Most people will spend the next year trying to figure out where AI fits into their life and business… and they still won't come close to what we just did in 3 hours today. Day 1 of the AI Advantage Summit (click for replay!) was ELECTRIC! In just a few hours, we took on the biggest AI challenge so many are facing right now - too many tools, too much noise, not enough clarity - and we crushed it together. Now you know: - Why AI is here to empower us, not steal our futures - The 4 levers to achieve peak AI success - How to build your AI fluency (and go from Level 1 → Level 3) - Why you don’t need to be “techy” to learn AI And Tony Robbins’ session on the 3 different kinds of patterns you can model to thrive through any world shift?! UNFORGETTABLE! If you missed any part of it, you can watch the entire replay here (but it’s only up for a limited time so do not wait!!) When we go LIVE for Day 2, we will show you how AI can multiply your creativity, communication & marketing by transforming hours of effort into minutes. Plus we’ve got an amazing session from the AI Surfer, one of our most loved guests of all time… we’ve got a Harvard AI Happiness expert who’s going to transform your thinking… and so much more! So set your alarms now for 11am PT - don’t be late because you won’t want to miss a second!

The most successful people are not successful because they know everything. They are successful because they never stop learning. That is the difference. While most people want quick answers, high performers keep building better thinking. They stay curious. They ask better questions. They study what is changing. They refine how they work. They know that the faster the world moves, the more dangerous it is to rely on old assumptions. Learning keeps them sharp. It keeps them adaptable. It keeps them relevant. The people who keep growing are usually the ones who keep learning before they are forced to. They do not wait until the market changes, the tools evolve, or the results slow down. They stay in motion. They read, test, listen, observe, and apply. That is why they spot opportunities earlier and adjust faster than everyone else. Learning is not just knowledge. It is leverage. Every new skill shortens future struggle. Every new insight reduces trial and error. Every lesson compounds into faster decisions, better execution, and less wasted time. That is why the best people are not obsessed with learning for appearance. They are obsessed with it because it saves them time, helps them move with confidence, and keeps them from getting stuck. And here is the truth a lot of people miss. Success can make people comfortable. Comfort can make people lazy. And laziness in learning is often the beginning of irrelevance. The most successful people know they cannot afford to coast. They know yesterday’s strategy will not guarantee tomorrow’s results. So they keep sharpening their edge. They stay open. They stay humble. They stay willing to be a beginner again. That mindset is powerful. Because people who love learning do not panic when things change. They adapt. They figure it out. They learn the tool, study the shift, test the idea, and keep moving. While others feel threatened by change, they use learning to stay ahead of it. That is why they keep winning. In a world moving this fast, learning is no longer optional. It is part of staying valuable. It is part of protecting momentum. It is part of building a future where growth does not stall the moment the environment changes.

Being ahead in 2026 is no longer about simply using AI. That bar is too low. The real advantage now comes from using AI in a way that changes how work gets done, how fast decisions get made, and how much time gets reclaimed across the business. The conversation has moved beyond experimentation. Leading organizations are redesigning workflows around human and AI collaboration, increasing AI investment, and focusing on turning pilots into real operating leverage. That is the shift more people need to understand. In the early phase, being ahead meant trying the tools. Testing prompts. Seeing what was possible. In 2026, that is baseline behavior. The people and teams creating distance now are doing something more meaningful. They are building systems where AI reduces time-to-first-draft, shortens time-to-decision, lowers rework, and removes avoidable admin from the week. They are not just adopting AI. They are redesigning work around it. That is what makes this urgent. Because the gap is widening between those who casually use AI and those who operationalize it. Global AI adoption continued to rise through 2025, and employers increasingly expect AI-related capability, alongside analytical, creative, and adaptive human skills. At the same time, leaders are placing more weight on AI literacy, process redesign, and human oversight, not just access to tools. So what does it actually mean to be ahead? It means knowing where time is leaking and fixing that first. It means spotting the work that slows teams down, scattered planning, repetitive communication, slow handoffs, weak documentation, delayed decisions, and using AI to compress those cycle times. It means turning AI into a working layer inside the business, not a side tool people use occasionally when they remember. The real winners are not the ones generating the most content. They are the ones creating the most useful momentum. It also means keeping human judgment in the loop. That part matters even more now. Recent workplace research points to the need for selective delegation, calibrated reliance, and stronger human oversight as AI becomes more embedded in workflows. The advantage is not speed alone. It is speed with standards. Speed with context. Speed without creating expensive mistakes that have to be fixed later.

Everyone is talking about prompts. But prompts are not the real differentiator. The skill that will matter most in the next five years is judgment. Not just knowing how to use AI, but knowing when to use it, how to guide it, what to trust, what to question, and what to do next. That is the skill that will separate people who get real leverage from people who just create faster noise. This is where a lot of people get it wrong. They think the future belongs to the people who can type the cleverest prompts. It does not. Prompting is useful, but it is only the entry point. The real advantage goes to the person who can look at an AI output and instantly ask, Is this accurate? Is this relevant? Is this complete? Is this good enough for the moment? That is judgment. Because in the real world, speed without judgment creates rework. And rework is expensive. The winning skill is not blind adoption. It is disciplined discernment. It is knowing how to use AI to compress time-to-first-draft, reduce research time, and move faster on execution, while still applying human standards to the final decision. It is being able to collaborate with AI without outsourcing your thinking to it. For entrepreneurs, leaders, and teams, this changes the game. The people who stay relevant will not be the ones who use AI for everything. They will be the ones who use it with intention. They will know which tasks to automate, which decisions to slow down, and where human context still matters most. They will save time without lowering standards. They will move faster without becoming careless. That is what real leverage looks like. Over the next five years, tools will keep changing. Models will improve. Interfaces will get easier. The technical barrier will keep dropping. Which means the human edge becomes even more valuable. Judgment will be the multiplier. It protects quality. It reduces rework. It improves decision speed. It turns AI from a novelty into an advantage. The future will not reward people who simply use AI.

I know I’m probably slow to this realization but … This is something I learned in the last 2+ years from very successful people here in Skool that has made a huge difference. Focus is subtraction of everything that isn’t your goal and anything but the work to achieve it. From a business standpoint, putting all your efforts into solving a single, most leveraged problem and removing everything that doesn’t solve that single problem.