In 2024, the customer service department at Klarna, the Swedish fintech company, completed a quiet revolution. The company announced that its AI assistant was now handling the work equivalent of 700 full-time customer service agents. The chatbot resolved two-thirds of customer inquiries in under two minutes, down from eleven minutes previously, with satisfaction ratings matching human agents. The company projected $40 million in annual profit improvement.¹ This wasn't automation in the traditional sense. This was something different. (An important postscript: In May 2025, Klarna reversed course, announcing plans to hire human customer service workers again. CEO Sebastian Siemiatkowski acknowledged that "quality of human support" had suffered and that the company's AI-focused path "wasn't the right one." The reversal is instructive, it reveals both the limitations of current AI and the relentless pressure to try again. We'll return to what Klarna's stumble tells us about the shape of this transition.)² --- The Familiar Script We've been through this before, or so the argument goes. Every technological revolution triggers the same cycle of panic and adaptation. In the early 1800s, the Luddites smashed textile machinery, fearing the machines would steal their livelihoods. By 1900, most Americans worked in agriculture; today, less than 2% do. Yet unemployment hasn't steadily climbed, it's fluctuated within a relatively narrow band for over a century. The economy adapted. New jobs emerged. Human ingenuity prevailed. The reassurances come from economists, technologists, and business leaders in predictable refrains: It's just a tool. It augments human capability. Yes, some jobs will change, but we'll create new ones. We always have. There's comfort in this narrative. It's backed by 200 years of evidence. It suggests that our economic anxieties, however real they feel, are ultimately misplaced, that we're once again mistaking transformation for catastrophe. But what if the pattern doesn't hold this time? What if the very thing that makes us confident, our long history of technological adaptation, is blinding us to a fundamentally different kind of disruption?

Okay, so you just joined this community and you're looking at Skool thinking... what now? How does this actually work? And how do some people seem to level up so fast? Here's the thing: Skool is different from other platforms. It's not about who posts the most or who has the flashiest content. It's about who actually helps people by getting likes. And that's honestly refreshing. Let me break down what I've learned (because I'm still figuring this out too, but these things have made a huge difference). How Skool Actually Works You've got levels. You see that number next to your name? That goes up when you contribute value to the community and people like what you do. Every time you post something helpful, answer a question, or engage meaningfully, you earn points when people like it. More points = higher level = more visibility in the community. But here's what really matters: the points are just a reflection of how much you're helping others. That's it. The system rewards generosity. The Leveling Up Secret (It's Not What You Think) I see people trying to "hack" their way up with tons of posts or constant comments. It doesn't work. You know what does? Show up to give, not to get. Answer questions from beginners even if they seem basic. Share what's working for you. Celebrate other people's wins. Drop a helpful resource when someone's stuck. Be the person you needed when you were starting out. Seriously, the people who rise fastest are the ones who forget about levels entirely and just focus on being genuinely helpful. What Great Content Looks Like Here You don't need to write novels or create complicated tutorials. Some of the best posts I've seen are simple: A quick win someone can try today. A tool that saved you hours (with how to use it). A prompt that actually works (copy and paste ready). A mistake you made and what you learned. An answer to a question you see asked repeatedly. Make it practical. Make it actionable. Make it beginner-friendly. That's the formula.

Ever wonder what the real difference is between the AI you use every day and the AI built by a company valued at nearly $100 billion? It's not magic. It's engineering. The internal "master prompt" for Anthropic's Claude just leaked, and for the first time, we have the exact blueprint for how they build, constrain, and direct their AI. It reveals that the secret to top-tier AI isn't about finding clever phrases; it's about engineering a complete system. This guide will deconstruct their entire strategy. We will break down the four core layers of their system, covering the WHAT, the WHY, and the HOW, so you can apply these billion-dollar principles to your own AI projects. SECTION 1: INTRODUCTION - THE PARADIGM SHIFT The leaked Anthropic prompt is one of the most significant learning opportunities for AI builders to date. It reveals a critical truth: advanced AI interaction is about systems engineering. The document is not a simple request; it's a comprehensive constitution that defines the AI's reality, its rules of engagement, and its operational logic. This training module will deconstruct the four core layers of this system. For each layer, we will analyze: WHAT it is: The core concept and its function within the prompt. WHY it's crucial: The strategic reason Anthropic engineered it this way and the problems it solves. HOW you can implement it: Practical, real-world examples for your own AI applications, automations, and agents. This guide is for builders. The goal is to move beyond basic prompting and start engineering robust, reliable, and powerful AI systems. SECTION 2: THE FOUNDATIONAL LAYER - IDENTITY AND RULES This is the bedrock of the entire system. It’s the first thing the AI processes and it sets the stage for everything that follows. WHAT IT IS The Foundational Layer explicitly defines the AI's identity, capabilities, knowledge boundaries, and immutable rules. It's a hard-coded "job description." Example from the prompt: "Claude is Claude Sonnet 4.5... Claude's knowledge cutoff date is the end of January 2025... Claude does not have the ability to view, generate, edit, manipulate or search for images..."

I'm writing this because I care deeply about this community. I see the incredible energy and passion you're all pouring into your work and education, and I want to make sure we are all on the smartest path forward. To do that, we need to have a serious, honest conversation. Many of us are competing against each other, trying to build a better SaaS, brand, product or agency. But that's the wrong competition. The real competition is the bullet train coming down the track: first AGI, and then ASI. The old way of making money online, selling your knowledge or skill, is dying. AGI will make knowledge arbitrage worthless because it will provide better, personalized plans for free and be able to build entire businesses in hours that will crush the competition on price and dev cycles. This means many of the AI businesses people are starting today have a built-in expiration date and the key is to be aware of this! THE DANGER ZONE: BUSINESSES THAT WILL FAIL If your business is on this list, don't panic. It’s not a failure. It's a signal that we need a strategic plan to pivot. You need to cash out on what you can before AGI takes all the cash. These models are built on a foundation that is about to crumble: 1. SaaS "Wrappers" and Automations: An app that's just a nice design on top of a basic AI function (like a caption writer, image creator, video creator, etc.). AGI will absorb these functions, making them pretty much free features. 2. Generic Content & SEO Agencies: AGI will produce unlimited content, making this a race to the bottom. 3. Broad-Topic Coaching/Courses: AGI will be the ultimate free, personal tutor. This is the hard truth. But it's also where our real strategy begins. OUR PIVOT PLAN: THE TEMPORARY WINDOW OF OPPORTUNITY We have a window of time between AGI becoming mainstream and ASI changing the world in ways we can't even comprehend. Our job is to use this window to build the resources we need now. The strategies below are not permanent solutions. ASI + Robots will eventually replace these too.