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🧩 The AI Use Case Inventory: The Smallest Governance Move With the Biggest Payoff
Most organizations do not struggle with AI because they lack tools. They struggle because they lack visibility. When we cannot clearly see where AI is being used, what data it touches, and what decisions it influences, we cannot scale adoption confidently. We either freeze, or we let shadow usage spread until trust breaks. An AI use case inventory sounds unglamorous, but it is one of the highest leverage moves we can make. It turns AI from scattered experimentation into a managed capability. ------------- Context: Why AI Gets Messy Fast ------------- AI adoption often begins with good intentions. A team tests a tool for summarizing meetings. Another team uses AI to draft marketing copy. A leader asks for faster reporting. Someone finds an AI feature in an existing platform and switches it on. None of this feels risky in isolation. Then, a few months later, the organization is surprised. People cannot answer basic questions. Which teams are using AI. What tools are in play. Are we putting customer data into third-party systems. Are we relying on AI outputs in decisions that affect customers. Which workflows are automated. Who owns them. The problem is not that AI is uniquely chaotic. The problem is that AI is easy to adopt without coordination. It spreads through convenience. It hides inside everyday tools. It slips into workflows because it saves time, and then it becomes normal before anyone has defined standards. When that happens, leadership tends to react in one of two ways. We either clamp down and restrict everything, which kills momentum and creates resentment, or we ignore it and hope for the best, which creates silent risk. An inventory is the middle path. It does not require perfect policy. It requires honesty. It starts with one simple act: seeing reality clearly. ------------- Insight 1: You Cannot Govern What You Cannot See ------------- Governance often fails because it is built on assumptions. We write rules based on what we think is happening, not what is actually happening. AI makes this worse because usage is distributed and often informal.
🧩 The AI Use Case Inventory: The Smallest Governance Move With the Biggest Payoff
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The Difference Between Grinding… and Living on Purpose
I was up at 4:35am this morning… on a Sunday… diving head first into work. And the truth is — it didn’t feel like grinding at all. Because when you love what you’re building, when you know it’s stretching you as a man, when it’s tied to being in service to your family and making a real impact… the work hits different. It stops feeling like pressure. It starts feeling like purpose. I don’t get excited about being busy. I get excited about growing. About becoming more disciplined. More focused. More capable than I was yesterday. That’s what fuels me. Not the hours. Not the grind. The progress. So if you’re in a season where you’re putting in the reps — don’t just ask yourself how hard you’re working. Ask yourself who the work is helping you become. Because when the mission is bigger than you…even a 4:35am Sunday start feels like a privilege.
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Claude Interactive Responses, ChatGPT Ads Explained & More AI News You Can Use
This week, I show you how to use Claude's new Interactive Reponses, breaks down AI ads at the Superb Owl and how ads in ChatGPT work (for now), reviews our testing results comparing GPT-5.3-codex and Claude Opus 4.6, and way more. Enjoy!
✍️ Using AI Without Exploiting Creativity
AI can make us faster, but speed is not the same as integrity. If we want AI to strengthen our work and our reputation, we have to prove that we can use it without becoming careless with other people’s ideas, labour, and intellectual property. ------------- Context: The Quiet Tension Under AI Adoption ------------- Many teams feel two pressures at the same time. One pressure is competitive, we need to move faster, produce more, and keep up with a world where AI is raising output expectations. The other pressure is ethical and cultural, we do not want to become the kind of organization that treats creative work as disposable fuel. This tension shows up in everyday decisions. Should we feed a competitor’s article into a model to summarize it. Can we train internal systems on client documents? Is it okay to generate a “style match” for a brand voice that resembles a specific creator. Should we use AI to produce imagery that looks like an artist’s work? Often, people are not trying to do the wrong thing. They are trying to do the work and do it well, but the norms are unclear. Legal guidance can be complex and evolving, and people fall back on two unhelpful extremes. Either everything is fine because “AI does it,” or nothing is safe so we avoid AI entirely. Neither extreme builds confidence. The path forward is practical ethics, clear standards, repeatable habits, and respect for creators as a core value, not a compliance checkbox. We can use AI powerfully while still acting like the kind of team others want to trust. ------------- Insight 1: “Can We?” and “Should We?” Are Different Questions ------------- AI makes it easy to do things that used to require effort. That ease tempts us to treat capability as permission. But capability is not the same as legitimacy. The question is about technical possibilities. The question should be about impact, consent, and trust. Teams that ignore the should we question move fast in the short term and pay later in reputation, relationships, and internal culture.
✍️ Using AI Without Exploiting Creativity
AI Caricature Challenge
Caricature Challenge Post 💚 This evening I've seen at least 5 people posting their caricatures done by GPT. Couldn't help it. Had to join the fun. Now it's your turn! Create your caricature and post it in the comments below. Here's the prompt: "Create a caricature of me and my job based on everything you know about me" Let's see what AI thinks you look like! 👀 🍀 Batch
AI Caricature Challenge
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