AI is all about prompting, but most people misunderstand what prompting actually is. Lately, I’ve been seeing posts that say some version of this:
- “If you’re just prompting AI, you’re doing it wrong”
- “Prompting isn’t real AI skill”
I understand what people are trying to say. But the way this gets framed often confuses people, because it suggests that prompting itself is shallow or misguided.
The problem isn’t prompting. The problem is prompting without understanding.
Prompting Is the Interface, Not the Shortcut
Prompting isn’t about typing a question and accepting the first response you get. It’s about:
- Explaining intent
- Setting constraints
- Defining what “good” looks like
- Refining until the output matches reality
That isn’t misuse. That’s interaction. In practice, prompting is just writing with feedback. The real test is whether you can recognize what’s missing or what doesn’t quite align, and then explain that clearly enough to redirect the tool. If you can’t do that, the issue isn’t the prompt. It’s that you don’t yet understand the problem deeply enough.
In 2026, the value of a prompt isn’t measured by the words you put in, but by your ability to audit what comes out. Without domain expertise, you aren’t really prompting, you’re reviewing output you don’t yet have the authority to fully validate.
Why Subject-Matter Expertise Changes Everything
This is why subject-matter experts get wildly different results from AI than novices. An expert doesn’t use AI to discover the problem. They already understand the problem and have scoped the solution, so they use AI to shape, test, and refine that solution faster.
This is where technical writers tend to have a headstart. For decades, we have sat in the 'messy middle' of architecture, prompting humans to extract structured truth from raw ideas. AI doesn't replace this skill, it simply removes the middleman. It requires the same iterative rigor, rephrasing for clarity and defining usable scope, but also applies it to a machine interface. If you’ve spent years translating SME intent into systems, you aren't just 'using AI, you’re exercising Strategic Intent at scale.
This is the shift from 'Prompt Engineer' to 'AI Architect.' The engineer focuses on the syntax of the request; the Architect focuses on the integrity of the solution. One is a task, and the other is leadership. AI doesn’t change the work. It exposes who already knows how to think clearly about scope and strategy.
From Theory to Practice
I put this architect mindset to the test when I built my own application. The challenge wasn’t the code or the infrastructure; it was the transfer of expertise. I’m not just building a tool, I’m encoding decades of documentation experience—the hard-won lessons of structure, hierarchy, and clarity—into a system that could act on my behalf.
I didn't treat the AI as a "creator." I treated it as an apprentice that needed a rigid framework to succeed. By defining the exact boundaries of what the system should not do, I was able to automate my own "Strategic Intent."
Because I understood the domain, I could spot the difference between a minor technical glitch and a fundamental breach of logic. I knew when the AI was hallucinating a feature versus correctly respecting the architectural scope I had set. This wasn't "prompting" in the casual sense, it was knowledge engineering. My decades in the "messy middle" of technical architecture allowed me to build a moat around the application that a non-expert simply wouldn’t know how to dig.
The Real “But” in the AI Conversation
So yes, AI is all about prompting, but prompting assumes judgment. It assumes the ability to say:
- “This is missing, and that’s okay.”
- “This is missing, and that’s a problem.”
Without that foundation, AI feels either magical or useless. With it, AI becomes leverage. The conversation shouldn’t be don’t just prompt. It should be learn how to explain the boundaries of what you know.
AI doesn’t eliminate the need for expertise. It makes the absence of it obvious. The real question isn’t whether you can prompt AI, it’s whether you have the domain authority to know when the AI has respected your boundaries—or when it has quietly replaced your strategy with its own averages.