Capitalogix

Business Lessons from the NFL

Today was Super Bowl Sunday 2025. As a fan, I found myself rooting for the Philadelphia Eagles today. But at times, I was rooting for Patrick Mahomes and the Chiefs out of respect for the talent and the incredible record they’ve compiled.

Meanwhile, it also made me think about my home team, the Dallas Cowboys, and how long it’s been since we’ve had any real post-season success. 

Obviously, the Jones family has done many things right. According to Forbes, for the ninth straight year, the Dallas Cowboys are the world’s most valuable sports team, worth an estimated $10.1 billion — the first to cross the 11-figure threshold and $1.3 billion beyond their closest competition.

They’ve mastered winning in the business sense, even when they struggle on the field.

Jerry Jones does a lot right in building his “Disney Ride.” However, this post will focus more on what the coaches and players do to win. 

 

Business Lessons From the NFL

 

I’m regularly surprised by the levels of innovation and strategic thinking I see in football.

Football is something I used to love to play. And it is still something that informs my thoughts and actions.

Some lessons relate to teamwork, while others relate to coaching or management.

Some of these lessons stem back to youth football ... but I still learn from watching games – and even more, from watching Dallas Cowboys practices at The Star. 

Think about it ...  even in middle school, the coaches have a game plan. There are team practices and individual drills. They have a depth chart listing the first, second, and third choices to fill specific roles. In short, they focus on the fundamentals in ways that most businesses don’t.

The picture below is of my brother’s high school team way back in 1989. While lots have changed since then, much of what we will discuss in this post remains timeless.

 

 

Losing to an 8th Grade Team

The scary truth is that most businesses are less prepared for their challenges than an 8th-grade football team. That might sound disrespectful – but if you think about it ... it’s pretty accurate. Here is a short video highlighting what many businesses could learn from observing how organized sports teams operate, particularly in setting goals and effectively preparing for challenges.

via YouTube.

If you are skimming, here is a quick summary of the key points in the video.

Organization and Preparation

• Structure: Football teams have a clear hierarchy, including a head coach, assistant coaches, and trainers.
• Practice: Teams engage in regular practice sessions to prepare for games, emphasizing the importance of training.
• Game Plan: They develop strategies and a game plan before facing opponents, including watching game films to understand their competition.

Dynamic Strategy

• Adaptability: Teams adjust their strategies based on the game’s flow, recognizing whether they are on offense or defense.
• Audibles: Just as a football team may call an audible when faced with unexpected defensive setups, businesses should adapt their strategies in real time.

Learning From Experience

• Post-Game Analysis: Coaches review game films to identify what worked and what didn’t, learning from past experiences to improve future performance.
• Continuous Improvement: Ongoing training is crucial in businesses, similar to how football players receive coaching during practice to enhance their skills.

Importance of Coaching

• Role of Coaches: Coaching is crucial for developing talent and focusing on achieving defined goals.
• Encouragement of Growth: Active coaching leads to better outcomes and overall improvement.

 

A Deeper Look Into the Lessons

There is immense value in the structured coaching and preparation that sports teams exemplify. Here are some thoughts to help businesses adopt similar principles that foster teamwork, adaptability, and continuous improvement.

Vince Lombardi once famously started training camp by announcing, “Gentlemen, this is a football.” He stressed the hidden power of mastering the fundamentals. Beyond that, he believed that how you do something is how you tend to do everything ... which led to his famous  quote, “Football is not just a game, but a way of life.”

So, let’s start at the beginning.

Football teams think about how to improve each player, how to beat this week’s opponent, and then how to string together wins to achieve a higher goal.   

The team thinks of itself as a team. They expect to practice. And they get coached.

In addition, there is a playbook for both offense and defense. And they watch game films to review what went right ... and what they can learn and use later.

Contrast that with many businesses. Entrepreneurs often get myopic ... they get focused on today, focused on survival, and they lose sight of the bigger picture and how all the pieces fit together. 

The amount of thought and preparation that goes into football - which is ultimately a game - is a valuable lesson for business. 

What about when you get to the highest level? If an 8th-grade football team is equivalent to a typical business, what about the businesses that are killing it? That would be similar to an NFL team. 

Let’s look at the Cowboys. 

 

Practice Makes Perfect

How you do one thing is how you do everything. So, they try to do everything right. 

Each time I’ve watched a practice session, I’ve come away impressed by the amount of preparation, effort, and skill displayed.

During practice, there’s a scheduled agenda. The practice is broken into chunks, each with a designed purpose and a desired intensity. There’s a rhythm, even to the breaks.

Every minute is scripted. There’s a long-term plan to handle the season ... but, there was also a focus on the short-term details and their current opponent.

They alternate between individual and group drills. Moreover, the drills run fast ... but for shorter periods than you’d guess. It is bang-bang-bang – never longer than a player’s attention span. They move from drill to drill, working not just on plays but also on skill sets (where are you looking, which foot you plant, how to best use your hands, etc.).

They use advanced technology to get an edge (including player geolocation monitoring, biometric tracking, medical recovery devices, robotic tackling dummies, and virtual reality headsets). 

They don’t just film games; they film the practices ... and each player’s individual drills. Coaches and players get a personalized cut on their tablets when they leave. It is a process of constant feedback and constant improvement. Everything has the potential to be a lesson. 

 

Beyond The Snap

The focus is not just on the players and the team. They focus on the competition as well. Before a game, the coaches prepare a game plan and have the team watch videos of their opponent to understand tendencies and mentally prepare for what will happen.

During the game, changes in personnel groups and schemes keep competitors on their toes and allow the team to identify coverages and predict plays. If the offense realizes a play has been expected, they call an audible based on what they see in front of them. Coaches from different hierarchies work in tandem to respond faster to new problems. 

After the game, the film is reviewed in detail. Each person gets a grade on each play, and the coaches make notes for each person about what they did well and what they could do better.

Think about it ... everyone knows what game they are playing ... and for the most part, everybody understands the rules and how to keep score (and even where they are in the standings). Even the coaches get feedback based on performance and look to others for guidance. 

Imagine how easy that would be to do in business. Imagine how much better things could be if you did those things.

Challenge accepted.

And, just for fun, here’s a video of me doing a cartwheel after a Dallas Cowboys win.

 

via YouTube.

Sports make you do funny things.

Whether you are watching or playing – Enjoy the game!

Here Are Some Links For Your Weekly Reading - February 9th, 2025

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

Lighter Links:

• OpenAI's Deep Research Smashes Records for the World's Hardest AI Exam, With ChatGPT O3-Mini and DeepSeek Left in Its Wake. (TechRadar)
• You Can Try DeepSeek’s R1 Through Perplexity—without the Security Risk. (FastCompany)
• The Recruitment Effort that Helped Build Elon Musk’s DOGE Army. (Wired)
• Humans are Evolving Before Our Eyes on the Tibetan Plateau. (ScienceAlert)
• How to Naturally Boost Your Dopamine, Oxytocin, Serotonin, and Endorphins. (FastCompany)

 

 

Trading Links:

• The True Cost of a Super Bowl Ad? You Don’t Want to Know. (FastCompany)
• Trump Says America Was at Its Richest in the Late 1800s. Is That True? (MarketWatch)
• The “5 Types of Wealth”: Why You’re Wealthier Than You Think. (BigThink)
• America’s Most Generous Philanthropists 2025. (Forbes)
• Why the AI World is Suddenly Obsessed With a 160-Year-Old Economics Paradox. What Is It – And What Does It Mean Today? (NPR)

 

 

My Thoughts on Deepseek as an AI Entrepreneur & Hedge Fund Manager

Every now and then, a moment comes along that forces everyone to stop and rethink what they thought they knew. DeepSeek—a relatively unknown AI startup—just delivered one of those moments.

Imagine this: last week, a company most people had never heard of claimed to have built a cutting-edge AI model for just $5.6 million – and they made it open source. Meanwhile, industry giants like Meta, Google, and OpenAI spend hundreds of millions—sometimes billions—on similar efforts. The implications are massive, and investors felt it immediately.

Within hours, Nvidia’s stock price plunged 16.86%, wiping out over $600 billion in market value. Other AI-heavy stocks followed suit. The reaction? Panic, speculation, and a flood of questions:

• Have we been overpaying for AI development?
• Is brute-force scaling the wrong path?
• What does this mean for the balance of power in the AI world?

What’s happening here isn’t just a new startup making waves. It’s a fundamental shift in how AI is built—and it could change the competitive landscape for years to come.

What makes DeepSeek different?

To me, the main point is that, until recently, AI companies have been treating LLMs like an arms race—the more GPUs, the better. That’s part of why LLMs have become so expensive. Meanwhile, DeepSeek took an efficiency-first approach that reduced computational waste and more efficiently used GPU resources.

This type of disruption will become increasingly frequent across all industries. Exponential technologies are accelerating innovation cycles and opening unexpected development paths. While these discontinuous innovations may seem like isolated surprises, they’re becoming a fundamental part of the competitive landscape. The key isn’t to react to each disruption individually - it’s to develop better strategies for operating in this rapidly evolving environment.

In this case, Deepseek’s breakthrough wasn’t about doing more of what its competitors were good at. Instead, they thought of something else they could do to well to compete. Their breakthrough wasn’t about power ... it was about perspective. It is a good reminder and blueprint to study.

Some think the key message is that businesses no longer need to stock up on Nvidia’s best GPUs to have an advantage. Even if that is true, it begs the question: Will the demand for high-end GPUs decline if AI processing needs start shrinking? Asked another way, if other AI companies also use efficiency-first architecture, will Nvidia’s dominance weaken?

From my perspective, the answer is that Nvidia will continue to grow. I’m excited about a world where the companies that can afford to spend the most money don’t necessarily win. Increased accessibility to high-performing AI models means more entrepreneurs can join the space and create new businesses with novel approaches. Ultimately, many more businesses will build AI into their infrastructure, and chip sales will continue to expand.

AI isn’t just about computing power anymore – it’s about creativity and utility, too. Constraints have always bred innovation, and as companies begin to do more with less, I think you’ll see a shift in the balance of power.

What about America and data privacy?

Despite my excitement about the AI boom, there are valid privacy fears. When I discussed TikTok a few weeks ago, it was clear that the U.S. was taking a stronger stand on protecting its citizens from foreign interference. DeepSeek presents challenges.

To start, it does censor content deemed sensitive by the Chinese government – that also means that particular historical and political topics are met with ambiguous or sanitized responses.

It collects all of your user inputs, any personal information you share, and technical details like your keystroke patterns. They do explicitly tell you this in their Terms of Service. The data is stored in China, raising concerns about legal oversight and privacy laws.

You likely have very little recourse if your data is accessed by or shared with external entities.

My Thoughts

First, DeepSeek is undoubtedly exciting. Even if they’ve embellished their story, the result is impressive. However, it’s also not the end of Nvidia or American-based AI companies. 

Knowing when to sprint and when to jog is an important skill.

AI is shaping our digital world, and DeepSeek is a massive force function in the industry. It is ultimately a good thing for AI (yes, even the Chinese competition).

However, you should probably ask yourself if the benefits of using Deepseek outweigh the risks.

When I coach people on using generative AI, I’ve always urged caution about sharing your sensitive IP with publicly hosted GPTs. Even with OpenAI or Meta, there are clear risks.

It’s also clear that China isn’t the only entity trying to track you or better use your data. As a reminder, if you don’t know how someone is making money off a product … you’re the product. They’re commoditizing you and your data.

That being said, It’s important to be proactive, and it seems to become even more important every week. The landscape is shifting so quickly.

Even so, you have time.

Being proactive also means being smart. As a user of the tools, you don’t need to switch to DeepSeek. Even as a non-tech entrepreneur, now is the time to explore the AI uses that excite you, not to force big leaps. 

If you’re like me and are an entrepreneur in the space, you should certainly take the lessons from DeepSeek and think about how to apply these ideas in your ecosystem.

But my #1 lesson for AI adoption is the same as my #1 lesson for building any habit: Start small - and start in a way that gives you energy.

Humans are good at seeing big changes on the horizon but notoriously bad at predicting what those changes will be.

The goal isn’t to be so fast that you beat everyone else … just to be fast enough not to be left behind.

Onwards!

Carl Sagan's Foresight from 1996

Carl Sagan was an astronomer and planetary scientist whose most enduring legacy lies in his extraordinary ability to communicate complex ideas to the general public.

Shortly before his death, he participated in an oddly prescient interview about short-form media and public attention. It is worth clicking to hear his clear thoughts about how governments will use ignorance of science and technology to control people.

 

via YouTube

He goes into more detail about this topic in his book, The Demon-Haunted World: Science as a Candle in the Dark."

“I have a foreboding of an America in my children’s or grandchildren’s time—when the United States is a service and information economy; when nearly all the key manufacturing industries have slipped away to other countries; when awesome technological powers are in the hands of a very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness ... the dumbing down of America is most evident in the slow decay of substantive content in the enormously influential media, the 30 second sound bites (now down to 10 seconds or less), lowest common denominator programming, credulous presentations on pseudoscience and superstition, but especially a kind of celebration of ignorance."  - Carl Sagan, The Demon-Haunted World

With the national outcry at TikTok's ban being upheld in the Supreme Court, this feels even more relevant. 

With TikTok, Instagram Reels, and YouTube Shorts, even 30 seconds of attention sounds generous. Smooth-sounding AI-generated slop only makes it worse.

In many ways, we've even forgotten how to be appropriately skeptical. It's not enough to question authority and look for trusted evidence; you must also question their detractors and replacements. Laziness and ignorance rarely lead to good outcomes.

There is room in life for faith, optimism, and belief. But when you question what's being pushed toward you, how influenced are you by your existing biases and beliefs? It's hard to reason someone out of a position that they did not reason themselves into. 

Do you think America is becoming more or less ignorant? If more, what do you think it would take to reverse that trend?

The Reverse Turing: Advanced AIs Trying To Figure Out Who Is Human

The Turing Test, originally called the Imitation Game, tests a machine's ability to emulate a human. Developed in 1949, it is still a relevant test for AI. The Turing Test measures both knowledge and the ability to express it in a manner indistinguishable from a human response.

There is no agreed-upon definition for intelligence, so we can only approximate what skills we test AI on. 

While many people still believe they can tell when an AI has written something, several LLMs (like ChatGPT) have passed modern versions of the Turing Test. Many, including me, would argue LLMs still can't consistently pass the test. 

But what about the alternative? Could you convince an AI that you're not human?

Recently, a video went viral, showing a human pitting himself in VR against an AI version of Aristotle, Mozart, Leonardo da Vinci, Cleopatra, and Genghis Khan (who was played by a human).

 

via Tore Knabe

To set up the test, the human scripted the beginning and end of the dialogue and gave the AI agents a full transcript of the conversation up to that point. The entire video then played out in one recording, with no cuts.

In this "reverse" Turing test, the chatbots were scripted using various LLMs, asked questions, and then challenged to guess who the human was. Tore Knabe, the virtual reality game developer who devised the test and played the Genghis Khan role, answered one of the questions with a quote from Conan the Barbarian. 

"What a leader should do is to crush his enemies, see them driven before him, and hear the lamentations of their women."

Listening to his stuttered response, contrasted by the clunky and verbose AI responses, makes it very apparent to us, the audience, that he's human. The machines voted three-to-one that his response wasn't "nuanced or strategic" enough to represent an AI modeled on Genghis Khan's exploits. To ease your mind about hidden variables, the AIs weren't processing his voice directly. The audio was transcribed and sent to the AIs as text. 

Ultimately, this is a flawed test, and we don't really know how much of this is an actual test (versus just entertainment). In any case, it's still an interesting thought experiment. 

Do you think you could fool an AI? What if you had time to craft a response without penalty? What if your life was on the line?

For a bonus, here's a social Turing game where you can chat with someone for two minutes and try to figure out if it is a human or an AI. 

We live in interesting times!

How AIs (Like ChatGPT) Learn

I first wrote about this video a few years ago, when artificial intelligence first captured the media's attention. Back then, we were impressed that algorithms could help you pick out your Christmas gifts on Amazon, suggest new music for you on Spotify, and do their best to capture your attention on websites. 

AI is seemingly everywhere now. And what is surprising to me isn't its prevalence or impact ... it is the speed and breadth of its adoption. Last night, at an early holiday dinner, we talked extensively about how easy to adopt and how accessible tools like ChatGPT are (and almost none of us were Nerds). 

With all that being said, I think it's wise to have a basic understanding of the things that most impact our lives. Even if you're not a big fan of AI, understanding its growing powers will benefit you. 

The video below is a bit simple in its explanations, but it describes some fundamental concepts worth understanding.

 

CGP Grey via Youtube

The video is engaging and easy to understand. It focuses on genetic algorithms (which is one type of machine learning) and ignores some of the other more complicated techniques and approaches. For example

In my experience, it is more useful for an executive to understand what tools like this can do rather than how they work. Likewise, it is better to understand when to use tools like this rather than knowing precisely how to use them. But, a cursory understanding like this video still adds value. 

As machine learning gets more complicated and evolves, it gets harder for humans to assess their output or process accurately. Here is something to consider:

How do you know that the answer it gives is the answer you seek?

Just because an algorithm responds quickly and confidently doesn't mean it's right.

While bots can deliver impressive results, their decision-making processes can be opaque. This presents both a risk and an opportunity. Artificial intelligence seems cool, but artificial stupidity is scary ... and making mistakes at light speed rarely results in good outcomes.

It's human nature to feel safer when we understand something. It's human nature to envision machines making human-like decisions, just faster. But we are quickly going beyond that ... way beyond that!

In the past, algorithms were static while data changed. But now we're in a different world - one where the algorithms themselves evolve and dramatically adapt to handle different types of data. While this might sound like a subtle distinction, it represents a fundamental shift in how AI systems learn and operate.

One of the challenges of understanding exponential technologies is that their progress isn't linear. This makes it difficult for humans to accurately gauge how rapidly these tools will advance in capability. As algorithms grow more complex, they will increasingly operate in ways that may not be fully understood by their developers (and even less so by their users). As a result, we'll likely find ourselves using AI to solve problems and accomplish tasks that aren't even on our radar today. 

It might sound strange, but it doesn't matter why a bot makes a decision or what inputs it uses to make the decision. What matters is whether it accomplishes its goal and how its performance and level of decision-making rank in relation to its prior performance and other options (and, perhaps, whether the bot is biased).

Part of what makes artificial intelligence exciting is that it can do a lot of things well that humans are really bad at. And, even when you're using an AI in your domain expertise, it can be a great first step to save you time and effort. 

It's a brave new world, and not only is Big Brother watching, but algorithms are, too.

Live long and prosper!

Why Leave The House When You Can Shop Online ...

The holidays are almost here! Time's running out to get your gifts in time. 

Luckily, it's never been easier to get stuff. On top of online shopping, Amazon has stewarded the switch to almost instantaneous shipping. 

I remember when malls were filled to the brim, and Black Friday led to stampedes and people dying. Now, it's brick-and-mortar stores that are dying.

Not only are the in-store deals not as good, but the best deals are online. Here's a chart showing the surge of online shopping.

 

via visualcapitalist

Online shopping now accounts for about 15% of consumer spending, up from 4.1% in 2010. 

In addition, Q4 always sees a massive spike, with online spending accounting for 17.1% of consumer spending in 2023. 

This year, Cyber Monday attracted over 64 million U.S. shoppers, three times the number who shopped in stores. 

You can find change everywhere, but one place to look hasn't changed. Amazon is all about infrastructure and disruption. 

• Amazon announced Rufus, a new generative AI-powered conversational shopping experience.
• Amazon announced a way to get your prescriptions online faster and cheaper than a traditional pharmacy.
• Now, you can even buy cars on Amazon.

It's interesting to consider how drastically this changes supply chain management. People now expect free and fast shipping and the ability to return items if they don't work out (instead of trying them in-store). Meanwhile, brands have high fixed costs due to their existing retail locations, yet they need to keep most of their stock in warehouses instead of their box stores to deal with the surplus of online orders. 

We're already seeing the failure of malls and the bust of commercial real estate. If this trend continues of work-from-home and online shopping, we could see a $250 billion decrease in commercial property value by 2026.  

What do you think it would take to stop the bleeding and encourage both consumers and employees to leave their homes?

Futurism and The Epidemic of Impossible Statistics

I can’t pretend this is a new phenomenon, but I also can’t pretend it’s not becoming a pet peeve of mine. 

If you’ve been following me for any amount of time, you’ll know I love the future, and I love random statistics. If I’m not talking about AI or entrepreneurship, it’s generally because I’m sharing some interesting chart or statistic. 

At the intersection of my two loves comes a pretty severe issue ...

Bullshit statistics. 

Futurists can’t help themselves. If you repeat something enough times, it begins to feel true. This is a key part of the reality distortion field that surrounds charismatic leaders. Their “functional fiction” becomes useful - not because it’s grounded in fact, but because it enables us to envision what’s possible and work to make it real.

In their defense, nobody minds if you talk about the future broadly. However, a problem arises when directional belief masquerades as fact or science. For example, if someone has thought about something many times, there is a tendency to confidently discuss or project exponential growth with specific timelines and metrics (rather than broadly discussing what will eventually come).

This tendency can make intelligent people seem delusional (or at least out of touch).

Elon Musk is a great example. While he has undeniably been a significant force for innovation and progress in the world, here are a few of the outlandish claims he’s made recently.

• “I think by 2040, probably there are more humanoid robots than there are people.”
• “I feel comfortable saying that AI is getting 10 times better each year.”
• Or, his 70% chance of moving to Mars, and his expectation of colonization starting in 2029.

Some of those may be true, and all of them might turn out to be right ... but they are still wild-ass guesses.

Elon is by no means the only one doing this. 

I routinely make up statistics to help me simplify or understand things better. The key is to acknowledge these “shortcuts” are still essentially educated guesses. Here’s an example. When I imagine how advanced AI will become by the end of my lifetime, I have to consider my current age (and expected lifespan) and how rapidly AI is improving. If I assign the number “100” to how good AI will be at the end of my life, what value would I assign to it now? Turns out, I’d give it a value of three. Of course, there’s always the possibility I could get hit by a bus tomorrow. I’m not a scientist. I haven’t done detailed research about chips or when we move to quantum computing. Realistically, I don’t have to. The precise numbers aren’t what matters here. I don’t take that statistic literally. It’s directional, and it gives a sense of the rate of change and the velocity of invention. In that sense, even though it isn’t factual, it’s useful.

I’d say any serious scientist knows that you can’t reliably predict the future with that level of precision – but it doesn’t take a scientist to know that. 

First, the statistic or shortcut has to pass a simple “sniff” test. Then, you have to account for likely bottlenecks or constraints. Too many of these crazy estimates assume almost infinitely scaling results with no setbacks or limitations in materials or energy. 

Don’t underestimate the value of a good rule-of-thumb or mental model. Moore’s Law is a great example of that. It stemmed from an observation and prediction about the semiconductor industry made by Intel co-founder Gordon Moore in 1965. A grossly simplified version is that computing power doubles every two years. That has held true for more than 50 years.

I have two Gaping Void illustrations that express fundamental truths about this: “First, Bring Order to Chaos” and “Wisdom Comes from Finer Distinctions.”

Here’s the reality. The future is exciting ... and it’s coming fast. In many ways, it will likely be bigger and cooler than you could have imagined. In other ways, it will radically underperform your expectations. 

I can say that not because I know any more than you, but because I’m focused on what doesn’t change. We’ve had many periods of innovation ... each bigger than the last. It’s likely there will be aspects of the next 20 years no one can predict. But, we know what innovation looks like. 

We’ve been here before. 

As a reminder, if it sounds too good to be true ... there’s a good chance it is. Yet, to pretend there’s not a chance outlandish claims will come true would be to make too precise a claim again. 

In many ways, predicting how your business or product will change is much easier than how the world will change.

The best way to predict the future is to create it - and the most effective way to create it is to focus on the elements within your control.

While it’s important to play an exponential game ... you can start “locally”. 

Food for thought! 

Part 2: Using ChatGPT's Advanced Voice Capabilities to Draft a Blog Post on Exponential Technologies

In part 1 of this post, I played around with ChatGPT’s new Advanced Voice Mode. I used it to create an article with essentially no editing, showing how quick and easy using the tool was. This time, I’ll redo that process, emphasizing the prompts used to interact with the AI. Then, I will add some additional prompts to refine the writing. Creating an article this way was dramatically quicker and easier than our typical process. And it’s pretty surprising to see the level of quality content that you can produce with the current state of the technology and relatively minimal effort.

This image was created using X’s Grok AI to pair with this article.

What follows is the transcript from my chat with Advanced Voice Mode, with only light editing and formatting to provide better insight into the process and its outputs.

 

“I want to write an article about how exponential technology will change life and business. Can you ask me questions until you have enough information to create an outline? And then I’ll give you some other topics, and you can ask me more questions until you have enough time to write the article.”

00:22

Great, let’s dive in! First, for the article on exponential technology, could you share what specific areas of life and business you want to focus on? Are there any particular technologies or industries you find most intriguing? This will help shape the direction of the outline.

“Yeah, I am the CEO of an AI platform company, and I tend to communicate with entrepreneurs, senior executives, and investors, and I’m primarily talking about AI.”

00:15

Great, focusing on AI makes a lot of sense given your background. Let’s narrow it down further. Are you interested in exploring how AI impacts specific industries, like finance or digital media? Or would you rather discuss broader themes, such as AI’s role in transforming business operations, customer experiences, or decision-making processes?

“It started in areas like finance and digital media, but it will impact broader areas.”

00:12

Great point! We can explore how AI began transforming finance and digital media and is now set to revolutionize various other sectors. We could highlight emerging trends and future possibilities in healthcare, education, retail, and more. How does that sound for the article’s direction?

“Sounds fine, but I also want to discuss how it will change everything. AI isn’t just another technological advancement; it’s a fundamental shift transforming the very fabric of our lives. It’s something different ... because it’s no longer just about the technology itself, but the adoption and what it creates and makes possible.”

00:16

Absolutely, AI’s impact hinges on how it’s adopted across industries and societies. It’s this integration into daily life and business that will truly redefine our future. Should we explore examples of this adoption and its potential to change everything?

“Yeah, and I think we ought to talk about how fast OpenAI got ChatGPT to a million users, and then to a hundred million users ... and the fact that it’s not only that the users are playing with the technology, it’s that the companies now have data about what people are trying to do and what they’re having challenges doing, and it’s literally giving them a roadmap of how to eliminate constraints faster and create what comes next at unprecedented speed and rates of change.”

00:21

The rapid adoption of ChatGPT highlights not just public interest, but also the potential for businesses to harness user data. This provides invaluable insights into user needs and pain points, effectively offering a roadmap for innovation. Shall we delve into how this data-driven approach is reshaping business strategies?

“Yes, and let’s do that at a high level and then pose a challenge to the user saying, you don’t have to figure out how to use the current state of technology today ... It’s more important for you to build the muscle about thinking about how tools like this are going to help you build what you want to create for tomorrow.”

00:22

That’s a powerful perspective. Let’s summarize the high-level implications of AI adoption and then challenge readers to think beyond current capabilities. By building a mindset geared towards leveraging AI for future opportunities, they’ll be better positioned to innovate and stay ahead in a rapidly changing landscape.

“I think that’s great. On a separate note, not related to the article, can you speed your voice up by like 0.25?”

00:10

Sure, I can do that. How does this sound?

“I also need you to increase the delay when you’re waiting for me to talk, because I’m someone who thinks and then talks. But I want you to talk a little bit faster like that, and that will seem much more natural for me when brainstorming.”

00:18

Got it! I’ll speak a bit faster and give you more time to think before jumping in. Let’s keep the brainstorming going. What other topics are on your mind for articles?

“I think that agentic processes are poised for the next big wave of innovation. And as much as everybody’s going to start to hear about it, it’s going to follow Gartner’s hype cycle, where we’re going to create inflated expectations and excitement ... but then have a trough of disillusionment as people find that it’s harder to do than they expected. As a practical aside, my company has created an autonomous trading system. In the beginning, we thought it was about trading better ... but it’s really about figuring out the myriad of ways that life gets in the way – from power failures, internet outages, fires in the server room, and geopolitical events. But the real issue is figuring out how to make something work reliably even in the face of errors, competition, mistakes, and bad luck.”

00:50

That’s a fascinating shift in perspective. It really underscores the importance of resilience and adaptability in AI systems. Do you think exploring these real-world challenges in an article could offer valuable insights for others in the tech industry? It seems like it could be a great way to share your expertise.

“Yeah, I just think we have to do that somewhat superficially, so that they think about some of the challenges but then realize that the right thing to do is partner with somebody who’s already figured it out.”

00:14

That’s a smart approach. You can introduce the complexities of implementing AI, just enough to highlight the challenges, and then pivot to the value of partnering with experts who have navigated these obstacles. This could position your company as a trusted guide in the AI landscape. How does that sound as a direction for your article?

“It sounds good. However, you’ve gone back to speaking slowly again. I don’t know if some human is reading the transcript, but you were doing great, and now you’re back to your original pace.”

00:19

I’ll keep the pace up. It sounds like you’re all set. What else would you like to cover?

“That Natural Language Processing has become a key component of AI innovation. It’s amazing how it’s changing how humans interact with computers or access AI capabilities. It used to be that you needed to be good at prompt engineering, but companies like OpenAI have figured out how to interpret simple requests and build a more detailed prompt behind the scenes, so you’re still getting the benefit of prompt engineering without having to become an expert at it yourself. A simple example is the difference between the response to a prompt simply consisting of the word “Improve – and (then a sentence)” six months ago, versus what you’ll get today. And the same is true for a simple image prompt. The result you would have gotten six months ago is vastly different than what you’ll get today because the tools and technologies and multimodal capabilities are working together beneath the surface to create a much more robust and resilient and capable answer engine.”

01:06

That’s a great observation. The evolution of AI is making it more accessible, allowing users to focus on their needs rather than the technicalities. This progress opens up new opportunities for innovation and creativity, as users can leverage AI’s capabilities more efficiently, effectively, and easily.

“OK, do you have enough information to create a basic outline?”

00:04

Absolutely! Here’s a basic outline for your article:

 

Title: Navigating the AI Revolution: From Exponential Technology to Practical Applications

I. Introduction

• The rapid growth of AI and its transformative impact on life and business.
• Brief overview of AI’s origins in industries like finance and digital media.

II. Exponential Technology in Business

• How AI is revolutionizing various sectors, including healthcare, education, and retail.
• AI’s role in reshaping business operations, customer experiences, and decision-making.

III. The Role of Natural Language Processing (NLP)

• The evolution of NLP in making AI more user-friendly.
• How companies like OpenAI simplify complex requests, enhancing user experience.

IV. Real-World Challenges and Resilience in AI

• Introduction to the challenges of implementing AI systems, using autonomous trading as an example.
• The importance of resilience and adaptability in AI, focusing on overcoming real-world obstacles.

V. Data-Driven Innovation

• How user data from AI applications provides insights for

 

“Your outline is fine. Please generate a rough draft. Please use some quotes, headlines, subheads, and bullets. I like structure in the article. And please end with a conclusion.”

00:17

Absolutely. Here’s a rough draft with the structure and formatting you requested.

 

Note: The entire conversation with ChatGPT’s Advanced Voice Mode occurred during a casual neighborhood walk lasting 10-15 minutes. I made no effort to rush the process - it was simply a natural dialogue with my handphone that concluded before I returned home. At this point, ChatGPT generated a draft of the article that was okay, but similar to last time. It didn’t really reflect our style to the level that would make us happy. So, I asked ChatGPT to rewrite the draft using my voice, tone, and style. To accomplish this, I provided five examples of previous articles and instructed it to analyze the voice, tone, and style ... and to generate a prompt that mimics those characteristics. I then returned to the original conversation where ChatGPT had provided its draft and requested it to rewrite the content with those instructions. Here is the output.

 

Navigating the AI Revolution: Bridging Exponential Technology with Practical Application

Imagine a world where artificial intelligence, once the stuff of sci-fi dreams, shapes the foundations of our daily lives and businesses. What began as a tool in niche sectors like finance and digital media now pulses through healthcare, education, and retail, each industry redefining its approach to productivity, decision-making, and even creativity. Yet, while AI’s exponential growth makes headlines, the real story often lies in the complex journey of making these systems resilient and truly reliable on a large scale.

This image was created using X’s Grok AI to pair with this article.

AI’s potential doesn’t just come from its incredible computational speed; it’s about adaptability—learning as it goes. Think of the impact it’s having in healthcare, where AI diagnoses diseases earlier and personalizes treatments, or in retail, where it sharpens customer experiences with laser-focused recommendations. But here’s the catch: many businesses hit roadblocks when trying to bring this transformative technology into their workflows. Moving from promise to practice takes more than powerful algorithms. It takes a strategy that integrates AI into every part of an organization, backed by a collaborative culture and a solid tech infrastructure to handle the unique demands AI brings.

Natural Language Processing: A Giant Leap Forward

One of the most accessible advancements in AI is natural language processing (NLP). You no longer need a deep technical background to generate impactful results. Companies like OpenAI have unlocked the potential for anyone to leverage complex technology without getting bogged down in the intricacies of prompt engineering. By transforming simple requests into nuanced responses, NLP democratizes technology—empowering business users, entrepreneurs, and consumers alike to harness AI for content creation, strategic analysis, and decision-making.

Real-World Resilience: AI’s Practical Challenges

Despite its transformative promise, deploying AI in the real world is not yet a plug-and-play endeavor. Take autonomous trading systems as an example. While initially focused on optimizing trading strategies, it became clear that the real mission was building resilience against the unpredictable: power outages, unstable internet, server issues, and even geopolitical shifts that could halt operations in an instant. Making AI that doesn’t just perform but thrives in an unpredictable world calls for a fundamental shift in thinking—from optimizing a single outcome to building systems that can handle whatever comes their way.

At its core, AI transforms raw data into actionable insights. For companies, this translates into deeper customer insights, trend forecasting, and optimizing operations on a grand scale. But here’s the challenge: it’s not just about amassing data but about pulling the right insights while respecting user privacy and regulatory requirements.

Those companies that can weave AI seamlessly into their processes—and keep the trust of their users—will lead the charge in this data-driven revolution.

Conclusion: Moving from Exponential to Essential

As AI advances from a cutting-edge tool to an essential part of business strategy, success will hinge not on speed but on the quality of execution. It’s about embedding resilience, enhancing user experience, and remaining ethically grounded. Companies that bring a clear vision and long-term adaptability to AI adoption will find themselves ahead, not just capitalizing on its transformative potential but building a future where AI becomes a natural, reliable partner in progress.

 

At that point, ChatGPT said:

Let me know if you’d like any adjustments! This draft keeps the original article’s structure and depth while incorporating your reflective, future-oriented tone and approachable insights.

 

Breaking The Fourth Wall

Hopefully, it wasn’t too confusing to read the transcripts and the article. In this section, I’ll discuss the experience and what I want to improve.

Ultimately, even after asking ChatGPT to rewrite the article, it doesn’t feel exactly like something I wrote. Yes, it was objectively better - cleaner, more structured, more polished. Yet it wasn’t quite “me.”

Better isn’t always good enough.

But here’s the real insight: This “almost but not quite” result might be what we need in the age of AI-assisted content creation. Think of it as a high-quality first draft that gives you a massive head start. Instead of staring at a blank page, you’re starting with something substantial that just needs your unique touch.

To be fair, I could have easily gotten closer to the intended target with just a few more prompts.

In addition, I could easily train an AI in-depth on my voice and writing style. Frankly, I should do that.

In the old days, we relied on style guides. With today’s level of AI, you can create custom AI prompts to transform base content into audience-specific communications. This opens up an intriguing possibility for businesses. The implications for scaling high-quality, consistent content are significant.

Or, I could practice what I preach and use this as the base primer to write something better. This article demonstrates the power of that hybrid approach. Some parts detail the AI’s contribution, while others share strategic insights and personal perspectives. Together, they create something more valuable than humans or machines can produce alone.

If you genuinely enjoy writing, AI shouldn’t be your replacement - it should be your amplifier, enhancing and multiplying what makes your writing uniquely yours.

As much as that’s true, sometimes you just have to produce decent-quality output. This process certainly did that, and there are plenty of simple add-ons that can elevate the quality from merely acceptable to genuinely good.

Even though I didn’t want to use another tool (because of the premise of this article), I pasted the article into a tool called Type (which is similar to Lex). Both are AI document editors that speed up and simplify the writing process. Type gave me these options, each of which would have improved the article.

• Improve: Remove clichés, fix errors, and improve transitions.

• Fix Errors: Fix grammar and spelling errors.

• Shorten: Remove fluff and simplify lengthy phrases.

• Enhance Structure and Formatting: Make things easier to skim and read.

Additionally, Type has a cool feature that analyzes your document and suggests things to incorporate at specific points. It can generate sentences, lists, and paragraphs directly at your cursor as you write. It also can help you find the perfect idea with real-time suggestions. Type analyzes your writing to identify opportunities to expand or improve it. When you like a suggestion, Type’s writing AI can write it out and insert it into your document.

Here are some of the suggestions it had for the “Navigating the AI Revolution” article.

• Highlight successful case studies of companies that have effectively integrated AI.

• Include specific metrics and ROl examples from Al implementations.

• Outline the necessary steps for businesses to begin their Al transformation journey.

• Describe the role of human oversight and the balance between automation and human judgment.

• Explore the future implications of Al on workforce development and job markets.

• Discuss the importance of cross-functional teams in Al implementations.

• Address cybersecurity concerns and protective measures when deploying Al systems.

It’s like having a team of grammar, style, story, and industry-specific knowledge specialists. You can brainstorm and examine issues from multiple angles to incrementally improve your base product and transform it into something worth saving and sharing.

In conclusion, I spent more time crafting the intro and conclusion than writing the base article with ChatGPT’s Advanced Voice Mode.

When I first started playing with AI tools, I hoped they could improve my writing. Now, I realize they’re already so capable and powerful that they are changing how I write and even how I think about writing.

In business, I often say you don’t want to be the bottleneck or limit of how good things can be. With tools like these, that’s true with writing as well. The limits of your initial thinking or knowledge no longer constrain the upper limit of what you can produce.

For executives and teams looking to stay ahead, the question isn’t whether to use AI in content creation - it’s how to use it most effectively while maintaining your authentic voice. The leaders who crack this code first will have a significant competitive advantage.

I’d love to hear your thoughts on this article or how you are using AI.

Why I'm Still Excited About The Future of GPTs as a 20+ Year AI CEO

Last week, I explained how to create content by simply talking to your computer using ChatGPT's new voice interface. In that post, I multi-tasked in a whole new way by writing the article by merely talking with ChatGPT while walking around my neighborhood to get some fresh air and "exercise."

In that article, I shared my conversation along with the end result - a quick and dirty article about the applications of AI voice agents. I didn't edit the article the way I usually would, but that was intentional to demonstrate what it could create on its own. My evaluation was that it produced content that met the minimum standard and provided a great starting point for me to enhance.

Next week, I'll redo that process, emphasizing the prompts used to interact with the AI. I also used some additional prompts to refine the writing.

As I find new tools, prompts, and applications, I can't help but share them with the people around me. Technology has always excited me and given me energy.

Meanwhile, as I share these tools and prompts with my son, Zach, it's clear he's not as excited as I am about them. For context, Zach and I work on these articles together. So, when I find a new writing tool that I think will make our lives easier, I'm quick to share it.

This past week, I shared some prompts with him that I thought were profound (because they were simple – but produced useful productive output). Through simple prompts and appropriate context settings, we can now get ChatGPT (or other tools like Gemini, Claude, or Perplexity) to perform functions a small business may not have internally. For example, a company could use AI as a comptroller or product manager. It can also help create reports and summarize meetings better than my assistant or I would.

 

Zach acknowledged the utility of capabilities like these ... but described them as 'pedestrian.' He was unimpressed because, in his eyes, these were capabilities that were already possible early into the public release of ChatGPT.

He does appreciate more specific use cases for generative AI – but focuses more heavily on apps with a singular utility. For example, he likes a writing app called Lex, which works more like a standard Word Processor (but with several nicely done AI assists) ... or the Hemmingway Editor app, which helps make your writing concise and correct (by suggesting fixes for lengthy, complex sentences, and common errors).

Instead of focusing on the new generality & ubiquity - and automating tasks outside his wheelhouse - he gets excited about supplementing his ability or improving his efficiency.

His lack of excitement helped me understand more why I'm excited.

Since the '90s, I've been fascinated by AI. For much of that time, two types of people shared my excitement. The first was Hollywood executives, who created cliché dystopian depictions to perpetuate a false human vs AI dichotomy (think The Terminator, I, Robot, or 2001: A Space Odyssey). The other were other people like me. Entrepreneurs or academics looking to leverage exponential technologies.

The average person had very little practical exposure to AI outside of the hidden-in-plain-sight applications that were often glorified decision logic. Eventually, you got tools like Siri or Alexa that put it into everyone's home.

My son takes for granted that even when ChatGPT grew popular, using it well took expertise. You had to be clever, deliberate, and patient to get results that weren't verbose garbage.

AI is genuinely becoming not just available but accessible.

Three great examples are Letterly, Talktastic, and Rosebud Journal.

Letterly is an application that allows me to dictate whatever I'm thinking. It runs a process behind the scenes to organize and clean up disorganized text. Then it gives me dozens of rewrite options that allow me to choose the tone (Business, Casual, Friendly, Clear and Concise, etc.), the purpose (Email, Social Post, Journal Entry, etc.), and the type of output (Structured, 2X Shorter, Meeting Takeaways, Detailed Summary, Outline, etc.). It sounds much more complicated than it really is. The primary reason that I like it is that it's so simple that I take it for granted. 

Another tool like that is Talktastic. For short burst dictation, TalkTastic is better than speech recognition tools (like ChatGPT, OpenAI Whisper, Google Speech-to-Text, or Apple Dictation). It is a game changer because it interprets what you're saying based on what it sees on your computer screen, regardless of the app or website. That means when you trigger it to run, TalkTastic analyzes a snapshot of your chosen app and automatically understands your conversation's tone, style, and substance while accurately spelling people's names and easily confused words. So you can turn your rough ideas into thoughtful and articulate language everywhere. I use it dozens of times every day to create short messages, emails, and even some of the sentences in an article like this. Currently, Taltastic only works on macOS devices (and is totally free while in beta).

Rosebud is a journalling app reimagined to incorporate AI in many subtle and clever ways. I've been tempted to journal many times throughout my career, but always found reasons to abandon the practice. That's not true anymore. Rosebud's AI journal has fundamentally changed how I look at and use tools like this. Chatting with AI tools is one thing (I wrote about that in a post called Conversing With AI), but Rosebud is a level beyond even that. It has all the benefits of a traditional journal, but it adds intelligent responses, subtle prompts, and reminders to think about certain things. It's interactive and collaborative. It challenges you to re-examine certain beliefs, set goals, or measure success in different ways. Try it!

Each of these tools is a great example of something you quickly take for granted because it's easy to get used to nice things.

Expect a lot more things like that.

Isn't that exciting?