Capitalogix

Is AI Making You And Your Team Smarter?

At the core of Capitalogix’s existence is a commitment to systemization and automation. 

At first, the goal was to eliminate fear, greed, and discretionary mistakes from trading.

Over time, we’ve worked hard at making countless things easier. Much like math, we found that the best practice is to simplify complex processes before trying to automate them.

I’m surprised by how many times I have had the same realization ... Less is more.

Likewise, I’ve learned the hard way that a great strategy is useless if people don’t get it. That is part of the reason that frameworks are so important.

Ultimately, the process, the system, and the automation should follow this basic recipe if you want it to succeed:  Simple, Repeatable, Consistent, and Scalable.

Finding ways to automate sounds great. Increasing efficiency, effectiveness, and certainty sounds great, too  ... but, routines and habits become ruts and limits when they become un-measured, un-managed, or forgotten. 

A practical reality of increasing automation and constant progress is that it becomes increasingly important to have expiration dates on decisions, systems, components, and automations. We need to shine a light on things to make sure they still make sense or to determine whether we have a better option.

Freeing humans to create the most value sounds great, too ... but, as the pace of technological progress increases, the importance of freeing people to do more diminishes if they don’t actively rise to the occasion.

 

My Use of Technology

I got my first computer in 1984. It was the original Macintosh. That means I’ve been searching for and collecting technology tools to make business and life easier and better since the mid-80s.

It has been a long and winding road. These days,  it seems like I’m constantly looking for new ways to use AI in my life.

As you might guess, I “play” with a lot of tools. Of course, I think of it as research, discovery, and skill-building ... rather than playing. Why? Because it is something I’m good at, it produces value – and it gives me energy ... so, I make sure to reserve a place for it in my routine.

While most of what I explore doesn’t make it into my “real work” routine, I now have a toolbox of dozens of tools that I use for everything from research, notetaking, brainstorming, writing, and even relaxing. 

It’s a little embarrassing, but my most popular YouTube video is an explainer video on Dragon NaturallySpeaking from 13 years ago. It was (and still is) dictation software, but from a time before your phone gave you that capability. 

As I focus on systemization, I also have to focus on optimization. 

Using generative AI tools for daily research has fundamentally changed how I approach information gathering. What began as a meditative practice—slowly reading, digesting, and reflecting on material—has evolved into a faster, more expansive process. With AI, I can now scan and synthesize a much broader set of sources in far less time. The quality of the summaries and takeaways is high, enabling me to deliver more value to others. I can write better articles, share timely insights with fellow business owners, and keep my team well-informed. The impact on others has grown — but something subtle has shifted in my own learning.

The tradeoff is that if I’m not as careful as I used to be while doing the research, and I don’t engage with the material in the same way I did before. When I did the research manually, I was “chewing and swallowing” each idea, pausing to make connections, reflecting on implications, and wrestling with the nuance. That process was slower, but it etched ideas more deeply into memory.

As a result, my favorite articles of the week or month would show up in how I spoke on stage, what I wrote about, and how I worked through roadblocks with employees. Now, I notice that although I’m exposed to more information, it doesn’t have the same weight or impact. I’m consuming more at scale ... but retaining less, or perhaps less deeply (at least in my head). In contrast, I store much more, both in terms of quantity and depth, in my second brain (meaning, the digital repositories available for search when needed).

This brings up a fundamental distinction between knowledge storage and knowledge retrieval. Storage is about accumulating information, while retrieval is about quickly accessing and using the correct information at the right time. It requires digestion. 

It’s kind of like Amazon. Amazon has made buying books and getting them on my shelves easier than ever. I’ve got 1000s of books with answers to many of life’s questions. But, I’d estimate that I’ve really only read around half of the books I currently have on my shelf. The point is that having a book on your shelf with the answer to a problem is not the same as having the answers. 

I now have many thousands of articles in my Evernote. There are probably over a hundred of them about better “prompt engineering” or using “prompting techniques better”... but I can’t pretend that each article has made me better at those things. I have gotten better at thin-slicing and knowing what I want to store to improve the quality of the raw material I search for.

So now, I’m exploring how to maintain a balance. I still want to leverage AI’s value, while reintroducing a layer of slowness and reflection into the process. Maybe that means manually summarizing some articles. Maybe it means pausing to journal about what I’ve read, or discussing it with someone. The goal is not to abandon the efficiency — but to ensure that efficiency doesn’t come at the cost of depth.

The priority is making sure I’m optimizing on the right thing. It’s not progress if you’re taking steps in the wrong direction.

Let me know what you think about that ... or what you are doing that you think is worth sharing.

Onwards!

Choosing To Be More Human in the Age of AI

Last week, I asked, “What do you do when AI gets better than you?” One of the key takeaways from that post was that AI is freeing you up to be more human.

My son (who helped write it) said he wished we used more examples and stories that dealt with “the future of being human” rather than “the future of work”. So, we decided that would be the “seed” idea for this post.

It’s funny, but when I started to gather my thoughts about it ... I felt a rush of emotions. 

Emotions and Logic

Emotions have frustratingly little to do with logic. Humans are driven by impulse and often by those that don’t represent our best nature. History shows that we’re driven by fear, greed, scarcity, and self-preservation. And, truthfully, that’s all “human”. But humans are also beautiful, meaning-making machines ... and throughout our often messy history, we’ve done amazing things and somehow survived.

Appreciating Life

Watching my father die was a catalyst for me to appreciate life and living more than I did. I gave a TEDx talk about that and wrote articles about the time value of a life worth living. At the end of his life, it was clear that he appreciated things more (a family dinner, a kiss goodbye, the beauty of a sunset) and that he would have done almost anything for more time. Two hidden gifts came from that “scarcity”. The first gift was recognizing that we got to choose how much more “life” we got out of the last part of my dad’s life. The second gift was realizing that you don’t have to wait for the end of life to “live like you only have a year left”.  

Final Goodbye

I have another memory from his deathbed as well. He had been out of it for a while, and I was worried that I wouldn’t get a chance to say a final goodbye and to tell him how much I loved him. Luckily, he woke up, and we had a few final lucid moments together. He looked me straight in the eyes, told me how much he loved me, and then with a touch of humor said, “Okay, so tell me how this relates to Veritas ...” which was the original name of the company I was running at that time. His final message to me was a reminder that life is not really about work.

Looking Beyond Work

Transparently, I still look at the world through a lens and filter that too often focuses on work. Yet I also recognize and strive to pay attention to the deeper meanings beyond that.

Getting back to the point of the article, it is easy to see how AI relates to work ... yet, it might be more important to consider how AI is going to affect the rest of your life. 

 

 

In the last article, we discussed how Lee Sedol, one of the world’s top Go players, retired after losing to AlphaGo. When asked about it, Lee said, “Losing to AI, in a sense, meant my entire world was collapsing.” He also explained, “I could no longer enjoy the game. So, I retired.” 

While it’s certainly his right to retire, I think it might have been the wrong choice ... or, at least, not what I would have done in that situation.

If playing Go was his passion, it might have been better for him to change how he “keeps score” to focus on his progress, rather than the distance between him and what AI could do.

As long as you believe you can get better (and have hope for continued improvements), there are many ways to leverage the capabilities and opportunities that come from that.

Many people engage in sports or games even though they know they won’t become the greatest of all time. The same is true for almost any hobby or pursuit (whether it’s in art, literature, philosophy, craftsmanship, or other fields). There will always be someone or something that can do it better, faster, or more efficiently. However, that shouldn’t be the sole determinant of whether you get joy or energy from pursuing a path of getting better at what you want to excel at.

One of my core beliefs is that the changes coming to the world will free us up to be more human. That means we have to choose what to pursue.

What’s more human than pursuing something difficult? 

The Beauty of Passion

In a world increasingly shaped by AI’s precision and efficiency, choosing to do something purely out of passion becomes a powerful act of self-expression. When a machine can paint more photorealistically or compose music with perfect mathematical harmony, human creativity finds new purpose not in competing, but in conveying emotion, imperfection, and lived experience.

 

As we focus on growing businesses and changing the world, I think it’s easy to lose sight of the passion that first got us into business. 

I do the research and write this newsletter, not because I expect it to make me a ton of money, or because AI can’t do it ... but because I enjoy it, and it’s almost like meditation for me. 

My son plays rugby despite enduring countless injuries, significant financial cost, and realizing that it takes increasing amounts of his time to stay competitive. From a logical standpoint, it makes almost no sense for him to spend scarce resources or risk such extreme bodily harm in his 30s. But he’s passionate about rugby, enjoys playing it, and recognizes how it improves other parts of his life. It is an excellent example of the time value of a life worth living. He made a conscious choice that this is what it takes to be, do, and have what he values most.

The Power of Fun 

Artificial Intelligence is probably better than you at poker ... does that mean you shouldn’t have some friends over and try to win their money?

Does it mean you shouldn’t try to learn a new instrument or write a book?

We often undervalue fun because it doesn’t always produce measurable outcomes, but fun is not frivolous. It’s how we bond, relax, and explore parts of ourselves we can’t access through obligation or structure.

We intrinsically understand this. You don’t worry about being the best when you’re playing pick-up basketball or throwing a football with your son. You’re focused on creating memories and having fun. 

Joy doesn’t need justification. 

 

Striving To Be The Best

Ultimately, you have to be willing to lose to be the best. In every pursuit, there will always be someone ahead of you. Whether it’s a faster runner, a sharper mind, or a newer technology, I want to be the man in the arena. 

It is not the critic who counts; not the man who points out how the strong man stumbles, or where the doer of deeds could have done them better. The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood; who strives valiantly; who errs, who comes short again and again, because there is no effort without error and shortcoming; but who does actually strive to do the deeds; who knows the great enthusiasms, the great devotions; who spends himself in a worthy cause; who at the best knows in the end the triumph of high achievement, and who at the worst, if he fails, at least fails while daring greatly, so that his place shall never be with those cold and timid souls who neither know victory nor defeat. - Theodore Roosevelt, Citizenship in a Republic

The point has never been to be the best at everything ... but to strive for your best.

I’ve always believed the game isn’t over until I win, not because I can’t lose, but because the belief empowers me to get back up again. 

Being second best — or tenth, or just a beginner — doesn’t diminish your effort; it validates it. The climb matters, even if you never reach the summit. Humans are wired for persistence and purpose, not perfection. 

Humanity got where we are today because people weren’t happy with the status quo. They pursued greatness and innovation. Sometimes, what seems like failure ends up being the most significant success. 

AI is an incredible opportunity. It’s an opportunity to increase your productivity, to transform your business, and to redefine industries. It’s also an invitation to redefine your future and how you spend time. You can use it as an excuse to get smaller or bigger ... the power is in your perspective.

Hope that helps.

Are Your AI Fears Valid? What Experts Say

It's no surprise that there is often a disparity between what experts believe and what the average adult feels. It's even more pronounced in industries like AI that have been lambasted by science fiction and popular media.

Even just a few years ago, many of my advisors and friends told me to avoid using the term "AI" in our materials because they thought people would respond negatively to it. Back then, people expected AI to be artificial and clunky ... yet, somehow, it also reminded them of dystopian stories about AI Overlords and Terminators. An incompetent superpower is scary ... so is a competent superpower you can't trust!

As AI integrates more heavily into our everyday lives, people's hopes and concerns are intensifying... but should they be? 

Pew Research Center surveyed over 5,000 adults and 1,000 experts about their concerns related to AI. The infographic shows the difference in concern those groups had regarding specific issues.

 

Statista via VisualCapitalist

Half of experts (47%) report being more excited than concerned about AI’s future. Among U.S. adults, just 11% say the same.
Instead, 51% of adults say they’re more concerned than excited — more than triple the rate of experts (15%).

 

The most common—and well-founded—fears center on misinformation and the misappropriation of information. Experts and the average adult are in alignment here. 

I am consistently surprised by the lack of media literacy and skepticism demonstrated by otherwise intelligent people. Images and articles that scream "fake" or "AI" to me are shared virally and used to not only take advantage of the most susceptible but also to create dangerous echo chambers. 

Remember how bad phishing e-mails used to be, and how many of our elderly or disabled ended up giving money to a fake Prince from various random countries? Even my mother, an Ivy League-educated lawyer, couldn't help but click on some of these e-mails. Meanwhile, the quality of these attacks has risen exponentially.

And we're seeing the same thing now with AI. Not only are people falling for images, videos, and audio, but you also have the potential for custom apps and AI avatars that are fully focused on exploitation. 

AI Adoption Implications

Experts and the average adult have a significant disparity in beliefs about the long-term ramifications of AI adoption, such as potential isolation or job displacement. 

I'm curious, how concerned are you that AI will lead to fewer connections between people or job loss? 

I often say that technology adoption has very little to do with technology and much more to do with human nature.

That obviously includes AI adoption as well. 

Career growth often means abandoning an old role to take on something new and better. It's about delegating, outsourcing, or automating tasks so you can free up time to work on things that matter more.

It may sound like a joke, but I don't believe most people will lose jobs to AI. Instead, they'll lose jobs to people who use AI better. The future of work will be about amplifying human intelligence ... making better decisions, and taking smarter actions. If your job is about doing those things – and you don't use AI to do them – you will fall behind, and there will be consequences.

It's the same way that technology overtook farming. Technology didn't put people out of work, but it did force people to work differently.

Innovation has always created opportunity and prosperity in the long term. Jobs may look different, and some roles may be phased out, but new jobs will take their place. Think of it as tasks being automated, not jobs. 

Likewise, COVID is not why people have resisted returning to the office. COVID might have allowed them to work remotely in the first place, but their decision to resist going back to the office is a natural part of human nature.

When people found that technology enabled them to meet expectations without a commute, opportunities and possibilities expanded.

Some used the extra time to learn and grow, raising their expectations. Others used that time to rest or focus on other things. They're both choices, just with different consequences.

Choosing to Contract or Expand in the Age of AI 

AI presents us with a similar inflection point. I could have easily used AI to write this article much faster, and it certainly would have been easier in the short term. But what are the consequences of that choice?

While outreach and engagement are important, the primary benefit of writing a piece like this, for me, is to take the time and to go through the exercise of thinking about these issues ... what they mean, what they make possible, and how that impacts my sense of the future. That wouldn't happen if I didn't do it.  

I often say, "First bring order to chaos ... then wisdom comes from making finer distinctions." Doing work often entails embracing the chaos and making finer distinctions over time as you gain experience. With repetition, the quality of those results improves. As we increasingly rely on technology to do the work, to learn, and to grow, the technology learns and grows. If you fail to also learn and grow, it's not the technology's fault. It is a missed opportunity.

The same is true for connection. AI can help you connect better with yourself and others... or it can be another excuse to avoid connection.

You can now use an AI transcription service to record every word of an interaction, take notes, create a summary, and even highlight key insights. That sounds amazing! But far too many people become accustomed to the quality of that output and fail to think critically, make connections, or even read and process the information.

It could be argued that our society already has a connection problem (or an isolation epidemic), regardless of AI. Whether you blame it on social media, remote work, or COVID-19, for a long time, how we connect (and what we consider "connection") has been changing. However, many still have fulfilling lives despite the technology ... again, it's a choice. Do you use these vehicles to amplify your life, or are they a substitute and an excuse to justify failing to pursue connection in the real world?.

As said, actions have consequences ... and so do inactions.

I'm curious to hear your thoughts on these issues. Are you focused on the promise or the perils of AI?

The "Chart Of The Century" In 2025: A Look At Consumer Price Inflation

In an era of economic uncertainty, few visualizations have captured the attention of economists, policymakers, and everyday consumers like the “Chart of the Century” created and named by Mark Perry, an economics professor and AEI scholar. This chart tracks the dramatic shifts in consumer prices across various sectors of the American economy over a quarter-century, revealing patterns that challenge conventional wisdom about inflation, purchasing power, and economic well-being.

The most current version reports price increases from 2000 through the end of 2024 for 14 categories of goods and services, along with the average wage and overall Consumer Price Index. Here are the key findings.

 

• Wage growth has outpaced inflation by a significant margin (123.3% vs. 90%) from 2000 to 2024, resulting in a 16.1% increase in real purchasing power.
• Sharp divergence exists between sectors: Technology and tradable goods have become much cheaper, while healthcare, education, and childcare costs soared.
• Market competition and trade liberalization drive price decreases, while regulated markets and limited competition contribute to price increases.
• Despite objective improvements in purchasing power, many consumers still feel financial pressure due to changing consumption patterns and “quality of life creep”.
• Policy challenges remain in balancing regulation with market forces, particularly in essential services like healthcare and education.

 

Core Economic Metrics: The Big Picture

The foundation of this analysis rests on three critical metrics that provide context for all other price trends:

 

Metric	Change (2000-2024)
Consumer Price Index (CPI)	+90%
Average Hourly Income	+123.3%
Real Purchasing Power	+16.1%

 

From January 2000 to now, the CPI for All Items has increased by almost 90%. That is a big jump from its 59.6% level in 2019, when I first shared this chart.

 

These numbers tell a surprising story: despite widespread perceptions of economic hardship, Americans’ wages have grown significantly faster than inflation over these 24 years. This translates to a meaningful increase in real purchasing power – the ability to buy more goods and services with the same amount of work.

 

However, this aggregate picture masks dramatic variations across different categories of goods and services. Let’s explore these divergent trends.

 

The price of technology, electronics, and consumer goods — think toys and television sets — has tumbled over the past two decades. Why? These categories benefit from global competition, technological innovation, and manufacturing efficiencies.

Meanwhile, the cost of hospital stays, childcare, and college tuition, to name a few, have surged. Why? These sectors share important characteristics: they are typically non-tradable services (cannot be imported), operate in markets with limited competition, and are often subject to extensive regulation.

Below is Perry’s Chart of the Century. To help you interpret it better, lines above the overall inflation line have become functionally more expensive over time, and lines below the overall inflation line have become functionally less expensive. 

via Human Progress

For context, at the beginning of 2020, food, beverages, and housing were in line with inflation. They’ve now skyrocketed above inflation, which helps to explain the unease many households are feeling right now. College tuition and hospital services also have continued to rise relative to inflation over the past few years.

 

Market Dynamics: Understanding the Divergence

What explains these dramatically different price trajectories? Here are several (but not all of the) key factors:

Factors Driving Price Increases

• Government regulation creating compliance costs and barriers to entry.
• Quasi-monopolistic markets with limited price competition.
• Non-tradeable services protected from foreign competition.
• Limited technological disruption in certain service sectors.

Factors Driving Price Decreases

• Foreign competition putting downward pressure on prices.
• Technological advancement reducing production costs.
• Manufacturing optimization increasing efficiency.
• Market competition forcing price discipline.
• Trade liberalization expanding access to global markets.

Looking at the prices that decrease the most, they’re all technologies. New technologies almost always become less expensive as we optimize manufacturing, components become cheaper, and competition increases. According to VisualCapitalist, at the turn of the century, a flat-screen TV would cost around 17% of the median income ($42,148). Since then, though, prices fell quickly. Today, a new TV typically costs less than 1% of the U.S. median income ($54,132).

We should also consider the larger trends. For example, In 2020, I asked what Coronavirus would do to prices ... and the answer turned out to be way less than expected. If you don’t look at the rise in inflation but instead the change in trajectories, very few categories were heavily affected. While hospital services have increased significantly since 2019, they were already rising. There were some immediate impacts, but they went away relatively quickly. 

Another thing to consider is average hourly income. Since 2000, overall inflation has increased by 87.3%, while average hourly income has increased by 123.3%. This means that hourly income increased 38% faster than prices (which indicates a 16.1% decrease in overall time prices). You get 19.2% more today for the same amount of time worked ~24 years ago. This represents a mild increase in abundance since last year. 

via Human Progress

Although 10 of the 14 items rose in nominal prices over the past 24 years, only five had a higher time price when accounting for the 123.3 percent increase in hourly wages. Those items were medical care services, childcare and nursery school, college textbooks, college tuition and fees, and hospital services. 

The Consumer Experience: Perception vs. Reality

It’s interesting to look at data like that, knowing that the average household is feeling a “crunch” right now.

My guess is that few consumers distinguish between perception and reality. However, feeling a crunch isn’t necessarily the same as being in a crunch.

For instance, we must account for ‘quality of life creep,’ where people tend to splurge on luxuries as their standard of living improves. With the ease of online shopping and access to consumer credit, it has become increasingly easy to make impulse purchases, leading to reduced savings and feelings of financial scarcity. This phenomenon is a function of increased consumption (rather than inflation), yet it still leaves consumers feeling like they’re struggling to make ends meet. Our sense of what’s normal has risen, and that’s hard to unlearn. 

 

Perry’s ‘Chart of the Century’ reveals the complex relationships between inflation, consumption, and economic growth. While households may feel financial strain, the data shows that income has outpaced inflation, and technology has made many goods more affordable. Nonetheless, there is still a real sense of economic struggle. Especially in these last few months. 

 

Economic Patterns: Regulated vs. Free Markets

A clear pattern emerges when examining the relationship between market structures and price trends.

Regulated Markets (like healthcare and education) tend toward higher prices over time, feature less price competition, and offer limited consumer choice.

Free Markets, show price decreases over time, feature greater competition, and provide consumers more options.

This pattern raises important questions about the role of regulation in various economic sectors and the balance between consumer protection and market efficiency.

With that in mind, how can policymakers address sectors experiencing significant price hikes, such as healthcare and education, without stifling innovation in tradable goods and services? 

Future Outlook

Beyond all that, here are three other key trends to watch.

• AI Disruption: Telemedicine and online education could bend healthcare/education cost curves.
• Trade Wars: New tariffs risk reversing tech price declines (e.g., proposed tariffs on Chinese electronics).
• Generational Shifts: Millennials prioritize experiences over goods, potentially easing service demand.

As we continue to innovate and policy changes, it will be interesting to see if we can make essential services as dynamically competitive as consumer electronics. While America is one of the best countries in the world in countless ways, we do lag behind several countries in healthcare and education.

Onwards.

Here Are Some Links For Your Weekly Reading - April 20th, 2025

Here are some of the posts that caught my eye recently. Hope you find something interesting.

Lighter Links:

• OpenAI's Most Impressive Move Has Nothing to Do With AI. (ZDNet)
• AI Stuns Researchers by Rewriting Its Own Code to Overcome Limitations. (TalkAndroid)
• Meta’s New AI Tech Can Read Your Mind at Work…What Could Possibly Go Wrong? (AllWork)
• How to Enter a ‘Flow State’ on Command: Peak Performance Mind Hack Explained in 7 Minutes. (OpenCulture)
• British Anthropologist Claims Jesus' Tomb and Ark of the Covenant are Beneath the Great Pyramid. (JPost)

 

 

Trading Links:

• Trump’s Knives Are Out for Jerome Powell, Setting Up a Supreme Court Showdown Over the Fed’s Independence. (Fortune)
• First Shockwaves of Trump’s Tariffs are About to Hit the World Economy. (Bloomberg)
• America is Losing the Robot Wars. (Insider)
• The Only Way Some Manufacturing Jobs Will Return Stateside is If AI-Empowered Robots Do Them—And That’s a Good Thing. (Fortune)
• ‘China’s Elon Musk’ Uses Just Two Numbers to Demonstrate Why His Country’s Auto Industry is Now Outcompeting the U.S. And Europe. (Fortune)

Are Billionaires Popular?

We live in an interesting time. Many billionaires aren’t just business leaders - they’re also influencers, personalities, and public figures. 

While countless billionaires go under the radar, several of today’s billionaires have become controversial figures - like Elon Musk. So, how do the top 10 richest Americans rank in this so-called “popularity contest?”

via visualcapitalist

It’s interesting how many of the 10 wealthiest people in America are still flying relatively under the radar. In my head, names like Sergey Brin or Larry Page should still be household names. 

On the other side of this scale, the three richest billionaires have primarily unfavorable ratings ... with Mark Zuckerburg being the most disliked of the bunch. 

Meanwhile, Warren Buffett and Bill Gates have predominantly positive ratings - though Bill is more polarizing than Buffett. 

As an aside, the world’s richest lost over $200 billion in a single day as news of Trump’s tariffs rocked markets. For context, that drop is the fourth-largest one-day decline in the Bloomberg Billionaires Index’s 13-year history.

How Are You Feeling About The Tariffs?

Trump announced his reciprocal tariffs this week, and the world went into an uproar and the market into a tailspin. As an immediate result, JP Morgan switched its economic prediction from "Solid Growth" to "Recession Risk"

My take: Actions Have Consequences. More importantly,  we don't know all the actions ... and we certainly haven't recognized all the consequences. This is the beginning of something bigger than it seems, and many of the outcomes are beyond our current expectations or comprehension.

Sure, we saw some fundamental shifts last week ... but know that we are in for more.

The moves were big and fast enough that most people I know haven't had the time or brain cells to ponder things long and deep enough to form a well-reasoned opinion.

The only thing I "know" is that I expect more volatility and big moves.

With that in mind, here are some charts to help keep you informed as the consequences unfold. 

 

Chart #1 - Global Stock Market Returns in Q1 of 2025

via visualcapitalist

Chart #2 - Trump's Reciprocal Tariffs on Major Nations

via visualcapitalist

Chart #3 - Tariff Shock Wipes $5.3 Trillion Off S&P 500: Index Falls 10.5% in Two Days

via visualcapitalist

Looking at the first chart, it's clear that prior to this announcement, there was a U.S. sell-off, perhaps caused by concerns about inflation and slower GDP growth. As a result, more investment was moving toward Chinese and European stocks. 

After Trump's announcement, many things happened, including a joint response from China, Japan, and Korea - something I never thought I'd see. Also, many internet netizens started to plug questions into AI LLMs and receive similar results as Trump's tariffs. Contrary to a more complex equation, it appeared as if the tariff rates were calculated by dividing the deficit and imports of a country. Ultimately, this math was confirmed by the White House Deputy Press Secretary, Kush Desai. 

It will be interesting to see what is walked back and what is doubled down on over the next few weeks. 

Do you have faith?  Do you have an opinion?  I'd love to hear it!

Understanding the Shape of Change

Change is the only constant in life, yet it rarely unfolds in ways we expect. While we sense its approach, its shape — whether sudden and disruptive or slow and subtle — often defies our predictions. As the pace and scale of change accelerate, understanding its patterns becomes more crucial than ever.

The World Government Summit put together a helpful interactive website where you can test your knowledge on the trajectory of key statistical indicators for the development of society over the past decade. Here is the text from their opening screen.

 

Can we estimate how much the world has changed in a decade? Or do our own experiences impact the perception of progress? This work challenges the assumptions we make about how key statistical indicators regarding Health, the Environment, or Education evolve through the years. 

- The Shape of Change via the World Government Summit

The first part of the process was designed to be like a guessing game where you try to predict the direction and the rate of change of key issues shaping the world (like oil dependency, pollution,  literacy, economic freedom, etc.) by answering some questions at "The Shape of Change." It is simple, easy-to-use, and has a nice interface ... but answering the questions was more challenging than expected. Try it here. 

 

The Shape of Change via the World Government

The second part of the experiment lets you explore the year-over-year changes in key statistics regarding health, education, economy, and other topics.

 

The Shape of Change via the World Government

If you want to explore this further, I asked Perplexity to give me a broad overview of the project and its key insights. Here is the link.

The data is interesting. But, perhaps, your reaction to the data is more important. 

Were there any numbers that surprised you?

Taking Lessons on AI from my Grandmom

Almost every event I go to nowadays ends up focused on AI. At a recent event, conversations ranged from use cases for generative AI (and the ethics of AI image creators) to the long-term effects of AI and its adoption.

Before I could chime in, the conversation had gone to the various comparisons from past generations. When electricity was harnessed, articles claimed that it would never catch on, it would hurt productivity – and woe be unto the artisans it would potentially put out of business if it were to gain traction. 

When the radio or TV was released, the older generation was sure it would lead to the death of productivity, have horrible ramifications, and ultimately lead to the next generation's failure. 

People resist change. We're wired to avoid harm more than to seek pleasure. The reason is that, evolutionarily, you have to survive to have fun. 

On the other hand, my grandmother used to say: "It's easy to get used to nice things." 

 

 

Here's a transcript of some of my comments during that discussion: 

 

With AI, getting from "Zero-to-One" was a surprisingly long and difficult process.  Meaning, getting AI tools and capabilities to the point where normal people felt called to use it because they believed it would be useful or necessary was a long and winding road.  But now that everybody thinks it's useful, AI use will no longer be "special".  Instead, it will become part of the playing field.  And because of that, deciding to use AI is no longer a strategy.  It becomes table stakes.

But that creates a potential problem and distraction.  Why?  Because, for most of us, our unique ability is not based on our ability to use ChatGPT or some other AI tool of the day.  As more people focus on what a particular tool can do, they risk losing sight of what really matters for their real business.

Right now, ChatGPT is hot!  But, if you go back to the beginning of the Internet, MySpace or Netscape (or some other tools that were first and big) aren't necessarily the things that caught on and became standards.

I'm not saying that OpenAI and ChatGPT aren't important.  But what I believe is more important is that we passed a turning point where, all of a sudden, tons of people started to use something new.  That means there will be an increase of focus, resources, and activity concentrated on getting to next in that space.

You don't have to predict the technology; it is often easier and better to predict human nature instead.  We're going to find opportunities and challenges we wouldn't because of the concentration of energy, focus, and effort.  Consequently, AI, business, and life will evolve.

For most of us, what that means is that over the next five years, our success will not be tied to how well we use a tool that exists today, but rather on how we develop our capabilities to leverage tools like that to grow our business and improve our lives. 

Realize that your success will not be determined by how well you learn to use ChatGPT.  It will be determined by how well you envision your future and recognize opportunities to use tools to start making progress toward the things you really want and to become more and more of who you really are.  Right?

So, think about your long-term bigger future.  Pick a time 5, 10,  or even 20 years from now.  What does your desired bigger future look like?  Can you create a vivid vision where you describe in detail what you'd like to happen in your personal, professional, and business life?  Once you've done that, try to imagine what a likely midpoint might look like.  And then, using that as a directional compass, try to imagine what you can do in this coming year that aligns your actions with the path you've chosen.

 

Ultimately, as you start finding ways to use emerging technologies in a way that excites you, the fear and gloom fade.

The best way to break through a wall isn't with a wide net ... but with a sharp blow. You should be decisive and focused. 

Commit to using AI in ways that give you energy, which may be entirely different from how you use it now. 

So much of what we do now is anchored in the past. This is an opportunity to transcend the old ways you did things and to shape and transform your future (and perhaps even what you believe is possible).

I was an entrepreneur in the late 90s (during the DotCom Bubble). And I remember watching people start to emulate Steve Jobs ... wearing black faux-turtlenecks and talking about how they were transforming their business to be in an Internet company – or which Internet company would be the "next big thing." Looking back, an early sign that a crash was coming was that seemingly everybody had an opinion about what would be hot, and too many people were overly confident in their views because seemingly everyone was saying the same things. 

Human nature has remained stubbornly consistent through many waves of technology. 

The point is that almost nobody talks about the Internet with the focus and intensity they did in the late 90s ... in part because the Internet is now part of the fabric of society. At this point, it would be weird if somebody didn't use the Internet. And you don't really even have to think about how to use the Internet anymore because there's a WHO to do almost all those HOWs (and many of them are digital WHOs that do those HOWs for you without you even knowing they were needed or being done). 

The same is going to be true for AI. Like with any technology, it will suffer from all the same hype-cycle blues of inflated expectations and then disillusionment. But, when we come out the other side, AI will be better for it ... and so will society. 

Understanding the Possibility Scale

It helps to understand how we bring things into existence. To start, it's nearly impossible to manifest something you can't first imagine. And there is a moment just before something happens - when it becomes inevitable. 

I created this Possibility Scale to help envision the stages of becoming.

 

 

As an aside, before today, I would not have attempted to create an image for a post like this. While I love thinking and writing, image creation was outside my area of expertise or unique ability. But now things are different. Today, I simply asked ChatGPT to create that image. Yes, it took me four tries ... each retry starting with "that was great, now help me improve the prompt to (fix the thing I wanted done differently)."  At the end, I asked it to give me the complete prompt I could reuse. Contact me if you want the prompt.

Earlier, I mentioned how long it took to get from "Zero-to-One" with AI. But don't fret; things are speeding up, and we're just at the beginning of the process. If I created a scale to show the capabilities of AI, and set the endpoint at 100 to represent AI's potential when I die - even though I'm in my early 60s, I'd put us at only a 3 or 4 on that 100-point scale. Meaning, we are at the beginning of one of the biggest and most asymptotic curves that you can imagine. That also means that you're not late. You're early! Even the fact that you're thinking about stuff like this now means that you are massively ahead of most.

The trick isn't to figure out how to use AI or some AI tool. The trick is to keep the main thing the main thing. Build your ability to recognize when and how to use these new capabilities to bring the future forward faster.

Investing resources into your company is one thing. Realize that there are 1000s of these tools out there, and many more coming. You don't have to build something yourself. It is often faster and better to acquire a tool than it is to spend money on developing and building it.

Think of the Medici family. They invested in people, which in turn triggered the Renaissance. A key to moving forward in the Age of AI will be to invest in the right WHOs, seeking to create the kind of world you want to see or the types of capabilities you desire. Think of this as a strategic investment into creators and entrepreneurs with a vision or who are on a path that aligns with yours.

As you get better and better at doing that, you'll see increasing opportunities to use tools to engage people to collaborate with and create joint ventures. Ultimately, you will collaborate with technology (like it's your thought partner and then your business partner). We are entering exciting times where AI, automation, and innovation will make extraordinary things possible for people looking for opportunities to do extraordinary things.

As my grandmother said, it's easy to get used to nice things.

Onwards!

Mad About March Madness

March Madness is in full swing and will have the world's attention for a few more days. As you can guess, almost no one has a perfect bracket anymore. McNeese beat Clemson, Drake beat Mizzou, and Arkansas handed Kansas its first first-round loss since 2006. On Friday, the NCAA said that of the over 34 million brackets submitted at the start of March Madness, approximately 1,600 remained perfect. That's less than .1% after the first day. The first game of the tournament - Creighton vs. Louisville - busted over half of the brackets. 

Before 24/7 sports channels, people watched the weekly show "The Wide World of Sports."  Its opening theme promised "The thrill of victory and the agony of defeat!" and "The human drama of athletic competition." That defines March Madness.

The holy grail is mighty elusive in March Madness (as in most things). For example, the odds of getting the perfect bracket are 1 in 9,223,372,036,854,775,808 (that is 1 in 9.223 quintillion if that was too many zeros count). If you want better odds, then you can have a 1 in 2.4 trillion chance based on a Duke Mathematician's formula that takes into account ranks). It's easier to win back-to-back lotteries than picking a perfect bracket. Nonetheless, I bet you felt pretty good when you filled out your bracket.

via Duke University

Here's some more crazy March Madness Stats: 

• Companies expect $4 Billion of corporate losses due to employees tracking games
• The highest-paid NCAA coach, Kansas's Bill Self, makes a salary of $8.8 Million
• In 2018, it was estimated that March Madness generated $10 Billion in gambling (twice as much as the Super Bowl)

 

Feeding the Madness

"Not only is there more to life than basketball, there's a lot more to basketball than basketball." - Phil Jackson

In 2017, I highlighted three people who were (semi) successful at predicting March Madness: a 13-year-old who used a mix of guesswork and preferences, a 47-year-old English woman who used algorithms and data science (despite not knowing the game), and a 70-year-old bookie who had his finger on the pulse of the betting world. None of them had the same success even a year later.

Finding an edge is hard - Maintaining an edge is even harder.

That's not to say there aren't edges to be found. 

Bracket-choosing mimics the way investors pick trades or allocate assets. Some people use gut feelings, some base their decisions on current and historical performance, and some use predictive models. You've got different inputs, weights, and miscellaneous factors influencing your decision. That makes you feel powerful. But knowing the history, their ranks, etc., can help make an educated guess, and they can also lead you astray. 

The allure of March Madness is the same as gambling or trading. As sports fans, it's easy to believe we know something the layman doesn't. We want the bragging rights for the sleeper pick that went deeper than most expected, our alma mater winning, and for the big upset we predicted. 

You'd think an NCAA analyst might have a better shot at a perfect bracket than your grandma or musical-loving co-worker.

In reality, several of the highest-ranked brackets every year are guesses. 

The commonality in all decisions is that we are biased. Bias is inherent to the process because there isn't a clear-cut answer. We don't know who will win or what makes a perfect prediction. 

Think about it from a market efficiency standpoint. People make decisions based on many factors — sometimes irrational ones — which can create inefficiencies and complexities. It can be hard to find those inefficiencies and capitalize on them, but they're there to be found. 

In trading, AI and advanced math help remove biases and identify inefficiencies humans miss.

Can machine learning also help in March Madness?

“The greater the uncertainty, the bigger the gap between what you can measure and what matters, the more you should watch out for overfitting - that is, the more you should prefer simplicity” - Tom Griffiths

The data is there. Over 100,000 NCAA regular-season games were played over the last 25+ years, and we generally have plenty of statistics about the teams for each season. There are plenty of questions to be asked about that data that may add an extra edge. 

That said, people have tried before with mediocre success. It's hard to overcome the intangibles of sports—hustle, the crowd, momentum—and it's hard to overcome the odds of 1 in 9.2 quintillion. 

Two lessons can be learned from this:

1. People aren't as good at prediction as they predict they are.
2. Machine Learning isn't a one-size-fits-all answer to all your problems.

Something to think about.

 

Feeding the Madness

"Not only is there more to life than basketball, there's a lot more to basketball than basketball." - Phil Jackson

In 2017, I highlighted three people who were (semi) successful at predicting March Madness: a 13-year-old who used a mix of guesswork and preferences, a 47-year-old English woman who used algorithms and data science (despite not knowing the game), and a 70-year-old bookie who had his finger on the pulse of the betting world. None of them had the same success even a year later.

Finding an edge is hard - Maintaining an edge is even harder.

That's not to say there aren't edges to be found. 

Bracket-choosing mimics the way investors pick trades or allocate assets. Some people use gut feelings, some base their decisions on current and historical performance, and some use predictive models. You've got different inputs, weights, and miscellaneous factors influencing your decision. That makes you feel powerful. But knowing the history, their ranks, etc., can help make an educated guess, and they can also lead you astray. 

The allure of March Madness is the same as gambling or trading. As sports fans, it's easy to believe we know something the layman doesn't. We want the bragging rights for the sleeper pick that went deeper than most expected, our alma mater winning, and for the big upset we predicted. 

You'd think an NCAA analyst might have a better shot at a perfect bracket than your grandma or musical-loving co-worker.

In reality, several of the highest-ranked brackets every year are guesses. 

The commonality in all decisions is that we are biased. Bias is inherent to the process because there isn't a clear-cut answer. We don't know who will win or what makes a perfect prediction. 

Think about it from a market efficiency standpoint. People make decisions based on many factors — sometimes irrational ones — which can create inefficiencies and complexities. It can be hard to find those inefficiencies and capitalize on them, but they're there to be found. 

In trading, AI and advanced math help remove biases and identify inefficiencies humans miss.

Can machine learning also help in March Madness?

“The greater the uncertainty, the bigger the gap between what you can measure and what matters, the more you should watch out for overfitting - that is, the more you should prefer simplicity” - Tom Griffiths

The data is there. Over 100,000 NCAA regular-season games were played over the last 25+ years, and we generally have plenty of statistics about the teams for each season. There are plenty of questions to be asked about that data that may add an extra edge. 

That said, people have tried before with mediocre success. It's hard to overcome the intangibles of sports—hustle, the crowd, momentum—and it's hard to overcome the odds of 1 in 9.2 quintillion. 

Two lessons can be learned from this:

1. People aren't as good at prediction as they predict they are.
2. Machine Learning isn't a one-size-fits-all answer to all your problems.

Something to think about.