Thoughts about the markets, automated trading algorithms, artificial intelligence, and lots of other stuff

  • Visualizing Humanity’s Future in Space Exploration

    While space and space travel aren’t our usual topics of conversation, they do come up frequently.

    When you think about the future of technology, it‘s not just AI, automation, and Ozempic. Two emerging frontiers we don’t talk about enough are healthcare (longevity, regenerative medicine, and other breakthroughs) — and, you guessed it, Space.

    Space Still Feels Like the Final Frontier

    Growing up in the 60s and 70s, Space was a bastion of technological advancement, and it captured the collective minds of America and the World.

    I still remember watching the lunar landing and thinking how cool it was (and it still is)! And as a strange coincidence, over the past week, I’ve had three separate people comment that it was staged and fake (but that’s a totally different story, and I’m not going to write about it).

    Then, for decades, space exploration faded into the background. The zeitgeist moved on. It wasn’t until Elon Musk and SpaceX brought it back into the limelight with grandiose claims that we started to see meaningful momentum.

    Don’t get me wrong, the wheels were still turning behind the scenes, but it’s amazing what focused attention can do for an industry.

    We’ve evolved from government showpieces to a commercial ecosystem

    Humanity’s Future in Space

    I love spaceflight for many of the same reasons I love AI. 

    It’s a global initiative heralding innovation and improvements that promise to transform the world (or worlds). It is a catalyst for many exponential technologies. And in many respects, it is the path to our inevitable future.

    Many astronauts, even from the Apollo era, talk about the incredible feeling they experience after a few days in Space. As they look at Earth from above, they lose their sense of borders and nationality. They call it the “Overview Effect”. The Saudi astronaut Sultan bin Salman Al-Saud, who flew on the Space Shuttle in 1985, commented on this, saying, “The first day or so, we all pointed to our countries. On the third or fourth day, we were pointing to our continents. By the fifth day, we were aware of only one Earth.”

    On some level, space changes how we see borders, conflict, and collaboration.

    The infographic below comes from the Global 50 Future Opportunities Report from the Dubai Future Foundation. It introduces the breadth of programs and capabilities enabling humanity’s expansion into Space.

    An infographic highlighting space programs, space stations, and the future of space travel

    via visualcapitalist

    While only three countries currently have the capabilities of independent human spaceflight (China, Russia, and the United States), eight countries now have interplanetary probe capabilities.

    Today, commercial firms conduct about 70% of all spacecraft launches, and launch costs are 40 times lower than in the 1980s.

    What Comes Next?

    As the ISS nears retirement, the future is far more commercial, with several private stations planned for launch from America, such as Axiom Station and Haven-1.

    What excites me most now are the innovations enabling the next wave of exploration — and it’s not just cheaper space travel.

    • Space Flex – biohacking at the next level offers personalized supplements to prevent bone and muscle loss, supporting longer space missions and eventually planetary settlement.
    • Breakthrough Energy Sources and Storage – Breakthroughs in areas like cold fusion, energy storage, and dark energy are vital to powering advanced spacecraft and sustaining long-term settlements.
    • Network of Networks – advanced AI, automation, and communication networks will reduce disruptions and enable intelligent transitions between satellite and cellular networks. This is important for resilient connectivity in autonomous systems and disaster response.

    For investors and innovators, Space is less about rockets and more about a platform for new industries: in‑orbit manufacturing, earth observation data, resilient communications, and even biomedical breakthroughs unlocked by microgravity.

    When you zoom out, the “space age” is really an extension of the digital and AI revolutions into a new domain — one that will reshape risk, opportunity, and how we think about growth timelines.

    The Power of the Space Race

    For the first time, it feels like we are not just visiting Space; we are building there.

    Stations, networks, and new technologies are laying the groundwork for a permanent presence beyond Earth.

    Humans are wired to think linearly and locally, but I am grateful that some people see farther. While the universe is vast beyond comprehension, so is human curiosity. And as technology grows, so does our reach … and the questions we can afford to ask.

    Every new step outward expands what we believe is possible.

    We are only beginning to build the infrastructure of the space age, and the most exciting chapters are still ahead.

    In an era of intense global political strife, it gives me hope to see an initiative that links and aligns so many powerful minds.

    Onwards!

  • If We’re Not Alone In The Universe … Where Are The Aliens?!

    A lot is going on in our world, and some of that may not even be from our world.

    As an investor, I look at where capital and talent cluster. The renewed focus on space-tech, unidentified anomalous phenomena, and the potential of non-human intelligence isn’t just sci‑fi — it’s a signal (mixed with plenty of noise and misinterpretation).

    In this post, I’ll connect today’s disclosure headlines, the math behind extraterrestrial life, and what the Fermi Paradox suggests about our own future.

    Why Aliens Are Back in the News

    Trump has publicly ordered federal agencies to begin declassifying and releasing UFO/UAP and “alien”–related government files. He framed it partly as a response to Barack Obama’s recent podcast comments that “aliens are real”. When presidents from Trump to Obama nod at aliens, it signals that the topic has moved beyond late‑night jokes and into serious discourse.

    The disclosure process is just starting and will likely be slow, partial, and heavily filtered, at least at first.

    Experts note that many UFO/UAP files are classified less because of “aliens” and more because they contain sensitive data about sensors, intelligence methods, or military capabilities. Those portions will likely remain redacted.

    Said differently, many of the anomalous behaviors seen in videos are likely the result of military technologies from us or other nations.

    As a potentially related aside, retired U.S. Air Force Major General Neil McCasland recently went missing. His disappearance is drawing attention because of his past roles in highly classified space and UFO-related programs. Authorities have not publicly tied the case to any confirmed national security breach or conspiracy.

    As I look at markets and opportunities, I tend to focus on where energy, attention, and resources flow. So, even accounting for sensationalism and misinformation, it seems to me that this is an area worth paying attention to … even if just to figure out whether there’s something to pay attention to.

    So let’s dive into the crazy, at least a little bit.

    Capital Is Voting on Space

    I tend to read a wide variety of sources on an even wider variety of topics. Recently, I’ve noticed a significant uptick in stories about aliens, UFOs, non-human intelligence, and non-human technology. This has gone from fringe obsession, to cable‑news segment, and now to a Congressional hearing topic.

    In addition, several of my seemingly sane and highly credible friends claim to have direct knowledge that billionaires and hedge funds are quietly funding space tech and non-human intelligence bets because that’s where asymmetric advantage lives.

    Smart money is behaving as if the upside of being early to this frontier dwarfs the embarrassment risk of being wrong.

    While I believe it’s naive to assume that there’s no other form of life in a universe as vast as what we understand … I’m also highly skeptical of anyone who claims that they have specific knowledge or proof.

    With that said, I have seen enough stuff from people I trust to expect that our beliefs about these issues will shift massively in the very near future. As an example, check out Skywatch.ai, some of its videos, or this NewsNation broadcast.

    Are We Alone? Turning Speculation Into Math

    Meanwhile, Information Is Beautiful has an interactive data visualization to help you decide if we’re alone in the Universe. 

    As usual, it’s well done, fun, and informative. 

    For the slightly geeky among us, the model lets you adjust the estimate by playing with the Drake and Seager equations, which turn bar‑napkin speculation into math, estimating how many civilizations or life‑bearing worlds might actually exist.

    The Drake equation estimates the number of detectable extraterrestrial civilizations in our galaxy and the Universe. It factors in variables such as the number of habitable planets, the likelihood of life and intelligent life, and the duration over which a civilization sends signals into space. 

    The Seager equation is a modern take on the equation, focusing on bio-signatures of life that we can currently detect – for example, the number of observable stars/planets, the % have life, and the % chance of detectable bio-signature gas. 

    Even if you assume life is incredibly rare, the incredibly big numbers of planets mean ‘rare’ still translates to ‘many’. Click here to play with the Are We Alone in the Universe infographic. 

    via Information Is Beautiful

    For both equations, the infographic lets you view various default options and also enables you to change the variables based on your beliefs. 

    For example, the skeptic’s default answer for Drake’s equation shows 0.0000062 communicating civilizations in our galaxy, which is still 924,000 in the Universe. The equivalent for Seager’s equation shows 0.0009000 planets with detectable life in our “galactic neighborhood” and 135,000,000 planets in our Universe. 

    Even with the “lowest possible” selection chosen, Drake’s equation still shows 42 communicating civilizations (Douglas Adams, anyone?) in the Universe.

    Screen Shot 2020-12-13 at 2.54.27 PM

    via Information Is Beautiful

    Even if the probability is tiny on any single planet, at scale it becomes almost inevitable — which is how many breakthrough bets work in markets as well.

    One of the most interesting numbers (and potentially influential numbers for me) is the length of time a civilization sends signals into space. Conservative estimates are 420 years, but optimistic estimates are 10,000 or more. 

    One other thing to consider is that some scientists believe that life is most likely to grow on planets with very high gravity, which would also make escaping their atmosphere for space travel nigh impossible.

    So, Where Are They?

    The Universe is loud on paper, but quiet in practice.

    So, if the math says it’s likely that there are aliens … why don’t we see them?

    In 2020, I linked to an NBC News article claiming that a former Israeli space security chief says extraterrestrials exist, and Trump knows about it.

    There are many stories (or theories) about how we have encountered aliens before and just kept them secret. Here are some links to things you might find interesting if you want to learn more about this.

    So, while some may still believe aliens don’t exist – I think it’s a more helpful thought experiment to wonder why we haven’t seen them. This matters not just to astronomers and conspiracy theorists, but to anyone thinking about risk, technology, and the fate of complex civilizations.

    For example, the Fermi Paradox addresses the apparent contradiction between the lack of evidence for extraterrestrial civilizations and the high-probability estimates of their existence. 

    When considering the key factors for a spacefaring civilization capable of communication, we think about habitability, life, technological progress, and social interaction. However, it’s possible that most civilizations die of self‑inflicted wounds (war, engineered plagues, or environmental collapse) long before they can shout across the galaxy. 

    If that is true, perhaps the real question isn’t ‘Are we alone?’ but ‘Can we master our own trajectory before we join the list of civilizations that disappeared in silence?’

    Not to mention, even forgoing the numerous roadblocks to intelligent and communicative life, it’s entirely possible that other planets that surpassed these roadblocks existed a long, long time ago, in a galaxy far away …

    If any aliens are reading this … don’t worry, I won’t tell. But we will find out who you voted for in the last election.

    What do you think?

  • Here Are Some Links For Your Weekly Reading – March 8, 2026

    Lighter Links:

    Trading Links:

  • Turning Friends Into Frenemies: A Powerful Prompting Framework

    If you’re reading this, you’re probably using AI more than you used to — but how has your use actually evolved?

    The more I use AI, the more I worry it agrees with me too much … or worse, that I agree with it too quickly.

    For me, as AI becomes more powerful, I’m using it in more places more often. It’s becoming a step in almost every process I do.

    At the beginning, my use was very simple. I would highlight a sentence and say, “Improve this.” I was often surprised by an LLM’s ability to take a jumble of words and distill something shorter and more meaningful. I’m sure many started to feel like they could put voice to their thoughts.

    Then, I was impressed by AI’s ability to turn long articles or collections of sources into tight summaries that made clear why they mattered and what to do next.

    Over time, I learned to use AI to help me do things I already did, to the point where it enhanced my ability to do it … or freed me up to do a little bit more.

    Now, if I’m doing something repeatedly and not using AI or automation, I assume that’s a problem.

    Not everyone feels that way.

    For example, this weekly commentary is still primarily written by humans (my son, Zach, and me). As AI becomes a larger part of the production process, Zach becomes increasingly dubious of how I use AI. He worries that AI-In-the-Loop processes impact our writing in ways that we quickly become desensitized to or stop noticing altogether(for example, logical patterns, word choices, common idiosyncrasies, or misplaced confidence).

    Too Much of Anything Isn’t Good — Even Agreement

    As amazing as AI tools are, it’s well-documented that they can be sycophantic, hallucinate & fabricate, and be surprisingly rigid in their process … if  you don’t have a good enough process in place to manage things like that.

    Meanwhile, prompt researchers found that making AI agents ruder resulted in better performance on complex reasoning tasks.

    So I wanted an AI that communicates with me like a sharp board member — not a flattering intern. That’s where prompts like the Frenemy Prompt come in.

    I saw this on Tech Radar. Here is the basic idea.

    Respond with direct, critical analysis. Prioritize clarity over kindness. Do not compliment me or soften the tone of your answer. Identify my logical blindspots and point out the flaws in my assumptions. Fact-check my claims. Refute my conclusions where you can.

    The Frenemy Fact-Check

    This prompt turns an AI into a hostile‑but‑useful executive reviewer that turns text into decision‑grade clarity by separating what’s said, what’s assumed, what’s missing, and what actually matters.

    It’s designed to:

    • Take a piece of text (an article, memo, thread, transcript)
    • Refuse to trust it
    • Separate what is actually said from what is assumed
    • Stress‑test it like a skeptical board member, and
    • End with a clear decision posture and a best next step

    A Fluff-Busting Example:

    If you’ve been a reader for a while, then you know I share a lot of links to a wide range of materials. What you see is the filtered list after I’ve read it, tagged it, ranked it, and decided what to share … but what I see is much broader. Some of it is AI slop, conspiracy theory madness, or aspirational thinking masquerading as strategic thinking. I wanted something that helped me sort, sift, and filter what comes across my screen. For example, this week I clicked on this article claiming that new experiments confirm the existence of parallel universes. If I simply asked AI to summarize the article, it would. But this prompt gives me something different. Its response started this way:

    Executive Brief:

    Posture: Probe — The piece argues that multiple experimental and theoretical threads make the many‑worlds / multiverse idea increasingly plausible; it’s an interpretive synthesis, not a proof.

    Biggest risk: Conflating interpretation and empirical demonstration — many claims are inference/speculation built on experimental results.

    Next action: Identify the article’s specific factual claims and separate which are quote-backed, which are inference, and which require verification.

    That prompt then goes on to identify all the different claims to verify, fluff to bust, and even makes it easy for me to expand the research or reconcile the language. Here is the output of the first step if you are curious.

    The point of this article isn’t to share a polished prompt. My production version is long, messy, and customized to my workflow and input sources. However, if you’re interested, here is a basic Frenemy Fact-Check Framework prompt that you can customize.

    I’m sharing the idea as a seed — useful on its own, but far more powerful once you make it simple, repeatable, consistent, and scalable.

    For context, my current version, 7.0, is over twice as long, has portions that a human won’t understand, and understands me and my needs much better than this seed.

    And it was AI that helped me iterate on the prompt until it reached that point.

    Creating a Production-Grade Process

    The way you do that is by analyzing what you’re doing, both in terms of what the audience sees (front stage) and what is required to reliably produce the front-stage experience (backstage).

    Most prompts focus on the front stage and don’t handle the backstage well enough to be reliable in production.

    Front Stage vs. Back Stage

    Front stage, it looks like: “AI reads something and gives a sharp executive review.”

    Backstage, it’s doing something much more important: It’s not focused on “smartness” or “creativity”… it is manufacturing reliability.

    Think of it like a restaurant:

    • The dining room is what customers see (front stage).
    • The kitchen is why the same dish comes out the same way every night (backstage).

    A professional-grade Frenemy prompt must include the kitchen spec for decision-grade analysis.

    Here are some high-level concepts to consider in a prompt like this.

    First Principles of the Prompt

    At its heart, the system enforces three laws:

    Law 1: Words ≠ Truth

    If it’s not quoted, it’s not solid.

    Anything not directly supported by text must be labeled:

    • Inference (reasonable but not stated)
    • Speculation (guessing)

    Law 2: Structure Beats Intelligence

    There is a difference between could be strengthened by briefly contrasting “clever but inconsistent” vs. “structured and reliable.” My production prompt doesn’t rely on the model being ‘smart.’ It relies on the structure we wrap around it.

    It relies on:

    • Rigid section definitions
    • Mandatory labels
    • Forced ordering
    • Hard cap limits

    This is why it’s long. But, it’s not verbosity — it’s scaffolding.

    Law 3: Decisions Are the Point

    Every run ends with:

    • A posture (Proceed / Pause / Probe / Pivot)
    • A biggest risk
    • A next action
    • A control panel that helps the user choose what happens next

    As AI makes analysis easier to generate, it becomes even more important not to automate “analysis for analysis’s sake.” This prompt framework was designed to encourage right actions.

    The longer the content and project you give AI, the more likely it is to break protocol and make mistakes. A production-grade prompt like this constrains the AI so it can’t “help” in the wrong way, and blocks hallucinations or fake precision by default. It turns raw text into structured evidence, labels ambiguity clearly, and keeps outputs consistent and stable—even under pressure or long inputs. Most importantly, it keeps humans in control through a clear command interface, which is why it’s far more reliable than the average prompt.

    I’d love to hear about ways you’re using AI to improve the quality of your output, enhance your performance, or expand what you believe is possible.

  • What Do Abraham Lincoln and Family Finance Have in Common? My Cousins.

    A few years ago, I brought my cousin, Matt Pinsker, an expert in Civil War history and Abraham Lincoln, to speak to an exclusive mastermind. He did an outstanding job of relating Lincoln’s letters and history to the entrepreneurial mindset. As a result, he also did a podcast with me, Dan Sullivan, and Steven Krein on the ultimate entrepreneurial president. Steven Krein is also my cousin, so it was a family affair. 

    Recently, he released a book called Boss Lincoln, exploring Lincoln’s expertise in party politics and his skillful navigation of treacherous partisan crosscurrents, helping build the Republican Party into a viable force.

    Not to mention, undertaking such actions with emancipation and the war’s outcome at stake, while facing severe criticism from all directions.

    Although Lincoln is one of the most celebrated Presidents in history, he faced immense challenges during his time. In private, he was clever and persistent, able to use skillful manipulation, straightforward intimidation, or thoughtful debate as required to accomplish his goals.

    Lessons from his presidency are still incredibly relevant today (if not more so).

    But he’s not the only cousin who has recently released a book.

    Photos of my Cousins Matt and Beth, with their books and a brief description of the books

    Don’t Wait. Plan Ahead.

    Beth is a financial-planning columnist at MarketWatch and has been a Certified Financial Planner™ since 2018. She won a SABEW Best in Business award in 2023 for commentary for a series of columns about caring for her mother, which she turned into the premise for this book.

    It includes some incredible anecdotes about their parents, as well as personal stories from many children and spouses of aging parents. More importantly, it’s a powerful handbook for everything you need to know about the complex world of end-of-life financial planning.

    Even though I grew up with them, I still learned things about the family I didn’t already know.

    Check Them Out

    If you want to purchase Matt Pinsker’s most recent book, Boss Lincoln, you can do so here: WW Norton | Amazon | Barnes & Noble

    If you want to purchase Beth Pinsker’s book, My Mother’s Money, you can do so here: Penguin Randomhouse | Amazon | Barnes & Noble

    And, if you want to listen to the podcast episode with Matt & Steven Krein, you can do so here:

    We talk about revolutions, technology, future-orientation, and more. It’s a great episode, and worth listening to for entrepreneurs, history buffs, and anyone looking to thrive in a changing world. 

    Hope you enjoy it. 

  • Here Are Some Links For Your Weekly Reading – March 1, 2026

    Lighter Links:

    Trading Links:

  • The “Chart Of The Century” In 2026: A Look At Consumer Price Inflation (CPI)

    If you ask most people whether life has gotten more affordable since 2000, the instinctive answer is ‘no.’ Groceries feel expensive, rent and healthcare feel punishing, and headlines about inflation haven’t helped.

    Yet Mark Perry’s ‘Chart of the Century’ tells a more complicated story. Over the past 25 years, average wages have grown faster than overall inflation — meaning many Americans can buy more with each hour of work than they could in 2000. The challenge is that this progress is uneven and often invisible, especially in the everyday essentials where people feel prices most.

    The most current version reports price increases from 2000 through the end of 2025 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 (131% vs. 92.6%) from 2000 to 2025, resulting in a 20% 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 declines, while regulated markets and limited competition drive 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:

    MetricChange
    (2000-2025)
    Consumer Price Index (CPI)+92.6%
    Average Hourly Income+131%
    Real Purchasing Power+20%

    From January 2000 to now, the CPI for All Items has increased by over 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 25 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, has 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.

    Mark Perry’s “Chart of the Century” Showing CPI of selected US Consumer Goods

    via Mark Perry

    Here is how to read this chart.

    • Think of the CPI line as the baseline: it’s the average rate of inflation for all items combined.​
    • Any category’s line running far above that baseline is a “price climber” that has gotten significantly harder to afford over time.​
    • Any line trending well below that baseline is a “price deflator” that has become more affordable relative to your income and other prices.

    Looking at the chart, the conventional wisdom holds: many ‘luxuries’ have gotten cheaper, while several everyday ‘necessities’ have become more expensive.

    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. Since last year, they’ve increased by another 3.1% (the CPI for ALL ITEMS increased by 2.7%). College tuition and hospital services have also 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 creates compliance costs and barriers to entry.
    • Quasi-monopolistic markets with limited price competition.
    • Non-tradeable services protect 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 increases efficiency.
    • Market competition forces price discipline.
    • Trade liberalization expands 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).

    Longer-term trends also matter. For example, in 2020, I asked how the coronavirus would affect prices … and the actual impact turned out far less dramatic than many feared. 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 key factor is average hourly income. Since 2000, overall inflation has increased by 92%, while average hourly income has increased by 131%. This means that hourly income increased ~40% faster than prices (which indicates a 20% decrease in overall time prices). So, if your work earned 10 units of goods in 2000, it would now get you 12 units. 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 25 years, only 5 had a higher time price when accounting for increases in hourly wages. Those items were medical care services, childcare and nursery school, college textbooks, college tuition and fees, and hospital services. 

    So how does this show up in real life?

    The Consumer Experience: Perception vs. Reality

    It’s striking 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 (such as healthcare and education) tend to have higher prices over time, less price competition, and limited consumer choice.

    Free Markets show price decreases over time, feature greater competition, and provide consumers with 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 the cost curves for healthcare and education.
    • Trade Wars: While the tariffs were just struck down by the Supreme Court, that likely doesn’t mean the end of this saga.
    • Generational Shifts: Millennials prioritize experiences over goods, potentially easing service demand.

    As innovation and policy evolve, it will be interesting to see if we can make essential services as dynamically competitive as consumer electronics. While America excels in many ways, we lag behind several countries in healthcare and education in terms of cost and outcomes.

    I’d love to know what you think about this and how you see it playing out.

    Onwards.

  • A Look At The Megacities of Today & Tomorrow

    Studying long‑term population trends shows not just how we grew from small tribes to global megacities, but where capital, innovation, and geopolitical power are likely to concentrate next.

    From ancient civilizations to modern metropolises, population dynamics have influenced everything from economic prosperity to social structures.

    A Window Into Our Past Gives Us a Glimpse at Our Future.


    By studying this critical aspect of human history, we can gain valuable insights into the past, present, and future of societies.

    Population growth is a complex, multifaceted phenomenon with far‑reaching implications. It reveals the demographic forces that have shaped our world — and continue to influence where we’re headed.

    Historically, human populations grew steadily but relatively slowly until that changed dramatically. 

    Scientists estimate that humans have existed for at least 130,000 years. However, it took until 1804 for our population to reach 1 billion. We doubled that population by 1927 (123 years later), and then doubled it again only 47 years later (in 1974). 

    Early population growth was largely driven by the agricultural revolution. Since the Industrial Revolution (in 1804), advances in health and safety, and new technologies have significantly improved the quality of life, spurring rapid population growth.

    For investors, operators, and policymakers, demographic data is not trivia. It is one of the few datasets that let us reliably look decades into the future — and it shapes where markets, labor, and infrastructure demand will emerge.

    Here is a quick overview of key factors to consider.

    Demographics: A Glimpse of the Future

    It’s hard to predict some things accurately. Accordingly, one goal in data science is to figure out what we can “know” to “guess” less.

    Population growth is a prime example. One of the easiest ways to predict how many 60-year-olds there will be in 40 years is to look at how many 20-year-olds there are today. Obviously, the number won’t be exact, but it’s a pretty good head start.

    Likewise, demographic forecasts are powerful but not omniscient; wars, pandemics, and climate shocks can redraw maps. The point isn’t precision, but probabilities—and they still overwhelmingly favor certain regions and city types.”

    This principle of using known data to make educated predictions applies to many aspects of future planning, including urban development and resource allocation. By leveraging current demographic information, we can better prepare for the challenges and opportunities that will likely impact the cities of tomorrow.

    • Economic Implications: A growing population can expand the workforce, fueling economic growth. However, it can also strain resources, requiring increased investment in infrastructure, education, and healthcare.
    • Social and Environmental Pressures: Demographic shifts, such as aging populations or youth bulges, can profoundly affect social structures, healthcare systems, and the environment.
    • Technological Acceleration: Dense urban populations can accelerate innovation, data creation, and the adoption of new technologies.

    These demographic patterns are not abstract — they have concrete consequences for economies, societies, and the environment.

    Why It Matters

    Population growth is more than just a numerical metric. It is a fundamental lens through which we can analyze:

    • Historical Development: By understanding past population trends, we can better appreciate the factors that have shaped human civilizations.
    • Future Planning: Governments, businesses, and organizations can use population data to inform decisions on resource allocation, infrastructure development, and social policies.

    Have World Population Growth Numbers Peaked?

    World population growth rates peaked in the late 1960s and have declined sharply over the past four decades, but we’re still on an upward trend. We’re expected to reach 9 billion people by 2050, but much of that growth comes from developing countries – and it’s almost exclusively from urban areas. 

    Axios created an interactive graphic that shows how birth rates and population structures vary across countries.

    via Axios (Click for an Interactive Graph)

    There are more people alive today than at any point in history — and the population is still growing, just more unevenly. Much of the future population growth will not occur in remote villages, but in dense urban centers. That shift is already reshaping the map of the world’s largest cities.

    Urbanization: Megacities

    For more than a century, humanity has been quietly reorganizing itself from villages into vast, dense cities. For example, in the 1800’s, only about 10% of the population lived in urban areas. Since 2014, over 50% of the world’s population has lived in urban areas – today it’s approximately 55%. That number is growing.

    Ironically, as we grow more digitally connected, our world is shrinking, and our populations are concentrating. 

    What Megacities Change: Power, Capital, and Talent

    An interesting consequence of this rapid urbanization and population growth in developing countries has been the increased development of Megacities – defined as cities with populations greater than 10 million.

    Today, there are 33 megacities – more than triple the number in the 1990s. They will increasingly anchor a disproportionate share of the world’s talent, capital, and innovation.

    This creates a set of interesting opportunities and challenges. 

    For example, how will these cities deal with infrastructure – sanitation, transportation, etc?

    Visual Capitalist’s graphic below ranks the world’s 50 largest cities from 1975 to 2050.

    an infographic showing the expected 50 most populous cities in 2050

    via visualcapitalist

    Today, in most high-income countries, about 80% of the population lives in urban areas, in contrast to the predominantly rural populations of lower-income countries. 

    As a result, we see many of these megacities forming in developing countries.

    At the same time, many high‑income countries face aging or even shrinking populations. That divergence — young, rapidly growing cities in emerging markets versus older, slower‑growing cities in developed markets — will shape everything from capital flows to immigration policy.

    Tokyo and New York helped define the last century of urbanization. Dhaka, Lagos, and Jakarta may define the next.

    Looking ahead to 2050, Dhaka is expected to become the world’s most populous city, with more than 52 million inhabitants, just ahead of Jakarta. Meanwhile, Africa emerges as the world’s fastest-growing urban region, accounting for 13 of the 50 largest cities.

    As a side note, we’re also seeing countries like China making substantial investments and alliances in these developing areas. This is likely done to profit from the expected growth and also to shift the future balance of power in their favor. Sometimes it makes sense to focus on the marathon rather than just the sprint.

    Demographics Meets AI

    As the world becomes more digitally decentralized and globally connected, our physical lives are concentrating into a relatively small number of megacities. Understanding where those cities are, and how they grow, is one of the most reliable ways to anticipate where opportunity — and risk — will cluster next.

    Over the next few decades, two forces will shape the playing field more than any others: where people live (demographics) and how they work (AI). As cities like Dhaka and Jakarta become powerhouses, it will force to rethink which places sit at the center of the global map.

    Over the next few decades, a handful of megacities will punch far above their weight in shaping markets, culture, and geopolitics. Not every megacity will thrive; governance quality, adaptability, and technology adoption will separate winners from cautionary tales.

    If most of the world’s growth concentrates in perhaps 50 megacities, what does a well‑positioned portfolio, business, or career look like — and how far is it from where you are today?

  • Here Are Some Links For Your Weekly Reading – February 22, 2026

    Doom & Gloom

    Lighter Links:

    Trading Links:

  • How To Detect Baloney with Carl Sagan: Trust, Tests, and Tiny Bets

    Information can glitter like gold — and still turn out to be worthless fool’s gold.

    Too often, organizations chase compelling narratives, market buzz, or charismatic claims instead of rigorous evidence. Decisions that matter need more than persuasion … they need proof.

    Carl Sagan had a name for the tools that keep you from falling for fool’s gold. He called it the “Baloney Detection Kit.” Sagan originally outlined them in The Demon-Haunted World (and they were recently summarized in Big Think ).

    A photo of Carl Sagan on a black background

    Collectively, they are a set of critical thinking tools to help separate fact from fiction. These ideas aren’t just for science; they form a solid foundation for any high‑stakes business decision.

    This post shows how to turn Sagan’s Baloney Detection Kit into concrete workflows, metrics, and tiny bets that make your organization more trustworthy and anti-fragile.

    Here are the basics.

    The Baloney Detection Kit

    At its core, the baloney detection kit pushes you to:

    1. Demand independent confirmation. Check claims with sources that weren’t involved in making them, while encouraging debate by all relevant experts.
    2. Avoid reliance solely on authority or persuasion. Experts can be wrong; evidence matters more than credentials alone.
    3. Create multiple hypotheses and test them. Don’t fixate on the first explanation; try to disprove competing ideas.
    4. Be your own fiercest critic. The hypothesis you like most is often the one you must test hardest.
    5. Quantify where possible and ensure every link in a reasoning chain holds up.
    6. Favor simplicity (Occam’s Razor) and insist that ideas be falsifiable — that there is some way to test whether they are wrong. The simplest answer is often the truth.

    Sagan’s emphasis is clear: skepticism is not cynicism — it’s a disciplined, systematic evaluation of evidence. Countless cognitive biases make stories appealing, but rigorous scrutiny separates what’s reliable.

    That’s powerful when you’re evaluating a news story or a scientific claim. It’s even more powerful when you wire it into how your organization decides what to do next.

    From Personal Skepticism to Organizational Practice

    These ideas are powerful personal tools, but they’re also powerful organizational frameworks.

    1. Tag every substantive claim before it leaves the building.
    Each claim gets a status like:

    • VERIFIED — independently checked
    • PRELIMINARY — plausible but unconfirmed
    • UNVERIFIED — high uncertainty
      Require visible flags and named reviewers before high-impact claims go public.

    2. Ask the “Stop Question.”
    For every major decision, answer:

    “What single observation would make us reverse course?”

    If you can’t articulate that, treat the initiative as exploratory.

    3. Document provenance for numbers.
    Every quantitative claim must list source, method, scope, and uncertainty in one place. Without that, weight it less in decisions.

    4. Build a structured decision workflow.

    • Author fills verification details.
    • Reviewer assesses evidence quality.
    • Senior Approver signs off on high-stakes items.
    • Rotating External Reviewer audits samples regularly.

    Track metrics quarterly, such as: % verified vs. unverified claims, time to verification, and errors caught in adversarial review.

    Why You Need A Risk-First Lens

    Most businesses get so excited about what could go right that they ignore what is most likely to go wrong.

    “What Could Go Wrong?“ is often a sarcastic throwaway, when it should be the most serious question you ask before any launch.

    We live in a speed-first world, but if speed is rewarded over accuracy, skepticism will be ignored.

    Culture and clear rules trump short‑term results, and prevent the attrition most ‘overnight successes’ experience.

    Can You Imagine …

    Imagine an organization where …

    Every bold claim carries its verified provenance …

    Where errors are corrected, not shamed, and publicly learned from …

    Where small but frequent probes guide larger tasks and keep them on the rails …

    Imagine the difference in the anti-fragility of that organization, or the longevity, or even just the trust and respect between employees.

    Ask yourself: What percentage of your important decisions are uncertain or unverified?

    The future rewards organizations that can quickly and reliably separate signal from noise.

    If you make testing basic, provenance visible, and tiny, reversible bets your default, you turn skepticism into a competitive edge — and persuasive stories into durable advantages.