Level: Foundational Category: AI System Categories This term introduces the major categories of AI systems and what they are designed to do in practical use. 🪄 Simple Definition: A Large Language Model (LLM) is an AI system trained to understand, interpret, and generate human language. 🌟 Expanded Definition: LLMs are built using deep learning and trained on massive collections of text. This enables them to recognize patterns, understand context, and produce writing that feels natural and human-like. Examples include ChatGPT, Claude, Gemini, and Grok.LLMs can summarize documents, answer questions, write content, support research, and assist in decision-making.They don’t “think” like people—they generate responses based on statistical patterns learned during training. ⚡ In Action: You type: “Draft a follow-up message for customers who missed their service appointment.” The LLM produces a polished, professional message in seconds. 💡 Pro Tip: Clear instructions produce stronger results. Define the role, purpose, tone, and audience to guide the model effectively. This term is part of the Classroom Course - AI Fundamentals

✨ The Quirk: If you ask ChatGPT what time it is, it can’t actually tell you — even though it feels like it should. There’s no built-in awareness of the current clock or moment. What’s Going On: - ChatGPT doesn’t have a live clock or real-time awareness by default. - It generates responses based on patterns, not the current moment. - Time only exists for the model if you explicitly provide it. - So asking “What time is it?” is a bit like asking a calculator what day it is. 🔧 What To Do If You See It: - Don’t assume AI knows “now” — give it the time when it matters. - Include the date, time, or timeframe directly in your prompt. - Try this prompt: “It’s currently 3:15 PM on Tuesday. Based on that, what should I do next?” Why This Matters: This quirk is a reminder that AI is context-driven, not situationally aware. The clearer the context you provide, the smarter it feels. This one genuinely surprised me. For some reason, I assumed “knowing the time” was basic. Turns out, it’s not. Does this surprise you too? Or is this something you already knew? Try asking ChatGPT the time, and see what response you get.

There’s a lot of discussion about how overwhelming AI can feel—especially with the sheer breadth of products and services, and the speed at which new revisions and updates keep rolling out. For many people, it creates a constant sense of playing catch-up. So whether you’re just starting out, or you feel like you’re simply keeping pace, the best place to start—or recenter—is prompting. Prompting is the foundation of working with AI. It’s the way we express intent, provide context, and guide direction when interacting with intelligent systems. Not as a trick. Not as a hack. But as the underlying mechanism that determines whether AI feels helpful—or frustrating. 💎 Why Prompting Comes First 💎 Every AI interaction follows the same basic loop: You give input. AI responds. You react, refine, or redirect. No matter the tool, that loop doesn’t change. If your intent is unclear, the output will be too. If your context is thin, the response will be shallow. If your direction is vague, results will feel inconsistent. Better tools don’t fix that. Clear prompting does. 💎 Prompting Is About Thinking, Not Typing 💎 It’s easy to think prompting is about what words you use. It’s not. It’s about: - Knowing what you’re actually trying to achieve - Providing enough context for AI to work intelligently - Setting boundaries and expectations - Being willing to refine instead of restarting The strongest prompts usually come from clearer thinking—not longer instructions. 💎 Why This Transfers Across Tools 💎 This is why prompting shows up everywhere. Once you learn how to: - Frame a request clearly - Ask follow-up questions - Adjust direction through iteration You’ll notice something interesting happen. New AI tools start to feel familiar. Different interfaces. Different outputs. Same underlying conversation. That’s not coincidence. That’s the foundation at work. 💎 The Diamond in the Rough 💎 Prompting is often taken for granted. Because it feels simple, people assume it’s basic.

We were deep in conversation, driving to Florida. Talking at some length about the 2026 strategy for AI Bits & Pieces. What stays. What evolves. What new ideas might want a little room to grow. After a lot of back and forth, there was a pause. The kind that means someone is thinking, not finished. Then Michael started thinking out loud — as he does. I was listening. Or so I thought. Michael was reciting a finished thought — pulling together all the pieces of the conversation we’d just had about AI Bits & Pieces and its next chapter. Naturally, I answered. Quickly. Confidently. Like a spouse who’s been married a long time and knows the rhythm of these conversations. And then ChatGPT started talking. And then it just… stopped. Like, oh — sorry, go ahead. I remember thinking, "Why did it start talking?" Completely forgetting that Michael had ChatGPT set to voice mode to capture our thoughts and notes. So, I kept going. Added a little more context. And then, suddenly, ChatGPT jumped back in and essentially said, “Yes, I agree with Michele.” 😳 I looked at Michael with that "what just happened" face. That’s when it clicked. He wasn’t asking me. He was asking "TARS" (yes, from *Interstellar*) — as Michael calls ChatGPT. And somehow, without meaning to, I had jumped into a three-way conversation… and the AI wasn’t waiting at all — more like a cat behind the couch, ready to spring. I didn’t know whether to laugh or shake my head in bewilderment. Probably both 😂 And I thought to myself — "damn… it’s already here." Woven quietly into our conversations, our thinking, our planning. It made me wonder — where else is AI showing up that I’m not even consciously aware of? We’re just going on about our day — the kind of conversation I’ve had a thousand times with my partner of 27 years — and it’s already inserting itself into our lives. And maybe that’s how the biggest changes arrive — already settled in, before we realize we’ve adjusted. And that's AI in Real Life...

Real quick question — what email platform do you mostly use? I’m shaping upcoming classroom content and want the examples to line up with how you really work, not just theory. Thanks for taking a second to vote 👍