and systems without directly teaching them the stepping stones required to get there is not only unfair to them, it is also dangerous for your organization.

This past weekend, I conducted training for a group of business leaders, and we started with a prompt I had designed for instructional purposes. The question came up almost immediately: “Aren’t we all going to get the same answer?” Everyone was using the same tool and the same prompt, so it was a fair question. Given how often AI is framed as a matter of finding the “right” prompt, the expectation of consistent output makes sense. In case anyone reading may not know, they we

There is no shortage of information about AI and how to use it successfully online. The challenge a lot of professionals face is finding useful, accurate information that isn’t clickbait or someone trying to sell a quick, easy fix. Let’s be clear from the start. AI is not a fast, easy fix. It takes work and time. In the beginning, it usually takes more time than most people expect. The benefit is that if you’re willing to invest that effort up front, the return tends to grow

When someone is told to “figure it out,” they are not just learning a tool. They are trying to develop a way of thinking. Without structure, most people default to surface-level use. They try a few prompts, get mixed results, and struggle to connect the tool to their actual work. Over time, they either abandon it or use it in limited, inconsistent ways.

It is often said that when Michelangelo was asked how he created David, he explained that he simply removed everything that was not David. As someone who does not consider himself particularly artistic, I have always found that idea fascinating. I can hardly open a full fridge and figure out what to make for dinner, let alone look at a block of granite and see a work of art. The mind truly is a powerful thing. The masterpiece was not created in the traditional sense; it was r