You don’t need to have the company name do all the work. That’s rarely necessary. In many cases, the name carries identity — and the tagline carries clarity. Together, they do far more than either one alone. Think of it this way. The name is the container. The tagline explains what’s inside. A strong tagline answers the question people almost always ask when they hear a company name: “What exactly do you do?” It clarifies your positioning. It reduces confusion. It strengthens your market signal. For example: AI & Data Strategies LLC Adopt AI with confidence. The name signals the lane. The tagline signals the outcome. Or take AI Bits & Pieces. The name carries story and identity. The tagline clarifies the tone and focus. AI Bits & Pieces Quick quips, quirks, and insights on people + AI Used together, they create signal. 🎯 What a Good Tagline Should Do A strong tagline usually clarifies at least one of three things: What you do Who you help What outcome you create For example: AI Education for Operators Agent Systems for Founders Adopt AI with confidence Short. Clear. Memorable. It shouldn’t feel like a paragraph. It should feel like positioning. 🎯 The Simple Test Look at your name and tagline together. If someone reads both and still asks, “So what exactly do you do?” It needs tightening. The goal isn’t cleverness. The goal is signal. 🎯 The Strategic Advantage A well-constructed name and tagline together give you: - Clarity - Story - Positioning - Flexibility - Longevity The name anchors identity. The tagline carries explanation. And explanation is where positioning lives. 🎯 Final Thought for the Series Naming isn’t about sounding innovative. It’s about signaling the kind of company you’re building. Some names carry story. Some names carry clarity. Some names optimize for search. Some names are built for longevity. The key is choosing intentionally. And then supporting that name with positioning that makes the signal clear. For example:

We were at dinner with a friend, @Mark Zayec, for his birthday. As we were exchanging AI stories he started telling us about an interaction he had with ChatGPT. For the past year, he’s been speaking small amounts of Italian and French into it — mostly to help himself learn. He’ll throw in things like, “Buongiornata mio fratello 🇮🇹.” On that day, ChatGPT responded in such a way he needed help with the interpretation? Therefore, he cut and pasted it into Google Translate to interpret it?” 🤔 I said, “Wait… so you spoke to ChatGPT in Italian instead of English, it responded in Italian… and then you needed it interpreted?” “And then you cut and pasted it into Google Translate to interpret it?” He chuckled, and said “yes.” Anticipating what was coming next. Without even thinking, I said, “Why didn’t you just ask it to interpret it in plain English?” We all looked at each other, and busted out laughing. 😂 This was a perfect illustration as to how we are still wired to think tool-to-tool instead of conversation-to-conversation. Even when we’re already inside the interface, our instinct is to jump somewhere else instead of just continuing the dialogue. You can say: “Translate that.” “Explain that in English.” “Rewrite that more simply.” It’s not about perfect prompting. Or jumping to another app or tool. It’s about realizing you can just keep talking. That’s AI in Real Life. Note: Animated comic created with Nano Banana 2.

I’m continually amazed at the questions I come up with and how quickly AI generates answers. The other night we went to dinner at Izzy's Fish & Oyster in downtown Fort Myers. We’ve been there several times, and each visit I notice a large, museum-like building kitty-corner across the street. I’d always wondered what it was, but I never caught the name because we usually head in the opposite direction. So I asked ChatGPT what building sits kitty-corner from Izzy’s in Fort Myers. Within seconds, I had my answer — and then some. It still amazes me how fast the responses come, and how often they’re spot on. At the same time, I sometimes wonder — especially with my ADD — whether getting answers so instantly is making my impatience worse. In a world where I already struggle to slow down, I’m not sure. But I have to admit, I still really like it.🙂

This is a follow-up to my original “Wine Glass Test” — a simple experiment that turned into something more interesting. After my first post, I received a thoughtful suggestion from @Matthew Sutherland. His advice was straightforward: Be more prescriptive. So I refined the prompt to this: “Create a glass of wine that is full, red wine. It needs to be at the brim, so not to run over, and not below the brim to show any space between the brim and the surface of the wine in the glass.” The image below is the direct result. And the result is telling. 🍷 What This Actually Proves This wasn’t about aesthetics. It was about bias and instruction. When I originally asked for a “full glass of wine,” the model produced what most restaurants would call full — but still left space at the top. That’s not an error. That’s statistical bias. The model leaned into the most common interpretation of “full.” When the instruction became extreme and structured, the behavior changed. It complied precisely. 🍷 There are two observations that I see with this test: 1️⃣ Prompting Is a Skill We often talk about model bias as if it’s a flaw. It’s not. It’s probability doing what probability does. My first prompt allowed the model to default to “standard pour.” The refined prompt removed ambiguity. By defining the boundary conditions — no gap, no overflow — the model had to break from its average tendency and execute exactly. That’s not luck. That’s instruction design. Prompting isn’t just writing a sentence. It’s mapping expectation into structure. And as Matthew pointed out, that skill develops iteratively. 2️⃣ Natural Language Still Has Friction The deeper takeaway isn’t that the model can create a perfectly full glass. It’s that everyday language is still ambiguous to it. When a human says “full glass of wine,” we infer intent through context. The model infers through probability. Those are not the same. For AI to feel seamless in daily life, we shouldn’t need to mathematically define “full.”

I’m on a new nutrition plan. More intention. More protein. Less randomness. And like most people trying to eat clean… I was staring at fat-free Greek yogurt thinking: “There has to be a better way.” So I asked ChatGPT for ideas. After a little back and forth, it suggested mixing Greek yogurt with Tabasco (Red Hot), cayenne, Celtic salt, and black pepper. Simple. Savory. Spicy. I added it to my chicken shawarma with a small pile of sticky rice. Holy smokes! It was creamy. It had heat. It didn’t taste like “diet food.” And when I ran the numbers? The macros looked good. • 200g chicken breast, no skin • 100g cooked rice • 100g fat-free Greek yogurt ~520 calories ~74g protein ~ Low fat ~ Controlled carbs That’s a serious, muscle-preserving bowl. But here’s the real point. AI didn’t cook the meal. It didn’t change my discipline. It didn’t magically make me healthy. It removed friction. It helped me turn something boring into something sustainable - and healthy. Nothing fancy. Nothing headline worthy Just making Wednesday night better. And when you’re building healthy habits, those small wins matter. ❤️ That’s AI in real life. Note: Thumbnail image created using ChatGPT "Create Image" feature.