May 10, 2026

  • Choosing To Be Mindful in the Age of AI

    In the age of AI, we’re obsessed with better answers. But the real leverage may come from better questions.

    It’s easier to solve someone else’s problem than your own. Why? Because your biases, emotions, and problem-solving frameworks become part of the problem. Likewise, your blind spots likely go unexamined when you’re both the observer and the subject.

    As an entrepreneur, I strive to be objective about the decisions I make. Towards that goal, using key performance indicators, getting different perspectives from trusted advisors, and relying on tried-and-true decision frameworks all help. 

    Mindfulness as a Decision Framework

    Combining all three creates a form of “mindfulness” that comes from dispassionately observing from a perspective of all perspectives.

    That almost-indifferent, objective approach is also where exponential technologies like AI excel. They amplify intelligence by helping make better decisions, take smarter actions, and continually improve performance. 

    In 2021, I shot a video about mindfulness and the future of AI. I think it has held up remarkably well.

    via YouTube

    When I shot this video, AI was still relatively limited.

    In just a few years, the technology has come so far. When I originally published the video, I suggested that:

    The future of AI will likely be based on swarm intelligence, where many specialist components communicate, coordinate, and collaborate to view a situation more objectively, better evaluate the possibilities, and determine the best outcome in a dynamic and adaptable way that adds a layer of objectivity and nuance to decision-making.

    Five years later, that prediction has largely materialized. Multi-agent frameworks, retrieval-augmented generation, and tool-using LLMs now orchestrate specialized components to tackle complex problems. The architecture isn’t identical to biological swarm intelligence, but the principle holds: better decisions emerge from coordinated, specialized perspectives, and from understanding the actual purpose of your tools.

    What Hasn’t Changed

    AI is a powerful solution for a seemingly infinite number of problems. But, much like the internet, it’s easy to get distracted by shiny objects, flashy intrusions, or compelling answers.

    It is important to stay mindful and diligent as you apply AI and AI agents to your business.

    Many of my friends are getting excited about these tools, and they’re using them for countless capabilities, but they’re not necessarily doing a good job of evaluating whether they should be.

    Sometimes, you shouldn’t even be looking for the right answer, you should be looking for the right question.

    The Importance of Better Questions

    One of the lessons I teach to our younger employees is that an answer is not THE answer. It’s intellectually lazy to think you’re done simply because you come up with a solution. There are often many ways to solve a problem, and the goal is to determine which yields the best results.

    Even if you find THE answer, it is likely only THE answer temporarily. It is a step in the right direction that buys you time to learn, improve, and re-evaluate.

    Mindfulness comes from slowing down, stepping back, and looking at something from multiple perspectives, and AI can be a powerful tool for that when used intentionally. It can help us explore different viewpoints, challenge assumptions, and think more broadly.

    But the greatest benefit of AI may not be in generating better answers. More often, it comes from helping us ask better questions.

    Used mindfully, AI becomes less of a shortcut to conclusions and more of a tool for deeper thinking.

    Recently, I’ve started using AI to sharpen my questions, and it’s changing the way I approach problems. At first, that sounds abstract, but in practice it forces a very different kind of thinking. Instead of immediately searching for conclusions, you start asking what actually makes a question “better” in the first place. How do you move from a vague sense of uncertainty to a question precise enough to reveal something useful?

    When I’m evaluating a project now, I rarely ask AI something broad like, “Is this a good opportunity?” Questions like that usually produce predictable answers. Instead, I use AI to pressure-test my own thinking. I’ll ask it to identify the assumptions underneath the idea, explore what would have to be true for the project to fail, or point out the questions I haven’t considered yet. The process feels less like outsourcing thought and more like refining it.

    That shift — from answer-seeking to question-sharpening — has changed how I handle ambiguity and make decisions. It has also changed what I consider trustworthy. I’ve started building what I think of as a “question pattern library”: prompts and frameworks that consistently help add structure to messy situations. Some questions help clarify the framing by forcing you to define the real decision being made rather than reacting to surface-level symptoms. Others establish criteria, helping determine how success should actually be measured before debating solutions. And some are designed to expose bottlenecks by identifying which assumption, if proven false, would completely change the next step.

    Over time, I’ve realized these questions work best when they build on each other. At important checkpoints, I’ll often run through a simple sequence: What became clearer? What does this change? Why does it matter? What’s the next best move? The answers themselves matter less than the way the questions force clearer thinking.

    The more I use AI this way, the more I think its greatest value may not be generating better answers at all. Used mindfully, its real strength is helping us examine our own thinking more carefully. Better questions create better distinctions, and better distinctions usually lead to better judgment. So before asking AI for an answer this week, it may be worth asking it to help you frame a better question first. You might discover that the most valuable part of the interaction isn’t the response, but the thinking process that led to it.

  • A Look at the Global Economy in 2026

    We live in interesting times!

    So whether you are a glass-half-full or a glass-half-empty person, you have plenty of ammunition.

    The news cycle is designed to monetize fear, so it reliably amplifies what is fragile, broken, or uncertain. But if you shift focus from the headlines to the data, the global economy in 2026 looks far more resilient (and more opportunity-rich) than most people realize.

    In this week’s commentary, I’ll walk through a few key charts that cut through the noise and highlight where growth, risk, and leverage are actually shifting.

    For example, you can focus on the $100 trillion global debt … but you could also focus on how U.S. states’ GDPs compare to global GDPs.

    The $126 Trillion Scoreboard

    The world economy is slated to reach $126 trillion this year, with four countries accounting for over half of that. Who tops the list?

    The United States. As we have for over 100 years.

    The graphic below visualizes the global economy as a whole using IMF projections from the April 2026 World Economic Outlook, breaking down nearly 200 countries by their share of nominal GDP.

    Infographic showing just four countries generate roughly half of all economic activity worldwide.

    via visualcapitalist

    Just four countries generate roughly half of all economic activity worldwide (U.S. ~$32T, China ~$21T, Germany ~$5T, and Japan ~$4T ). That concentration of economic power is striking, but as we’ll see, size alone doesn’t tell you who’s winning the next decade.

    Size Doesn’t Equal Speed

    Among the four largest economies, China is expected to lead with a projected 4.4% real growth in 2026, while the U.S. is anticipated to grow a solid 2.3%. In contrast, Germany and Japan (which have experienced years of stagnation) are forecast to grow only around 0.7–0.8%.

    China’s strong performance continues a trend observed over the past several decades, despite facing challenges such as a demographic slowdown and an ongoing property sector crisis.

    Once you look past the largest economies, there are real opportunities in large, fast‑growing markets across Asia. For example, India, at roughly $4.2 trillion in GDP, and Indonesia, at $1.5 trillion, are on track to play a much bigger role in the global order.

    With a forecasted 6.6% growth rate in 2026, India could surpass the United Kingdom and potentially Japan by 2028 — driven by a demographic dividend, expanding services exports, and rapidly maturing digital infrastructure. For entrepreneurs and investors, that shift isn’t just trivia; it should inform where you place bets, partner, and build.

    Tariffs, Trade, and the Debt Behind It All

    Since early 2025, high-tariff policies implemented by the U.S. have caused downward revisions in growth forecasts for several economies, especially in North America.

    Canada and Mexico are especially exposed. With U.S.-Canada relations strained and negotiations over a trilateral trade agreement progressing slowly, the North American economic bloc faces increasing uncertainty.

    via visualcapitalist

    After World War II, it took over 60 years for U.S. debt to reach $10 trillion. The next $10 trillion took 9 years to reach following the 2008 financial crisis. In the 2020s, pandemic spending compressed the interval to just five years.

    By the 2050s, each additional $10 trillion could take just one to two years.

    That is under modest assumptions, with no new wars, no recessions, and manageable interest rates. Even so, debt projections still reach $182 trillion by 2056. For context, we’re at about $39 Trillion now.

    That data comes from the Congressional Budget Office (CBO) and the White House as of March 2026.

    So is the Glass Half Full or Half Empty?

    The real story of the global economy isn’t just told with GDP rankings. While America and China dominate those numbers, it’s clear the landscape is changing.

    Traditional economic metrics might become less relevant in a world where regional conflicts, supply chain dynamics, and technological innovation can reshape global power dynamics overnight.

    In the longer term, birth rates and the growth of middle-class infrastructure are strong predictors of what lies ahead. That’s part of why we see so much growth in India and Indonesia.

    GDP alone doesn’t measure what truly matters in the modern global economy.

    The Variable That Changes Everything

    Looking beyond traditional economic metrics, I believe artificial intelligence will emerge as one of the most critical factors driving power, progress, and wealth creation in the coming years. It’s likely to become both the most coveted resource and the capability we’ll most actively seek to deny our adversaries.

    Economies that combine large markets, strong digital infrastructure, and responsive regulatory environments will be positioned to capture outsized gains. Those that lag on talent, compute, or data governance may see their nominal GDP grow while their strategic leverage erodes.

    Obviously, AI is something I think about and write about in many other articles, so even though I won’t add a detailed section here, it’s worth noting that AI is going to change the relative weight and importance of many other things in increasingly exponential ways.

    In conclusion, the scoreboard is changing on three fronts at once: where growth lives, how policy shapes risk, and how AI alters productivity and power. If you’re allocating capital or building companies in this environment, the advantage goes to leaders who can see beyond the fear‑driven headlines to where the real leverage is emerging.

    Onwards!

  • Here Are Some Links For Your Weekly Reading – May 10, 2026

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