If you’re new to the community — or you’re just starting to use (or trying to understand) ChatGPT and tools like it — this is the course for you. We’ve just added a new Classroom course: How LLMs Like ChatGPT Work This course is designed to help you understand what’s actually happening when you use ChatGPT, so you can stop guessing and start getting better results. The big idea is simple:👉 The more you understand how ChatGPT works, the better you can guide it with your prompts. What you’ll learn: - The building blocks behind ChatGPT and large language models (LLMs) - How prompts, responses, and conversation work together - Why ChatGPT answers the way it does — and why it sometimes sounds confident but gets things wrong - How this understanding helps you write clearer prompts and use AI more intentionally 📌 Quick Note: There are many LLMs similar to ChatGPT available today, like Gemini and Claude, which are covered in a separate course. In this course, we use ChatGPT illustratively to explain how LLMs work in practice. This course is: - Beginner-friendly - Plain English - Built for real-world use (not engineers) If you’ve ever wondered why ChatGPT responded the way it did — or how to steer it more effectively — this course will help.

Level: Foundational Category: Widely Known Types of AI This term is part of Level 1, which introduces the major types of AI people encounter in conversations about technology. Limited Memory AI bridges the gap between simple, rule-based systems and today’s more advanced learning models. 🪄 Simple Definition: Limited Memory AI can use recent information or past data to make better decisions, but it does not store long-term memories the way humans do. 🌟 Expanded Definition: - Most practical AI systems today fall into this category. Limited Memory AI models analyze historical data—such as images, sensor inputs, or user behavior—to improve predictions and actions. - Self-driving cars, fraud detection tools, recommendation engines, and many machine learning systems operate this way. - The “memory” is not human-like; it’s temporary or engineered. These systems learn from data patterns but do not form permanent memories or general understanding beyond what they were trained on. ⚡ In Action: A self-driving vehicle adjusts speed based on the movement of nearby cars. It uses real-time observations plus learned patterns from past data to decide how to respond. 💡 Pro Tip: When teaching AI, Limited Memory AI is a great example of how most real-world systems work. It shows people that AI doesn’t “remember” everything—it learns from data, acts in the moment, and resets.

We just updated and expanded one of our core classroom modules: AI Basics to Everyday Use — previously titled Widely Known AI. This newly revised version now provides a clearer, more structured path through Levels 1–4, covering: - The major types of AI - Key system categories - How modern AI models learn - Where AI shows up in everyday work This update reflects the needs of our growing community and sets the foundation for deeper learning across all future courses. If you haven’t reviewed the updated course yet, now is a great time to dive in, click here to check it out. Classroom content is updated weekly, so you’ll continue to see refinements, new pages, and expanded lessons designed to build real AI literacy — one practical concept at a time.

If benchmark charts make your eyes glaze over, you’re in the right place. Most people don’t need all the benchmarks — just the ones that actually change how an AI model feels when you use it. That’s why we’re launching a brand-new classroom this week: The Big 5 Benchmarks — Explained for Beginners. No jargon. No math. No research papers. Just simple, practical explanations of the five benchmarks that matter most when choosing or comparing AI models. Inside, you’ll learn what each benchmark really measures — each one includes a plain-English breakdown and real-world examples so you immediately see why it matters. Because when you know the right benchmarks, you stop guessing which model is better — and start choosing the model that fits the job. 💡 Takeaway Understanding the Big 5 benchmarks turns AI from mysterious to manageable — and helps you use the right model with confidence. Go to Classroom: Get Smarter LLMs Benchmark Stats Made Easy https://www.skool.com/ai-bits-and-pieces/classroom/fd2b30f7?md=79d6fd21074e45c5a88c54bf2389d67a

Day 5 – Pro Tip ⚡ How to Use the “Explain It Back to Me” Prompt Strategy - Before running the main instruction, simply add this one phrase at the end of your prompt: “Restate what I just asked in your own words before doing it.” - This catches misunderstandings early and ensures the model is fully aligned before it starts. Our newest classroom course is being released over the next 5-days. Each day, you’ll get one short, practical Pro Tip — designed to save you time, frustration, and confusion when using the world’s best Large Language Models (LLMs): Click on Classroom Link for complete 5-day multi-part course: https://www.skool.com/ai-bits-and-pieces/classroom/e870ce2c Classroom courses are written in multiple parts to help you build AI fluency at your own pace in 3-minute increments.