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

If you’ve followed the series so far, you’ve probably noticed something subtle. We didn’t spend much time chasing tools. We didn’t rank models. We didn’t optimize for features. And that was intentional. Because beneath every AI application, every interface, and every update, there’s a simpler truth: What actually compounds is not the tool. It’s how you work with it. That’s what this series has really been about. 💎 The Full Arc 1️⃣ Prompting Brings Clarity Everything starts with intent. When you can clearly express what you’re trying to do—and why—AI stops guessing and starts helping. 2️⃣ Iteration Builds Momentum Progress doesn’t come from perfect prompts. It comes from refining, nudging, and steering without starting over. Iteration turns effort into motion. 3️⃣ Fluency Reduces Friction At a certain point, the back-and-forth stops feeling heavy. You spend less time explaining and more time thinking. The interaction gets lighter. 4️⃣ Intuition Guides Action You begin to trust the flow. You know what to ask next. You adjust naturally. The conversation supports your thinking instead of interrupting it. 5️⃣ Application Multiplies Impact Once fluency is in place, it carries. Across tools. Across use cases. Across domains. You’re no longer learning AI one app at a time—you’re applying a skill. 💎 Why This Matters AI changes quickly. Tools come and go. Interfaces evolve. But fluency endures. When you build capability at the level of prompting, iteration, and intuition, new applications stop feeling intimidating. They feel familiar—even when they’re powerful. That’s when AI shifts from something you keep up with to something you use. 💎 The Quiet Unlock The biggest shift isn’t technical. It’s psychological. You stop asking: “Am I using the right tool?” And start asking: “What do I want to create or understand next?” That’s when AI becomes a life skill. Not because you mastered everything— but because you know how to begin. ✨ AI Bits & Pieces — helping people and businesses adopt AI with confidence.

Hello everyone — I wanted to share a quick video to walk through some recent changes we’ve made to the site. As the community has grown, it became clear that we needed a better way to organize content for members with different starting points. That’s where the four groups come in: - AI Curious - AI Enthusiast - Agency - Enterprise. In the video, I show how posts and classroom content are now organized by group so it’s easier to find what’s most relevant to you. That said, nothing here is meant to be restrictive. You’re encouraged to explore outside your group if you’re curious — sometimes that perspective is the most valuable part. This update is really about making the community easier to navigate as we approach 500 members, while keeping the spirit of open learning and shared experience intact. Thanks again for being here and for spending your time in this community. The questions, feedback, and quiet participation all matter more than you might realize. I genuinely appreciate every member of this community, and I’m glad we’re building this together. Respectfully. @Michael Wacht

Once prompting is clear, iteration is second nature, and intuition guides your work -- something important becomes obvious. You’re no longer learning AI tools one by one. You’re applying a skill. And that skill carries. 💎 Fluency Transfers, Even When the Interface Changes At this point, opening a new AI-powered application feels less intimidating. Before long, you’re comfortable exploring new apps and making them useful with very little friction. That’s because you already know how to: - Clarify intent - Provide useful context - Steer outcomes through iteration - Adjust tone and direction naturally So even when the interface looks different, the interaction feels familiar. The surface changes. The fluency does not. 💎 What This Looks Like in Real Use With the same underlying skills, you can move comfortably across many types of applications, including: - Image tools for fast concepts and visual exploration - Website builders like Lovable, where prompts shape pages without code - Research tools like NotebookLM, where good questions turn notes into insight - Discovery tools like Perplexity, where fluency sharpens questions into cited answers - Writing and planning tools that support thinking, not just output - Low-code and no-code platforms that turn intent into working solutions - Even advanced tools—like Claude Code—come within reach. Not because they’re simple, but because you already know how to think, ask, and iterate. These aren’t separate skills to master. They’re different places to apply the same fluency. 💎 Why This Changes the Experience of AI This is the moment when AI stops feeling fragmented. You’re no longer asking: “How do I learn this application?” You’re asking: “What do I want to create or understand here?” That shift replaces hesitation with confidence. Not because you know every feature—but because you trust how you work. 💎 There Is No Single AI Path Because people apply AI differently, progress doesn’t follow a universal sequence.

Once people understand that prompting is the foundation, the next realization is often harder to make: Iteration is not intuitive. Most of us are trained to start over when something isn’t right. We rewrite from scratch. We clear the page. We try again. That habit carries directly into how we work with AI. So instead of refining, we create a new prompt—often one that looks completely different—hoping the next output will feel like a fresh start. Ironically, that’s still iteration. The difference is that it’s happening implicitly, not intentionally. 💎 Why Iteration Feels Counterintuitive 💎 What feels like “starting over” is usually just a new instruction layered on top of the same idea. We change wording. We shift tone. We add detail. The output may look completely different, but the real change happened in the instruction, not in abandoning the process. Once you see this, something clicks: You don’t need to reset the conversation. You need to direct it. Iteration with AI isn’t about replacing prompts. It’s about shaping outcomes—often with fewer words, not more. 💎 The Feedback Loop That Actually Matters 💎 AI isn’t static software. It responds. That means the real value doesn’t come from a single instruction—it comes from the feedback loop: You ask. AI responds. You adjust. AI improves. That loop is where clarity forms. If a response is close but not quite right, that’s not failure—it’s information. It tells you exactly what to refine next. 💎 Small Adjustments, Big Impact 💎 Iteration often looks deceptively simple: - “That’s close—make it more concise.” - “Same structure, different audience.” - “Expand only this section.” - “Keep the idea, change the tone.” - “Apply this somewhere else.” These aren’t new prompts. They’re course corrections. Over time, those small adjustments compound into noticeably better outcomes. This is why experienced users don’t restart—they steer. 💎 Where the Diamond Gets Cut 💎 Prompting may be the diamond—but iteration is how it’s refined.