We just crossed 400 members, and I want to take a moment to say thank you to everyone who’s joined AI Bits & Pieces and helped shape what this space is becoming.🎉 This community was built on a simple idea: ✨AI is now a life skill. The goal here isn’t to chase tools or trends. It’s to build real understanding and practical fluency. So AI can be applied thoughtfully in everyday life, work, and business. As the community continues to grow, you’ll see more relevant content as we learn more about member preferences. That said, content is only one part of what makes this community work. 🤝 Just as important are the contributors who consistently show up and share real work — including open build journeys like @Holger Peschke 30-day RAG build, and @Matthew Sutherland, who consistently adds deeper insight and context to our content. @Muskan Ahlawat and @Judith Vanegas also deserve recognition for their consistent encouragement and thoughtful engagement. 🏆 Community Leaderboard To recognize members who have made meaningful contributions through participation, learning, and engagement — thank you for showing up. 1. @Frank van Bokhorst 2. @Holger Peschke 3. @Muskan Ahlawat 4. @Matthew Sutherland 5. @Dena Dion 6. @Judith Vanegas 7. @Jason Hagen 8. @Dorota Mleczko 9. @Usman Mohammed 10. @Roger Richards And new contributors: @Glenn Marcus and @Reynoso Anubis for their in-depth posts and videos that inspire and encourage us pursue new AI goals and applications.

A 5-Part Series on Prompting, Iteration, and Finding Your Own AI Rhythm We talk a lot about AI tools— Models. Apps. Updates. But beneath all of it, there’s one thing that quietly connects almost everything in modern AI: 💎 Prompting. Not as a trick. Not as a hack. But as the foundation—the way we communicate intent, context, and direction to AI. 💎 Prompting — often taken for granted, yet once refined, it unlocks real AI power. Over the next few posts, I’m kicking off a 5-part series called: 💎 Prompting: The Foundation for Unlocking Real AI Power We’ll explore: - Why prompting shows up everywhere, no matter the tool - Why iteration (not perfection) is the real superpower - Why some AI tools feel intuitive while others don’t - How prompting naturally enables us to expand from simple use to workflows and systems - And why there is no single “right” path when learning AI This series will reveal how such a simple act can unlock so much real capability. For the complete Series articles, visit: Series Hub ✨ AI Bits & Pieces — helping people and businesses adopt AI with confidence. Image created using “prompts” with ChatGPT.

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.

I was very excited to try the new Oakley Meta HSTN Transitions® AI Glasses. Short Review: A Strong Concept, Still Early Full Review: I recently spent time testing the Oakley Meta HSTN Transitions® AI glasses, and while I genuinely like the direction Meta and Oakley are heading, my overall takeaway is that this product still feels more like an early glimpse of the future than a finished, everyday device. This specific model combines Oakley’s sport-forward HSTN frame design with Transitions® lenses that automatically shift from clear to tinted based on lighting conditions. On paper, it sounds like an ideal blend of performance eyewear and AI-powered convenience. In real-world use, though, the experience is more nuanced. What These Glasses Are — and Aren’t: An important expectation to set up front: there is no visual display. Nothing appears in your field of view. All interaction happens through audio and voice commands. That design choice keeps the glasses lightweight and familiar, but it also defines the experience. These are not augmented reality glasses. They function more like hands-free AI-enabled audio glasses with cameras. Key Features: This model brings together several notable features: - Transitions® lenses that adapt automatically between indoor and outdoor lighting - Open-ear audio built into the frame for music, calls, and spoken responses - Hands-free voice control for asking questions, capturing photos or video, and triggering actions - Dual built-in cameras integrated into the frame - Sport-oriented Oakley design, clearly intended for outdoor and active use From a hardware perspective, this is a meaningful step forward compared to earlier Meta frames. The Oakley design finally makes the concept feel purposeful rather than experimental. What Works Well: The audio quality is better than expected, particularly outdoors. Music, calls, and spoken responses come through clearly without fully blocking ambient sound — an important detail for safety and awareness during activity.

So everyone's doing their 2026 goal-setting thing, right? I went a different route. I asked Claude: "What am I going to regret 12 months from now?" Here's the exact prompt I used: "It's December 2026. I'm looking back at this year. Analyze all our chats. Based on my current trajectory, what will I regret NOT doing? What will I wish I'd said no to? Be specific and brutally honest." And honestly? The feedback was... uncomfortable. 70% was spot-on enough that I had to sit with it 20% made me want to argue (which probably means it's hitting a nerve) 10% was off because Claude was missing some context The parts that really got me: "You're building everyone else's systems. When do you build the thing that's unmistakably YOURS?" "You're too available. That doesn't build wealth or freedom." "Stop saying yes to generic AI training workshops. You're positioning yourself as a commodity." Ouch. But also... true. Why I think this beats regular goal-setting Goals ask: "What do I want?" Regret asks: "What will I actually wish I'd done?" That second question? It cuts straight through all the BS we tell ourselves. It shows you what you're REALLY doing vs. what you think you're working toward. Try it yourself? → Use whatever AI you chat with most (Claude, ChatGPT, whatever) → If it has memory turned on, just paste the prompt → If not, give it some context first (screenshots of your calendar, recent project notes, whatever shows what you're actually up to) Not everything it says will be right. But the stuff that makes you defensive? That's the good stuff. Anyone else brave enough to try this? What did your AI roast you about? 👇