🌀 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.

AI reveals first super bowl ad. I better start studying to get ahead of the game! LOL

Built a terminal-based Prompt Builder for Claude Note before downloading: One thing to note — it requires zsh on macOS. The script uses zsh-specific syntax ((N) glob qualifiers, ${(s:,:)} splitting, print -r) and macOS-specific commands (pbcopy for clipboard, stat -f for file dates). If your on Linux or using bash, it won't work without modifications. Spent some time building a tool that solves a problem I kept running into - inconsistent prompts. Every time I'd start a Claude session, I was either forgetting key pieces (context, constraints, role) or spending too long thinking about structure before even getting to the actual work. So I built a Prompt Builder script that runs right in my terminal. Type prompt and it walks you through Anthropic's 9-element framework step by step - task, audience, tone, format, context, examples, role, reasoning, constraints. When you're done it copies the finished prompt to your clipboard with proper XML tags (which is how Anthropic recommends structuring prompts for best results). Just shipped v2.0 with templates (email, strategy, analysis, code review), a quick mode for when you just need task + role + constraints, a searchable prompt library so you can reload and tweak past prompts, and the ability to inject context from a file instead of typing it all out. Zero dependencies, pure shell script, works on any Mac terminal. Small tool but it's already changing how I work with Claude. Better inputs, better outputs. Every time.🔥

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