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).

I still remember my very first question to ChatGPT. I didn’t ask anything big or technical — I just typed, “Can you help me plan dinner for a few friends?” 🍽️ However, this first question was not without hesitation. Before typing those simple words, I called my daughter at college and asked, “Do you use ChatGPT?” After a few quick daughter–mommy jabs, she assured me I wasn’t going to break anything. I was skeptical, honestly. Curious, but also hoping it wouldn’t make me feel silly for not knowing where to start. But instead, it answered in a way that felt surprisingly easy to follow. ✨ And something in me softened. I realized I didn’t have to be an expert. I just had to be willing to try. 💛 If you’re new to all this, start anywhere. Even with ideas for entertaining friends and family. ❤️✨ Warmly, @Michele Wacht

We’re glad you’re here. This community is all about exploring the human side of AI — through bite-sized insights, quips, quirks, and practical stories you can use right away. 📝 We Encourage You to Post Often - Share wins, ask questions, and share interesting AI news. - Keep posts short, practical and easy to digest (think 60–second reads). - Use our Post Protocol: catchy title, strong hook, main insight, and a takeaway or prompt. - If you like, add your Author Footer (name, one-line tagline, and a url to LinkedIn). 🎓 Start Learning In the Classroom New here? A great place to begin is our Classroom Training. It’s designed to help you build AI literacy and fluency in small, practical bites you can use in conversations, projects, and learning. 🚀 Your First Step Introduce yourself below! Share a bit about who you are, how you’re using AI, or where you’re curious to start. 📌 Before You Post Please take a moment to review our Community Rules. Keeping things respectful, helpful, and light-hearted ensures everyone gets the most out of being here. We’re building this community one small piece at a time — and we’re glad you’re part of it.

Term: Response Level: Beginner Category: Core Concept 🪄 Simple Definition: A response is the answer the AI gives back after you type a prompt. 🌟 Expanded Definition: The response is the AI’s output — the text it generates based on your prompt. Responses can be short (a single fact) or long (a story, plan, or explanation). Since the AI is predicting the most likely next words, its responses can sound natural and human-like, though sometimes they may be off or inaccurate. ⚡ In Action: Prompt: “Write a haiku about the ocean. ”Response: The AI generates a three-line poem with 5-7-5 syllables. 💡 Pro Tip: If a response isn’t what you wanted, refine your prompt or ask the AI to try again. Think of it as a conversation where you guide the answer.

Yesterday I managed to get the full document into the vector database. Chunking, embeddings, the table setup in Supabase, everything worked. Yessss 😁 So today I want to take the next logical step. I want to actually talk to the vectorized data. Chat with it. Ask questions. See what kind of answers I get and how good the quality is, as far as I can judge at this point. This is the exciting part for me. Yesterday was all about structure and setup. Today is about seeing whether the whole pipeline actually produces meaningful results. If the retrieval works. If the embeddings make sense. If the answers stay close to the source. I know the answers won’t be perfect. But that is exactly why I’m doing this challenge. Now that the data is in the vector store, the next step is to create the retrieval flow in n8n, send a query, look at the matches, and see how the LLM responds with context. Let’s see how good or bad the first results will be. Time to experiment again.