🌀 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.

Quick update on the Claude Code learning journey I'm sharing in public. I've now completed three full self-guided lessons (15 terms/concepts total) in the Claude Code Hub, and everything is organized in one location for easy reference. 🔨 What's Been Covered So Far: Lesson 1: Getting Started with Claude Code Lesson 2: Core Interactions Lesson 3: What Claude Code Does 🔨 What Makes This Different I'm not waiting until I've "mastered" Claude Code to share what I'm learning. I'm documenting the journey in real time — the concepts, the commands, the lessons learned, and yes, the mistakes too. This isn't a polished tutorial series. It's a shared learning experience. And the community has been incredible — experienced Claude Code users jumping in with corrections, clarifications, and real-world tips that make the content better for everyone. 🔨 Access the Claude Code Hub Claude Code Hub - AI Terms & Posts

Welcome to the Out of The Box Series — where I test how far curiosity and AI can take me in 30, 60, or 90 minutes, using today’s best no-code and low-code tools. No setup. No training. Just pure exploration — right out of the box. 🎬 This Episode: ElevenLabs 🕒 Time Limit: 30 Minutes 📂 Category: AI Voice & Audio Creation What Is ElevenLabs? ElevenLabs is a tool that reads written text out loud using realistic-sounding AI voices. It’s often used to turn scripts, notes, or explanations into audio so people can hear information instead of just reading it. For this test, I had ChatGPT generate a short draft script for a brand-new video I am creating that is focused on an emerging shift many people are just starting to notice; the move from SEO (Search Engine Optimization) to AEO (Answer Engine Optimization). I started by testing two sort scripts, just to see how things work: - 🎙️ Audio Test #1: ElevenLabs default voice: Click to hear it - 🎧 Audio Test #2: ElevenLabs IVC (Instant Voice Cloning): Click to hear it Then I created a draft script for the video using ChatGPT: - 🎧 Audio Test #3: ElevenLabs IVC (Instant Voice Cloning): Click to hear it - Note: IVC required 10 seconds of my voice being recorded to provide the audio in a close representation of my voice. For this session there was no major editing tricks, no audio engineering - Just exploration. 🚀 Within 30 minutes, I created: - A complete video script written by ChatGPT - Three audio recordings using two different voice approaches (demo, and IVC) - The first draft of the audio for an upcoming video. Voice plays a big role, as most people realize. Thanks to ElevenLabs it is now accessible to the AI enthusiast and professional.

AI Bits & Pieces just launched a new training module for the AI Curious. You’re noticing how things that once felt familiar — writing, planning, searching, deciding — are now being reshaped in real time by AI. Not just a disruption.A clear evolution. AI is becoming a life skill, the same way search, email, and spreadsheets once did. This isn’t about being technical. It’s about understanding how AI can amplify your productivity by leveraging what you already have — your creativity. That’s where this community begins. AI Bits & Pieces — helping people and businesses adopt AI with confidence. Go to the Classroom to start your AI journey with confidence: AI Curious

After learning how to prompt clearly and iterate effectively, a natural question emerges: Does it matter which LLM I use if I’m iterating well? In the short run, the honest answer is no. If you’re clear in your intent and willing to refine direction, most modern LLMs will get you where you need to go. Prompting and iteration do a lot of the heavy lifting early on. That’s why many people experience an initial breakthrough and think, “Okay, I’ve got this.” And they do. At first. 💎 Why Iteration Levels the Field Early When you’re iterating well, you’re doing a few important things: - Clarifying what you actually want - Responding to output instead of restarting - Adjusting direction in small, intentional steps Those behaviors transfer. They work across LLMs because the interaction pattern is the same: input → response → refinement. In that phase, differences between LLMs fade into the background. You’re building skill, not dependency. 💎 When Fit Begins to Show Up As AI becomes something you use regularly—not occasionally—another shift starts to happen. You’re no longer experimenting. You’re working. And that’s when fit begins to show up. Not in dramatic ways In small ones that compound over time. You notice how an LLM responds to follow-ups. How much structure it assumes. How easily you can steer it without over-explaining. Tone and writing style are often where this becomes most obvious. Some people gravitate toward Claude because it feels more measured, structured, and editorial. Others prefer ChatGPT because it feels more conversational, adaptive, and easy to steer through quick iteration. Neither is better. They simply feel different to work with. And once AI becomes part of your daily rhythm, those differences start to matter. To be clear, this isn’t about specialty capabilities like coding, image creation, or domain-specific features. It’s about how naturally an LLM mirrors: - Your tone - Your writing style - The way you think through ideas