I had a moment this week that genuinely caught me off guard. I took a piece of writing I wasn’t happy with, moved it over to Claude expecting a softer, more polished take… and instead got something I didn’t expect at all. Claude swore. This video leans into the funny side of AI — the moments that catch you off guard and make you laugh. At the same time, it hints at something bigger: how quickly these systems are developing tone, personality, and presence. Curious if you’ve seen moments like this too.

ChatGPT seems like it could chat forever. Ask one question, then another, then another… it never runs out of responses. Or does it? Ever notice how sometimes ChatGPT slows down, forgets something you just said, or suddenly decides to draft the world’s most perfect email from scratch? And the longer you go, the stranger it gets. First it drops small details, then it starts mixing things up, and eventually it’s like a late-night storyteller making things up just to keep the show going. 🤯 That’s not your imagination — it’s memory limits. A chat only holds so much, and once it overflows, the seams start to show. The Quirk 🌀 We’re the same way. Ever tell a story that started clear but by the end you forgot your own point? ChatGPT just gets there faster. The Takeaway 👉 ChatGPT can go on forever — but if forever is contained within a single chat, it usually gets weird. The Anecdote That’s where Projects come in. Instead of stuffing everything into one never-ending chat, Projects let you split things into context-based threads — all under the same umbrella. Learn How to Use Projects to Keep ChatGPT Focused https://www.skool.com/ai-bits-and-pieces/projects-the-easiest-way-to-keep-chatgpt-focused?p=c6707d52 Written by @Michael Wacht 🔗View LinkedIn Profile Founder of AI & Data Strategies — helping people and businesses adopt AI with confidence.

🌀 The Quirk: When a prompt sounds authoritative, AI often mirrors that confidence — even if the answer itself is a best guess. 🌀What’s Going On: - AI is trained to mirror tone as much as intent. - Confident prompts signal “this is established knowledge.” - The model fills in missing context with the most likely answer. - Fluency can hide uncertainty, especially with new tools or edge cases. 🌀 What To Do If You See It: - Ask the model to flag assumptions before answering. - Request uncertainty explicitly: “What might be wrong here?” - Reframe the prompt as exploratory, not declarative. 👉 Try these prompts: “Answer cautiously. If any part is a guess, say so.” “Answer cautiously. If you’re unsure about any part, say so.” “Answer cautiously. Identify any assumptions and note where certainty is low.” “Answer cautiously. Call out any guesses.” Why This Matters: AI confidence is a delivery style, not a truth signal. Knowing when to slow the model (LLM) down is part of real AI fluency. 🎯 AI Bits & Pieces — helping people and businesses adopt AI with confidence.

If you’ve ever stood in a petting room — surrounded by wagging tails and hopeful eyes — you already understand this. Because selecting a dog or LLM as a companion isn’t really about specs, scores, or comparison charts. It’s more like that moment when a dog finally chooses you. ❤️ We spend so much time obsessing over characteristics. Speed. Size. Capabilities. But for most of us, that’s just noise. These companions have become so endlessly adaptable. Whether we’re talking about abilities or temperament, what actually drives our choice isn’t a technical spreadsheet. It’s a feeling. Style. Comfort. An intuitive sense that this one fits. 🐶 Pedigree vs. Personality On paper, pedigree matters. Performance matters. But in real life, you don’t fall in love with lineage — you fall in love with temperament. One companion might be “smarter” on a leaderboard, but if its tone feels robotic, or it misses your humor, the connection breaks down. We gravitate toward the personality that matches our rhythm, our thinking style, and the way we work. ❤️ The Instant Connection There’s a moment when a dog rests its head on your knee — and you just know. With an LLM companion, that moment often happens within the first few interactions. It anticipates your next thought. Formats things exactly the way your brain wants to see them. Responds in a way that makes you pause and think, oh… this works. That’s the difference between something you have to manage and a companion that simply gets the assignment. 🐕 Growing Together The best companions learn your routines without a word being said. They know the difference between work mood and walking mood. With a LLM, over time, it learns your shorthand. Your preferences. Your voice. Eventually, switching your LLM starts to feel less like a software upgrade and more like starting over with a brand-new puppy. Exciting, yes. But also — a little heartbreaking. 🐾 Care and Feeding In the end, it’s simple. My companion gets me. Both my dog and my LLM.

I’m excited to share something special with our AI Bits & Pieces community, especially the AI-curious members of our community. 🥁 🚀 Starting this week, my wife Michele will be contributing a new series called AI in Real Life — a warm, honest look at what it actually feels like to learn and use AI from the perspective of an everyday, real-world user. ✨ AI in Real Life is for anyone who’s ever thought: “I’m curious… but where do I begin?” This series will follow her personal journey with ChatGPT and other AI tools as she explores how they show up in everyday life — conversations with family, planning and organizing, trying new ideas, and even navigating the hesitation many of us felt in the beginning. Each week, Michele will share a short story, a small discovery, or a real-life moment that brought AI into her world in a simple, human way. My hope is that her voice helps make this community feel even more welcoming for those who are just getting started. ________ 🕰️ By way of background, Michele (@Michele Wacht ) spent twenty years as an executive selling services to the automotive OEM industry. She came from a corporate marketing and sales background, achieving top salesperson status at her company for many years before stepping away eight years ago to prioritize our family and be fully present for our daughter during her teen years. Now that Emma is off to college and recently turned 21, Michele felt ready to re-engage. And to my delight, she decided to join AI Bits and Pieces in helping people understand the benefits of AI — not from the perspective of an engineer or a strategist, but from the vantage point of someone discovering her own curiosity and how AI fits in as a life skill. If you’ve read Michele’s writing — as I and many of her friends have — you know she has a gift for turning simple moments into meaningful reflections. She approaches AI the same way — with curiosity, humor, and a down-to-earth honesty that reminds us that learning something new doesn’t always start with confidence. Sometimes it starts with dinner plans for friends, a college-age daughter on speed dial, and a willingness to try (a preview of her first post).