Generative AI as “Augmented” — Not “Artificial Intelligence”

Let’s get one thing straight: Large Language Models (LLMs) aren’t magic. They’re powerful, sure. Sometimes even jaw-droppingly good. But they’re not little digital brains. They don’t understand you the way your friend or coworker might. And that’s okay—as long as we use them the right way.

That’s why it’s time we stop thinking of AI as “artificial intelligence” and start calling it what it really is: augmented intelligence.  Augmenting your intelligence.

Prediction Does Not Equal Understanding

Here’s how LLMs like ChatGPT are trained and work at their core: they predict the next word in a sentence.

That’s it. One word at a time. Think about that for a minute.

They’ve been trained on oceans of text—books, websites, conversations—and they learn to guess what word should come next, based on what came before. The more text they see, the better they get at making those guesses sound human.

But they don’t know what they’re saying. There’s no true awareness or comprehension under the hood. No self-awareness means LLMs can sound confident and still be completely wrong and not know it. Ask an LLM for a made-up fact? It might serve it up like its gospel truth.

That’s a huge reason to shift your mindset: this tool isn’t an all-knowing oracle. It’s more like a very fast autocomplete that’s extremely good at mimicking intelligent conversation.

So why use it? Because it can supercharge your thinking—when you stay in the driver’s seat.

LLMs Are Brainstorming Machines

One thing LLMs do extremely well? Helping you think in new directions.

Need ten different names for your startup in a few seconds? Done.

Stuck on a slide for a presentation? Ask the LLM to suggest alternate layouts or phrasing.

Writing a blog post about AI (wink wink)? Use it to create an outline, rephrase clunky sentences, or play devil’s advocate.

LLMs are idea engines. They’re great at breaking writer’s block, generating drafts, and helping you consider options you hadn’t thought of. They don’t care if you throw out 90% of what they suggest. They’ll keep generating ideas as long as you keep asking.

The key is: you bring the judgment and creativity. The LLM brings the volume and variety. That’s the power of augmented intelligence.

Smarter Prompting = Better Collaboration

The real magic happens when you stop treating the AI like a search engine and start treating it like a teammate.

Let’s talk prompting strategies.

1. Flipped Interaction: Let the LLM Ask You

Instead of always feeding the AI questions, try this: present the AI with a task and ask it to ask you questions first to help it improve its answer.

Say you’re working on a pitch deck. Ask the LLM: “Before helping me, ask five clarifying questions to better understand my audience and goals.”

This gives you space to clarify your own thinking. And it gives the model more to work with. The results? Way more relevant and focused help.

2. Chain-of-Thought Prompting

Sometimes you want the LLM to show its work.

Instead of asking, “What’s the best option here?” say, “Walk through your reasoning step-by-step before choosing the best option.”

This chain-of-thought style prompting helps you catch logic gaps or errors, and sometimes it even helps the model reason better (wild, but true).

3. Use It as a Critic

Trying to improve a presentation, resume, or article? Ask the LLM to switch roles: “Act like a skeptical reviewer. What are the weak points here?”

This flips the dynamic from creator to editor. You stay in control, but now you have a fast, tireless partner giving you feedback without ego.

You can also layer roles and personas: ask it to be a curious customer, a board member, or even a college professor. Each perspective gives you a fresh lens on your work.

Augment, Don’t Abdicate

The real risk with LLMs is forgetting that you’re still the thinker.

These tools don’t replace your creativity, intuition, or domain expertise. But they can amplify them.

They help you move faster, generate more ideas, and refine your work with less friction. But they need your judgment. They need your context. They need your why.

So next time you open a chat window with an AI tool, don’t expect it to be “artificially intelligent.” That phrase sets the wrong expectations and leads to lazy use.

Instead, treat it like an augmentation of your intelligence. Like a sounding board, a collaborator, or a thought accelerator. Because that’s when the real magic happens.