Web/Tech

  • Making The Intangible … Tangible

    I remember getting excited when my son finally seemed smart enough that I believed he was more intelligent than our dog. For the record, it took longer than I thought it would.

    Likewise, human and chimpanzee infants start out remarkably similar in their early development. But here's where it gets interesting – their developmental paths take dramatically different turns once human babies begin acquiring language. This cognitive fork in the road fundamentally shapes their future capabilities.

    Language is a big domino. It allows "chunking" and makes learning new things more efficient, effective, and certain.

    Language is powerful in and of itself. Using language consciously is a multiplier.

    Today, I want to focus on one such use of language – the power of naming things. 

    The Power Of Naming Things

    “I read in a book once that a rose by any other name would smell as sweet, but I've never been able to believe it. I don't believe a rose WOULD be as nice if it was called a thistle or a skunk cabbage.” - L.M. Montgomery, Anne of Green Gables

    Before I go into detail, I shot a video on the subject, with a few examples from our business. 

    via Capitalogix's YouTube Channel

    Having a shared language allows you to communicate, coordinate, and collaborate more efficiently. But it's hard to have a shared language when you're discussing something intangible. 

    That's where naming comes in. When you name something, you make the "invisible" visible (for you, your team, and anyone else who might care). 

    I've often said the first step is to bring order to chaos. Then, wisdom comes from finer distinctions. Naming is a great way to create a natural taxonomy that helps people understand where they are – and where they are going.

    I like thinking of it in comparison to value ladders in marketing. 

    Value-ladder

    Each stage of the value ladder is meant to bring you to the next level. By the time someone gets to the top of the value ladder, they're your ideal customer. In other words, you create a natural pathway for a stranger (meaning someone who doesn't know you well) to follow, to gain value, trust, and momentum onwards … ultimately, ascending to become someone who believes in, and supports, what you offer and who you are. 

    Ultimately, successful collaboration relies on a common language. That is part of the reason naming is so important. The act of naming something makes it real, defines its boundaries and potentialities, and is often the first step toward understanding, adoption, and support. 

    Creating "Amplified Intelligence"

    There are always answers. We just have to be smart enough. - John Green

    Here is an example from our business. When we first started building trading systems, all we had was an idea. Then, we figured out an equation (and more of them). Next, we figured out some methods or techniques … which became recipes for success. As we progressed, we figured out a growing collection of useful and reliable ways to test, validate, automate, and execute the things we wanted to do (or to filter … or prevent the things we wanted to avoid or ignore).

    It probably seemed chaotic to someone who didn't understand the organizing principles. Fear, uncertainty, and doubt, which inhibit potential customers and stakeholders (such as a business's employees), compound the problem.

    Coming up with the right organizing principle (and name) makes it easier to understand, accept, and adopt. For example, many traders and trading firms want to amplify intelligence – meaning they want to make better decisions, take smarter actions, and ultimately perform better (which might mean making and keeping more money). To help firms amplify intelligence, we created the Capitalogix Insight Engine (which is a platform of equations, algorithms, methods, testing tools, automations, and execution capabilities). Within that platform, we have functional components (or modules) that focus on ideas like portfolio construction, sensible diversification, alpha generation, risk management, and allocation strategies. Some of those words may not mean much to you if you're not a trader, but if you are, it creates an order that makes sense and a path from the beginning to the end of the process.

    It makes sense. It explains where we are – while informing them about what might come later.

    The point is that naming things creates order, structure, and a contextual map of understanding.

    It is a compass heading used to navigate and guide in uncertain territory.

    On the other hand, beware of the consequences of becoming overly connected to labels. 

    Hope that helps.

  • The World Economy Going Into 2025 …

    Are you a glass half full or a glass half empty person? The recent economic news cycle has certainly been playing on people's fears.

    There is a lot of good news and reasons to be confident and excited about what's to come.

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

    Today, let's look at the $115 trillion global economy. For what it's worth, America is still the dominant force.

     

    20241228 World Economy in 2025 Infographic

    via VisualCapitalist

    America has topped the list for over 100 years and will comfortably continue that reign in 2025. China comes in second, and together, they account for approximately two-fifths of global GDP. That said, China is comparatively a newcomer to their spot – with about 15 years here. 

    While we top the list, the fastest-growing economies would go to countries like India, Australia, and Brazil – which are all expected to rise the ranks in the coming years. 

    The trend to watch here is what will happen in the Middle East, with Syria overthrowing their government and the Israel-Palestine conflict continuing and impacting the supply chain of surrounding countries as well. 

    It will also be interesting to see how Trump's re-election and the continuing Russia-Ukraine conflict affect global trends.

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

    The real story of 2025's global economy isn't just told with GDP rankings. While America and China dominate those numbers, traditional economic metrics are becoming less relevant in a world where regional conflicts, supply chain dynamics, and technological innovation can reshape global power dynamics overnight. In the longer term, birth rates and the growth of middle-class infrastructure are strong predictors of what lies ahead. GDP alone doesn't measure what truly matters in the modern global economy.

    What indicators are you watching?

  • 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.

     

    A dumbbell chart showing that online shopping as a percentage of total retail sales had climbed over time and spike in Q4 every year.

    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. 

    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?

  • Ready Fire Aim!

    Michael Masterson wrote a book called Ready Fire Aim: Zero to $100 Million In No Time Flat. It is a practical guide for entrepreneurs and business leaders, focusing on the different stages of business growth and the key challenges and priorities at each stage.

    A core message of the book is to start taking action quickly (instead of getting bogged down in over-planning) and use rapid iteration and real-world feedback to refine strategies.

    1_6-1YwAUx1EakS4S7e-WfLw

    The concept is presented in the context of growing a business – yet the lessons apply broadly. 

    Swift action should be your focus … not over-planning or perfect timing.

    Too many companies get stuck in a cycle of brainstorming, getting internal feedback, making changes, and failing to release the product.

    Even for released products, too many fail because they took too long to launch or ignored market feedback. 

    Masterson stresses that the value of live performance is that it helps you course-correct. He also cautions that there is no such thing as perfect timing. The best timing is almost always ‘Now!’

    Now, let’s extrapolate. 

    Let’s say you’re pondering a tricky work problem. You know you need to figure it out before the end of the week … but your brain keeps going in circles. 

    You don’t believe you can take decisive action and course-correct because you feel you have to get it right. 

    So, what can you do? Write it out. Write out the potential paths, ramifications, and worst-case scenarios as holistically as possible. 

    You’ll find that simply by writing it out instead of just ‘thinking,’ you end up more creative with more insight. 

    Writing aids in organizing and clarifying your thoughts. 

    AI As Your ‘Action’ Partner 

    AI can make this process easier, faster, and more manageable. Tools like ChatGPT can help you explore complex topics, run scenarios for you, and provide external feedback. 

    It’s not the same as real-world feedback, but it can shorten the ‘Aim’ part of the process. 

    As you externalize your thoughts in writing them to whatever AI you choose, you also get the same benefit you did writing your thoughts out in our previous example. 

    The business environment is changing faster than ever. Technology is advancing faster, adoption is getting easier, and the average Joe is becoming bullish on AI. Because of that, Masterson’s book is even more relevant now than it was in 2007. Here are a few of the other key takeaways from Ready, Fire, Aim.

    • Adapt Your Role: As a company scales, leaders must shift from “doing” to guiding and from tactics to strategy.
    • Be Sales-Focused: Keep revenue generation as a core priority, especially in the early stages.
    • Build Scalable Systems: Invest in operations and leadership at the right time to support sustainable growth.
    • Innovate Continuously: Avoid complacency by fostering an organizational culture that balances efficiency with creativity.

    AI and exponential technologies are going to compress cycle types. What used to be long-term planning will just be planning. You have to act fast, not only to capitalize on these trends but also to avoid being wiped out by them. 

    Are you keeping up?

  • Finding The Path Of Least Resistance …

    There’s a concept in design and transportation called Desire Paths. 

    A Desire Path is the path users take instead of the path intended by the builder. 

    Here’s a great example. 

    6tj18p093vb81Reddit via itstartswithani

    If you are interested, there is an active online community forum that shares examples of Desire Paths. It may give you some ideas and knowing laughs.

    I am a creature of habit, and even though much of what I think, feel, or do seems to be happening based on real-time choices or decisions, much of that is just a well-worn rut of unconscious behavior.

    As a subtle reminder to my son, who just got married, expect many of your existing Desire Paths to change (even if you don’t want them to).

    The lesson … It’s often easier to account for or take advantage of human nature (or nature) than to fight against it. 

    Here is a short video on how this relates to your business and tech adoption. I call it Functional Mapping. Check it out. 

     

    The video provides additional depth and detail beyond what’s covered in this post. I encourage you to watch it for a more complete perspective.

    Understanding the natural path for both technology and people makes it easier to understand and anticipate the capabilities, constraints, and milestones that define your path forward.   That means you actually have to understand the different types of users and what they expect to do. Here’s a diagram that explains how we build AI-enabled applications.

    6a00e5502e47b28833026bded38d1b200c-600wi

    Each stage is really about the opportunity to scale desired capabilities and automation.

    It isn’t really about building the technology; instead, it is about supporting the desire.

    You don’t have to get it right. You just have to create momentum in the right direction.   Meaning … if you can anticipate what is coming, you don’t have to build it. Instead, you should figure out where you want to build or create something that will move things in the right direction to help make that happen or benefit from it when it happens.

    You’ve probably heard me talk about how Capabilities become Prototypes. Then, Prototypes become Products. And, ultimately, Products become Platforms.

    This model is fractal. That means it works on many levels of magnification or iteration.

    What first looks like a product is later seen as a prototype for something bigger.

    SpaceX’s goal to get to Mars feels like their North Star right now … but once it’s achieved, it becomes the foundation for new goals.

    This Framework helps you validate capabilities before sinking resources into them. 

    It helps you anticipate which potential outcomes you want to accelerate. Rather than simply figuring out the easiest next step … you have to figure out which path is the best next step to your desired outcome.

    The world is changing fast! Hope you’re riding the wave instead of getting caught in the riptide!

    Onwards.

  • How Hard Is It To Run A Business In America?

    Running a business is hard. Of course, most people know that – but now VisualCapitalist has put together a chart to help visualize that sentiment. 

     

    This chart tracks the survival rate of businesses founded in 2013, by industry.

    via visualcapitalist

    20% of companies tracked failed in the first year … and only one-third last a decade.

    The numbers are worse than that in tech, mining, and oil & gas. Interestingly, those industries receive some of the largest government subsidies. 

    But, if you are reading this, chances are that you are a survivor. So, take pride in knowing the odds you've overcome … and be thankful. 

    It is Thanksgiving this week.

    Onwards! 

  • 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. 

    Image_the-true-color-of-white-lies

    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.

    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.

    ImageThis 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.

    Image (2)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.

     

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    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?