Capitalogix

The Benner Cycle: How Not To Predict Markets

When I first became interested in trading, I would often consult many traditional sources and old-school market wisdom.  I particularly liked the Stock Trader's Almanac. 

While there is real wisdom in some of those sources, most might as well be horoscopes or Nostradamus-level predictions.  Throw enough darts, and one of them might hit the bullseye. 

Still, it seems better than using astrology to trade. 

Want something easy to predict?  Traders love patterns ... from the simple head-and-shoulders to Fibonacci sequences and the Elliot Wave Theory.

Here's an example from Samuel Benner, an Ohio farmer, in 1875.  That year, he released a book titled "Benners Prophecies: Future Ups and Downs in Prices," and in it, he shared a now relatively famous chart called the Benner Cycle.  Some claim that it's been accurately predicting the ups and downs of the market for over 100 years.  Let's check it out. 

 

 

Here's what it does get right ... markets go up, and then they go down ... and that cycle continues.  Consequently, if you want to make money, you should buy low and sell high ... It's hard to call that a competitive advantage.

Mostly, you're looking at vague predictions with +/- 2-year error bars on a 10-year cycle. 

However, it was close to the dot-com bust and the 2008 crash, so even if you sold a little early, you'd have been reasonably happy with your decision to follow the cycle.

The truth is that we use cycle analysis in our live trading models.  However, it is a lot more rigorous and scientific than the Benner Cycle.  The trick is figuring out what to focus on—and what to ignore. 

Just as humans are good at seeing patterns where there are none ... they tend to see cycles that aren't anything but coincidences. 

This is a reminder that just because an AI chat service recommends something, it doesn't make it a good recommendation.  Those models do some things well.  Making scientific or mathematically rigorous market predictions probably isn't the area to trust ChatGPT or one of its rivals ... yet. 

We're seeing bots improve at running businesses and writing code, but off-the-shelf tools like ChatGPT are still known for generating hallucinations and overconfidence. 

Be careful out there.

Market Growth in the First Half of 2025.

According to S&P Global, the U.S. market cap rose by 4.7% in the past 6th months. This represents a modest gain compared to the average market capitalization growth of 12.2% during the same period.

Leaders in growth were South Korea, Spain, Germany, Italy, and Brazil.

 

via VisualCapitalist

We have previously discussed this, but in addition to investments in technology and artificial intelligence, global capital is also being directed toward emerging markets, where many businesses are being established.

At first glance, some may see U.S. underperformance, but it can also be read as a sign of relative maturity and stability. Another potential perspective is that U.S. companies have already experienced explosive growth in recent years, particularly in sectors such as tech and AI, suggesting the market may currently be in a phase of consolidation.

While it's always great to see explosive growth, people undervalue resilience and steady growth, especially in light of the volatile first quarter of the year. 

Time will tell! 

 

Diminishing Returns in AI: The Most Common AI Mistake

At some point, more of the same stops paying off ... it is called the law of diminishing returns.

via Sketchplanations

Nature (and common sense) reminds us that equilibrium is important. For example, when you exercise too much, you get injured; when you drink too much water, you get poisoned; etc. 

This concept applies almost everywhere.

• It's why diversification is so important in portfolio construction theory. 
• Or, why you don't want to put all your eggs in one basket (concentrating your risk).
• And, my favorite, it's also why you shouldn't only eat vegetables.

A related nugget of wisdom from the extreme ... Too much of a good thing is a bad thing! 

And of course ... Be moderate in everything, including moderation.

A recent study on the effects of ChatGPT use on brain activity also supports this theme. 

via "Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task" 

The study divided 54 subjects into three groups, and asked them to write several SAT essays using ChatGPT, Google, or nothing at all. They used an EEG to record the writers' brain activity. ChatGPT users showed the lowest brain engagement. Over time, ChatGPT users got lazier. 

As a result, the ChatGPT essays also ended up lacking original thought and sounding similar. 

 

The paper suggests that the use of LLMs could harm learning and retention. The group that wrote without any help showed the highest neural connectivity, and higher brain activation in creativity ideation, memory load, and semantic processing. This group was more engaged and curious, and expressed higher satisfaction with their work. 

 

The paper hasn't been peer-reviewed yet and has a small sample size. 

Ultimately, I think it's telling us something we probably could have already guessed. If you're not actually the one reading or writing something ... you're not going to absorb the information as well. Your brain isn't going to activate as well. And if you're not finding other places to train your brain, you'll get worse at critical thinking. 

 

A few weeks ago, I wrote about my research process and how AI has both bolstered and hindered certain aspects of it. I'm casting a wider net, but going less deep. 

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. - via "Is AI Making Your And Your Team Smarter?"

This isn't a call to avoid AI or to slow down its development. It's a call to deliberation and intentionality. Students are flaunting that they're using ChatGPT to shirk the system. Companies are releasing AI-written copy not only on their websites but also in press releases. Humans are falling in love with chatbots and leaving their spouses. 

 

Meanwhile, AI is also the underpinning of countless enhancements and increased productivity. 

 

The same thing happened with the Internet. 

 

At a certain point, overreliance becomes a crutch, not a tool. 

 

I bet AI makes unintelligent and lazy people lazier and less intelligent. 

I'm positive it can make YOU smarter and more effective if you use it in moderation and to support your unique abilities. 

Onwards! 

Nature (and common sense) reminds us that equilibrium is important. For example, when you exercise too much, you get injured; when you drink too much water, you get poisoned; etc. 

This concept applies almost everywhere.

• It's why diversification is so important in portfolio construction theory. 
• Or, why you don't want to put all your eggs in one basket (concentrating your risk).
• And, my favorite, it's also why you shouldn't only eat vegetables.

A related nugget of wisdom from the extreme ... Too much of a good thing is a bad thing! 

And of course ... Be moderate in everything, including moderation.

A recent study on the effects of ChatGPT use on brain activity also supports this theme. 

via "Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task" 

My Artificial Intelligence Journey

Time seems to go faster as I get older. Likewise, technology seems to be advancing faster than ever, too.

Take AI as an example... even though I've been involved in this field for many years, I'm surprised by how rapidly it's improving now.

I suspect that part of the surprise comes from comparing the current pace of change to my memories of how long it took to improve in the past. Even though I had a sense of the quickening, the thing about exponential technologies is that there's a tipping point ... and clearly we're past that point on the curve.

I'm often met with surprise when I talk about my AI journey ... because it began in 1991, when it was still hard to spell AI.

Looking back, it makes a lot more sense to me than it did as I was moving through it. Here is a video about that journey and what it means for you and your future. 

 

Click here to view the transcript of the video.

Looking back on my life and career, one could argue that I got my start in AI with my most recent company, Capitalogix, which was founded over 20 years ago. Or, perhaps, we could go back further and say it started with my previous company, IntellAgent Control (which was an early AI company, focused on the creation and use of intelligent agents). By today's standards, the technology we used back then was too simple to be considered AI, but at the time, we were on the cutting edge.

Maybe we should go further back and say it started when I became the first lawyer in my firm to use a computer ... or was it when I first fell in love with technology? 

The truth is ... I've spent my whole life on this path. My fascination with making better decisions, taking smarter actions, and getting better results probably started when I was two years old (because of the incident discussed in the video).

Ultimately, the starting point is irrelevant. Looking back, it seems inevitable. The decisions I made, the people I met, and my experiences ... they all led me here.

However, at any point in the journey, if you asked, "Is this where you thought you'd end up?" I doubt that I'd have said yes. 

I've always been fascinated by what makes people successful and how to become more efficient and effective. In a sense, that's what AI does. It's a capability amplifier. 

When I transitioned from being a corporate securities lawyer to an entrepreneur, Artificial Intelligence happened to be the best vehicle I found to do that. It made sense then, and it makes sense now.

Like most things in life, it's easy to see the golden thread looking backwards, but it's a lot harder to see projecting forwards.

I wouldn't have it any other way. It certainly keeps things interesting.

Onwards!

Time seems to go faster as I get older. Likewise, technology seems to be advancing faster than ever, too.

Take AI as an example... even though I've been involved in this field for many years, I'm surprised by how rapidly it's improving now.

I suspect that part of the surprise comes from comparing the current pace of change to my memories of how long it took to improve in the past. Even though I had a sense of the quickening, the thing about exponential technologies is that there's a tipping point ... and clearly we're past that point on the curve.

I'm often met with surprise when I talk about my AI journey ... because it began in 1991, when it was still hard to spell AI.

Looking back, it makes a lot more sense to me than it did as I was moving through it. Here is a video about that journey and what it means for you and your future. 

 

Click here to view the transcript of the video.

Looking back on my life and career, one could argue that I got my start in AI with my most recent company, Capitalogix, which was founded over 20 years ago. Or, perhaps, we could go back further and say it started with my previous company, IntellAgent Control (which was an early AI company, focused on the creation and use of intelligent agents). By today's standards, the technology we used back then was too simple to be considered AI, but at the time, we were on the cutting edge.

Maybe we should go further back and say it started when I became the first lawyer in my firm to use a computer ... or was it when I first fell in love with technology? 

The truth is ... I've spent my whole life on this path. My fascination with making better decisions, taking smarter actions, and getting better results probably started when I was two years old (because of the incident discussed in the video).

Ultimately, the starting point is irrelevant. Looking back, it seems inevitable. The decisions I made, the people I met, and my experiences ... they all led me here.

However, at any point in the journey, if you asked, "Is this where you thought you'd end up?" I doubt that I'd have said yes. 

I've always been fascinated by what makes people successful and how to become more efficient and effective. In a sense, that's what AI does. It's a capability amplifier. 

When I transitioned from being a corporate securities lawyer to an entrepreneur, Artificial Intelligence happened to be the best vehicle I found to do that. It made sense then, and it makes sense now.

Like most things in life, it's easy to see the golden thread looking backwards, but it's a lot harder to see projecting forwards.

I wouldn't have it any other way. It certainly keeps things interesting.

Onwards!

Major Asset Class Performance Since 2020

Last week, we highlighted the growth of cryptocurrencies. This week, we're taking a look at the performance of various asset classes during the previous 5 years - including Bitcoin. 

To start, let's get a sense of where things stand year-to-date.

This has been a "strange" year. As someone who follows Markets, I'm still surprised by how many times I'm tempted to say that.

In addition, I'm also surprised by how well global assets have fared year-to-date.

Here's a high-level overview.

via CapitalSpectator.

After a seemingly significant string of losses, U.S. stocks experienced a surprising rebound in May, marking their first monthly gain since January. This upturn propelled U.S. equities to the top of the performance leaderboard among major asset classes during the month. The rally was driven by broad strength across global markets, though some segments, particularly bonds in developed markets, faced declines.

Equities and bonds typically have an inverse relationship. Recently, both markets have been reacting sharply — stocks up, bonds down. This dynamic reflects uncertainty. The market is balancing hope and fear simultaneously — hope in economic recovery and corporate earnings, and fear of tighter monetary policy.

Game theory suggests that the conflicting incentives between growth-focused and risk-averse investors create a dynamic equilibrium sustaining this paradox. However, this brings up an uncomfortable question for investors:

 

What if the erosion of bonds’ safe haven triggers a systemic liquidity crisis when protection is most needed?

 

That is where a longer-term lens is particularly helpful, both for providing context and offering insights into portfolio mix and diversification strategies.

The infographic illustrates how major asset classes performed each year over five years, highlighting the impact of external shocks and policy changes. It emphasizes the importance of diversification by showing how different assets respond uniquely to economic shifts, enabling investors to identify risks and opportunities in recent market cycles.

 

via Visual Capitalist.

Bitcoin has performed better than I expected during the past five years, attracting both institutional and retail investors. Meanwhile, gold has seen renewed interest as falling interest rates and easing political uncertainty have led some investors to seek safer assets, reflecting a shift toward lower risk tolerance in segments of the market.

It's interesting to see the dichotomy between these two asset classes and their growth, despite their almost inverse profiles. 

Meanwhile, 2025 has been a rocky year for many asset classes. If you like potentially meaningful (but likely meaningless) factoids, 2025 has seen the S&P 500's fifth-worst start to a year in history. 

It will be interesting to see how the rest of this year plays out. 

Is Crypto Going Mainstream in 2025?

Humans are good at recognizing significant changes on the horizon, but not nearly as good at understanding the second and third-order consequences of those changes.

A great example is the Internet. As it spread, most adults understood that it would bring “big changes”. However, even as a tech entrepreneur at the time, I didn’t fully grasp what the rise of the Internet would cause or make possible.

I feel the same way today about the rise of AI. It literally will change everything.

Close behind that is what’s happening in Crypto.  

 

Where Attention Goes, Money Flows

I don’t claim to be a crypto expert or fan. Historically, I’ve been skeptical and resistant on many levels. Nevertheless, I've always argued the blockchain was here to stay. Now, even Crypto seems to be becoming an inevitability.

Governments are becoming supporters. Regulators are falling in line. Big banks and industry are building infrastructure. New giants are forming. Coinbase recently joined the S&P 500. Circle just had a wildly successful IPO. And the performance of stocks like these hints at the growing market appetite for crypto businesses.

Currently, Crypto’s market cap is over $3 trillion. At the beginning of Trump’s presidency, the cryptocurrency markets experienced a significant surge. Since Donald Trump’s re-election in November 2024, Bitcoin has surged 60 percent, reaching record highs. However, Bitcoin isn’t the only cryptocurrency experiencing a surge; even meme coins are seeing a massive increase in value. 

Nevada recently hosted a Bitcoin conference, featuring speakers such as Vice President JD Vance, Trump’s two eldest sons, Donald Trump Jr. and Eric Trump, as well as White House crypto advisor David Sacks. 

Despite the growth (and Trump’s support), there are still mainstream obstacles ... obstacles that may be addressed by increased investment in stablecoins. For context, countries such as the UAE and Vietnam boast higher rates of cryptocurrency ownership than the United States. 

 

Stablecoins Are Rising

A stablecoin is a type of cryptocurrency designed to maintain a stable value, typically pegged to a reference asset like a fiat currency (e.g., U.S. dollar) or a commodity (e.g., gold). This contrasts with other cryptocurrencies, such as Bitcoin, which can experience significant price fluctuations. They serve many purposes, but ultimately believe they’re an interesting way to store value on-chain and take steps into the crypto world. 

The stablecoin market in 2025 is dominated by a handful of major platforms and issuers, recognized for their scale, transparency, and integration into both traditional finance and decentralized finance (DeFi) ecosystems. The two largest and most respected stablecoin platforms are Tether and Circle.

 

    Tether (USDT)

•Market Position: Tether remains the largest stablecoin by market capitalization, with over $140 billion in circulation and controlling more than 60% of the stablecoin market.

•Key Features: USDT is widely used across centralized exchanges, DeFi protocols, and global payment networks. It is primarily backed by U.S. Treasury bills and managed by Cantor Fitzgerald, providing a reserve base comparable to that of major national treasuries.

 

    Circle (USDC)

•Market Position: USDC is the second-largest stablecoin, with a market cap exceeding $60 billion.

•Key Features: Known for its transparency, Circle publishes weekly attestations of reserves, which are held in cash and short-term U.S. government treasuries.

 

Stablecoin funding is projected to 10X.

 

CBInsights via Voronoi

When cryptocurrency started to gain popularity, I expressed concerns about how banks and governments would resist widespread adoption until they could introduce regulation and gain control over it. I remember confidently saying that, throughout history, governments have always protected the right to print and tax coin. That is still true ... it just means something different to me, now, than it did when I said it.

I’m starting to pay more attention to Crypto, blockchain, and other emerging DeFi technologies.

I’m seeing an increasing flow of talent, opportunities, and resources to this space.

For example, major payment players like Mastercard and Visa are allowing stablecoin transactions and even creating their own coins. 

I do believe growth in stablecoins will also result in growth in other forms of cryptocurrency as well. 

For context, here are the best-performing cryptocurrencies of 2024. 

 

via VisualCapitalist

I still won’t pretend to be knowledgeable about the various coins, but I recognize that they are becoming more common and useful as speculation markets. 

All in all, I believe we are witnessing the birth of another blue ocean, and we can expect increased attention and investment to continue.

Onwards! 

Make Way For 2025's Biggest Unicorns

Billion-dollar startups are becoming increasingly common with VC funding surging, and an increased focus on exponential technologies. 

VisualCapitalist put together an infographic based on May's PitchBook that highlights the newest Unicorns.

If you are curious, PitchBook defines Unicorns as venture-backed companies valued at $1 billion or more after a funding round, until they go public, get acquired, or drop below that valuation.

Here is the list for 2025.

 

Pitchbook via visualcapitalist

Topping the list (and eclipsing every other company on the list) is Yangtze Memory out of China. They're focused on flash memory and solid-state drives. Yup, that's still a thing.

Also high on the list is Abridge, an American AI startup focused on turning doctors' conversations with patients into documentation. If you've ever talked with a clinician of any sort, you know how time-consuming documentation currently is. The combination of AI and longevity—or age reversal—is likely to become an increasingly hot area for investment.

Meanwhile, a rising tide floats many boats ... and with the continuing rise of funding in AI, you'll also find a growing list of AI unicorns, like Peregrine, Synthesia, AnySphere, Mercor, and The Bot Company. 

Although these individual companies are interesting, the larger trend is probably more significant. 

There have been 43 new unicorns in 2025 alone. And while the most profitable unicorns from 2024 are still OpenAI, ByteDance, and SpaceX, their competition is on the rise.

I've been a tech entrepreneur for decades, so I'm used to the constant march of progress. But this feels different. The pace is quickening!

We certainly live in interesting times!

AI: We're Not Just Prompts!

AI’s trajectory isn’t just upward—it’s curving ever steeper. From DeepMind’s groundbreaking models to Flow’s democratization of filmmaking, people are becoming used to how quickly AI technology improves.

 

Breakneck doesn’t even seem adequate to explain the scale of the movements. Because it isn’t just about the rate of change – even the rate of change of the rate of change is accelerating ... and the result is exponential progress.

 

Here is a simple example. Remember when you mocked AI-generated videos on social media for obvious flaws (e.g., six fingers, unnatural blinking or movement, etc.). Over the past few months, AI media quality has improved so much that spotting fakes is now difficult, even for tech-savvy people.

 

Well, we just took another giant leap.

 

This week, Google’s DeepMind unit released three new core AI models: Imagen for image generation,  Lyria for music generation, and Veo 3 for video generation.

It only takes a quick look at Veo 3 to realize it represents a significant breakthrough in delivering astonishingly realistic videos.

I’m only including two examples here ... but I went down the rabbit hole and came away very impressed.

Take a look – Everything in the clip below may be fake, but the AI is real.

 

via Jerrod Lew

The era of effortless, hyper-real content has arrived.

 

One of the big takeaways from tools like this is that you no longer need content creation talent other than your ideas.

 

An example of this comes from Google’s new AI filmmaking tool, Flow. 

What Is Flow?

What if creating professional-grade videos required no cameras, no crew, and no weeks of editing?

 

Flow can imagine and create videos just from your ideas. Kind of like telling a friend a story and having them draw or act it out instantly.

How Does It Work?

Think of Flow as a giant box of movie Legos. You can bring your own pieces (like pictures or clips) or ask Flow to make new pieces for you. Then, you snap them together to build scenes and clips that look like real movies.

Why Is This Cool?

It is becoming easier for almost anyone to create the type of content that only a specialist could produce before. The tool makes it easy in these three ways.

1. Consistent: The videos stick together well, so your story doesn’t jump around confusingly.
2. Seamless: It’s easy to add or change things without breaking the flow.
3. Cinematic: The videos look high-quality — like something you’d see on TV or in theaters.

If you want to play with it, it’s available to Google Ultra subscribers through the Gemini app and Google Labs. 

Ok, but what can it do?

Redefining “Real”

Don’t skip this next part. It’s what gave me the idea for the post.

To set the stage, imagine you’re watching a video of a person talking. Typically, you think, “This is real — someone actually stood in front of a camera and spoke.” But now computers can make a video that looks and sounds so real, you can’t tell it’s fake.

 

Anyway, this week, I saw a cool video on social media. At first, I thought it was cool simply because of the idea it expressed. But the video gets even more interesting when you realize how it was created.

 

“Prompt Theory” is a mind-bending exploration of artificial intelligence brought to life. The premise examines what happens when AI-generated characters refuse to believe they’re not real. From stunning visuals to synced audio, this video showcases AI’s new immersive storytelling power while examining some pretty trippy concepts.

 

Hashem Al-Ghaili via X

I predict you will see a massive influx of AI-generated content flooding social media using tools like this. 

Meanwhile, digital “people” with likenesses and internal objectives are increasingly going to become persistent and gain the ability to influence our world. This is inevitable. Yet, it’s still a little disorienting to think about.

 

As digital agents gain persistence and purpose, we face profound questions about reality, ethics, and human creativity.

 

And that is only the beginning!

 

Perhaps we are living in a simulation?

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!

The World Is Getting Older ... You Are Too

We're on the cusp of a major demographic shift. 

Fertility rates are dropping and life expectancy is rising, basically across the globe. On the surface, not explicitly bad. It's great that improvements in healthcare, technology, and quality of life are resulting in a larger senior population. 

 

via visualcapitalist

In 1980, the average person was 26.5 years old. Today, the average person is 33.6 years old. 

Meanwhile, population growth has halved in the same time period. 

Based on this chart, the global population would start declining in 2085, as the average age rises to 42. By 2100, the global population will begin declining. 

Of course, there's variation depending on the country. 

Most countries are thinking about how to increase fertility rates. If fertility rates decline, and your population lives longer, you end up with a larger percentage of the population that cannot or does not work anymore. That results in more expenditure - especially in pension and healthcare systems -  without an accompanying increase in GDP or productivity. 

It seems unlikely that something won't dramatically affect these trends over the next 60 years.

Even if expenditure becomes a non-issue, countries are unlikely to be happy with declining population growth, in part because of declining production resources and tax income, but also because of diminished global power. 

What do you think?