By Tyler Drenon | UniteNews Contributing Writer
Everyone wants to “learn AI” right now, which is sort of like saying you want to “learn electricity.” It’s too broad to be useful. The trick isn’t to learn AI; it’s to learn how to work with it, direct it, and build things that use it. That means separating noise from knowledge. Let’s start with reality: there’s no single path to becoming “AI skilled.” The field fractures into at least three broad domains: users, builders, and architects. If you’re a user, your job isn’t to code models, it’s to command them. Learn prompt engineering, not as a parlor trick, but as a discipline: precision, context, and iteration. Use ChatGPT, Claude, and open-source models. Try chaining them with tools like LM Studio or Ollama. The best way to learn is to break things, ask absurd questions, test boundaries, and reverse-engineer why the model answers the way it does. If you’re a builder, you don’t need a PhD in math, but you do need to understand what the core concepts and why they work. Build something small, like a chatbot, a summarizer, or a local RAG app, then optimize it. Deploying a janky prototype teaches more than any YouTube course.
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