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

  • The Dead Internet Theory Isn’t the Story. The Audience Is.

    The Dead Internet Theory has been floating around the internet for years. In its simplest form, it claims that much of the internet isn’t really “people” anymore — that bots generate the content, interact with it, and influence what the remaining humans eventually see. The theory often goes further, suggesting coordinated efforts by governments or corporations to manufacture online consensus and shape public opinion.

    Whether or not you buy the conspiracy is almost beside the point.

    Like many enduring conspiracy theories, it gained traction because it gave people language for something they were already feeling. Social media started feeling repetitive. Comment sections became oddly homogeneous. Search results filled with articles that all seemed to say the same thing using slightly different words. You couldn’t always explain why, but it often felt like there was less humanity on the internet than there used to be, and it was more than just echo chambers.

    Recently, that conversation took an interesting turn. Fortune reported on Cloudflare data suggesting that automated agents now account for a majority of web traffic, driven by AI crawlers, assistants, and autonomous software rather than traditional search engines or human visitors (growing nearly 8000%). The web is increasingly being read, indexed, summarized, and interpreted by machines—not just people.

    Who’s Your Audience?

    The original theory may have gotten the “why” wrong.

    But it may have noticed the “what” before the rest of us did.

    The more interesting question isn’t whether the internet is dead; it’s who we’re talking to now.

    For most of the web’s history, publishing meant writing for another person. You wanted someone to read your article, visit your website, buy your product, or share your idea.

    Today, one of your readers is almost certainly an AI.

    Maybe it’s an assistant summarizing your article for someone who never visits your website. Maybe it’s a research agent deciding whether your work is worth citing. Maybe it’s an AI crawler building tomorrow’s foundation model. Increasingly, your content’s first audience isn’t a person at all.

    Part of the reason we’re even writing this article is that we’ve started adapting our writing.

    We’ve started writing with AI in mind.

    Not because we’re trying to “game” AI, but because AI has become part of the communication process. We think about whether an AI can correctly summarize an article. Whether the structure makes our argument easier to retrieve. Whether the key ideas are stated clearly enough that an AI won’t miss the point when someone asks about them six months from now.

    Every major communication technology has quietly changed how people communicate:

    • The printing press rewarded writers who could organize ideas across pages rather than in speeches.
    • Radio rewarded people who sounded conversational.
    • Television rewarded visual storytelling.
    • The web rewarded prioritizing hyperlinks.
    • Search engines rewarded discoverability.
    • Social media rewarded engagement.
    • Now AI rewards comprehension.

    When we first started this blog, our focus was primarily on introducing ideas in broad strokes and prompting readers to make connections and ask themselves questions they might not have asked before. Today, there’s a bit more scaffolding and a clearer takeaway. On the one hand, it’s a departure; on the other … wouldn’t you argue it makes articles more helpful for the average reader as well?

    Inversely, does optimizing content for AI legibility risk creating a new, more sophisticated version of the very “slop” problem it critiques — content perfectly structured for machine comprehension but hollow for human readers?

    Twenty years ago, businesses learned to write for search engines.

    Ten years ago, they learned to write for social media.

    Today, we’re learning to write so machines can accurately understand what we’re trying to say.

    While it feels different, it’s not really.

    Once you start looking at it that way, a lot of other trends suddenly make more sense.

    Slop-py Writing

    The explosion of AI-generated “slop” isn’t primarily a technology problem.

    It’s an incentive problem.

    Whenever the cost of producing something approaches zero, we get more of it.

    We didn’t invent spam because e-mail existed. We invented spam because sending one million e-mails cost almost nothing. The same is true for clickbait on the internet.

    AI didn’t invent mediocre content. It simply made mediocre content incredibly cheap.

    Markets generally don’t optimize for quality.

    They optimize for incentives, and the incentives have changed.

    Recursive & Fractal

    There’s another thought that’s been bothering us.

    AI learns from the internet.

    People increasingly use AI to produce content for the internet.

    Future AI systems will almost certainly learn from some of that AI-assisted content.

    The system is becoming recursive.

    Financial markets have always worked this way. Prices influence behavior, which influences prices. Recommendations influence demand, which influences future recommendations.

    Information is beginning to work the same way.

    The internet is no longer just where humans exchange ideas.

    It’s becoming an ecosystem where humans teach machines, machines organize information for humans, and machines increasingly teach other machines.

    Ironically, as content becomes abundant, something else becomes scarce.

    We’re rapidly approaching a world where almost any article, image, video, or podcast can be generated on demand.

    The scarce resource is intentionality. Experience. Judgment. Credibility.

    Those things don’t scale particularly well.

    And that’s exactly why they’ll become more valuable.

    There’s Still A Pulse …

    Perhaps that’s the real lesson hiding underneath the Dead Internet Theory.

    The internet isn’t dying, but it is evolving.

    The audience, participants, and economics are changing.

    The internet is no longer a discrete and relatively small ecosystem of websites built by uber-nerds. It’s now an ever-expanding universe filled with everything you could imagine and more.

    Yes, more bots are trying to influence you, trying to game you, and creating a lot of noise. But they haven’t replaced the people who post quality content or build cool things.

    The challenge isn’t figuring out whether the internet is dead.

    It’s learning how to create and find signal in a world that’s becoming increasingly good at generating noise.

  • Danger: Deepfakes & Data Breaches … The Future of Fraud

    Fraud isn’t new. But it is evolving.

    In May, we talked about social engineering and how far it had come. That’s only the tip of the iceberg.

    Visual Capitalist put together a chart on the fraud trends businesses expect to shape the future of digital risk.

    You may think this isn’t important to you, but the costs of even one incident can be world-changing, especially to a small business.

    via Visual Capitalist

    Where The Risk Is Growing Fastest

    While many of these are associated with social engineering, it’s worth delving deeper into specific mechanisms and the risks they pose.

    • Biometric Fraud – The surveyed businesses anticipate the largest increase in biometric fraud, with 67% forecasting a rise. As organizations increasingly depend on facial recognition, voice authentication, and remote onboarding, bad actors are continuously discovering new methods to exploit these systems.
    • Synthetic Fraud – 56% of surveyed businesses expect a rise in this category. Synthetic identity fraud occurs when criminals combine real data, such as a stolen Social Security number, with fake details, such as a made-up name or address, to create a brand-new, non-existent persona. Fraudsters use this fake profile to open bank accounts, apply for credit cards, and build up a fake credit history before maxing out loans and disappearing.
    • AI-Driven Attacks and AI-Generated Fake Profiles – 33% of surveyed businesses expect a rise in AI-generated fake profiles, as fraudsters use generative tools to impersonate real users online. The mechanism: bad actors train AI on scraped photos, videos, and voice clips — pulled from social media, webinars, even a company’s own marketing content — to clone a real person’s face or voice convincingly enough to pass remote verification or authorize a transaction, or to fabricate an entirely synthetic persona from scratch.


    It’s no longer enough for most businesses to be reactive; real-time risk monitoring and active protection are necessary.

    From Reactive To Proactive

    Even as technology improves, the basics stay the same: data breaches and criminal networks are permanent fixtures of this ecosystem — they have to be accounted for, and they’ll keep posing major threats

    The first move isn’t a new tool — it’s an assumption change. Treat every biometric check, every new account, and every unsolicited video or voice call as unverified until proven otherwise. The businesses that build that assumption into their processes now will spend far less time (and money) cleaning up after the ones that don’t.

    Are you prepared? If not, what’s the first step you’ll take to safeguard your business and assets?

  • Make Something … Then Make It Real.

    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. Human and chimpanzee infants also 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. 

    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 (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 … once a name sticks, people stop questioning whether it’s still true or not.

    Hope that helps.

  • Where Are Millionaires Created?

    In 2025, nearly one million people became new millionaires, averaging over 2,680 daily. A closer look shows that the United States contributed nearly half of these new millionaires, with over 441,000, while the UK ranked second with just over 43,000.

    UBS’s Global Wealth Report via visualcapitalist

    I know many people are feeling stressed about the state of the world, the market, etc. However, this is another reminder that the U.S. is one of the strongest markets and an incredible place to do business.

    Wealth creation is continuing at pace despite the headline anxiety, which itself signals where capital is flowing …

    Onwards!

  • How To Compete Against the Tech Giants

    The last time I drove in New York City, the traffic was so bad that I complained, “I didn’t understand why people came here.” It reminded me of a Yogi Berra quote about a restaurant he used to work at: “Nobody goes there anymore, it’s too crowded.

    The same is true in business. Opportunity draws a crowd … but the best opportunities are often in areas of less competition.

    For entrepreneurs, oversaturation can turn products into commodities, reducing profit potential. Conversely, many shy away when a challenge seems insurmountable, creating unexpected opportunities for those willing to take the risk.

    While Artificial Intelligence is becoming commoditized, that doesn’t mean every application is.

    As an entrepreneur, I’m drawn to projects others might dismiss as science fiction. These are the challenges that often lead to the most groundbreaking and rewarding outcomes.

    As a practical matter, exponential technologies are changing the game in many ways. First, based on what they make possible. Second, by how fast that can happen now. And third, by making it necessary to make the invisible visible (what I mean by that is you must focus on thinking about things that were previously inconceivable to you), and that results in mining a bucket of opportunities that used to get no thought given to them.

    Moonshot Projects

    Moonshot projects offer a unique advantage. While they may seem daunting, their audacious nature often means less competition and greater potential for transformative impact and extraordinary profits.

    A moonshot project is a highly ambitious, transformative endeavor that seeks to solve a significant problem or create a revolutionary innovation. These projects are characterized by:

    • Audacious Goals: They aim for breakthroughs that seem nearly impossible.
    • Disruptive Impact: They strive to create solutions that are vastly superior to existing offerings, often by introducing entirely new paradigms.
    • High-Risk, High-Reward: These projects embrace the potential for failure in pursuit of groundbreaking results.
    • Long-Term Focus: They prioritize long-term impact over short-term gains.
    • Technological Advancements: They leverage cutting-edge or even nascent technologies.
    • Paradigm Shifts: They challenge conventional wisdom and industry norms.

    Moonshot projects are inherently challenging. They demand significant resources, interdisciplinary collaboration, and a willingness to venture into the unknown. This perceived difficulty often deters potential competitors, creating a unique opportunity for those willing to take the risk.

    When successful, they push the boundaries of what is possible and redefine the landscape of their respective fields.

    For us here, autonomous trading happens in live markets amid power failures, pandemics, wars, and the President’s ability to post whatever he wants on social media at any time. What started out as the quest for a better algorithm led to a real-time decision-making process that dynamically adapts to what happens, audits itself, and continually learns and evolves. Literally science fiction from 20 years ago.

    In part, that is why a 10X mindset is particularly well suited to Moonshot projects. By aiming for a tenfold improvement over existing solutions, you’re essentially operating in a space with little to no competition or opposition. This allows you to redefine the rules of the game and establish a sustainable competitive advantage.

    Playing a New Game

    Our strategy of moonshot thinking creates a unique, sustainable competitive advantage that aligns perfectly with the Moonshot approach. By choosing to play a different game (with an asymmetric edge), we’re not just competing; we’re fundamentally changing the playing field.

    I’m not interested in going head-to-head with tech giants on their turf. Instead, the goal is to carve out our own niche, focused on our unique abilities to push the boundaries that extend our edge.

    Quote from Howard Getson

    Being slightly ahead of the competition can be a powerful attractor. It often leads potential competitors to seek collaboration rather than confrontation. They might approach you with ideas, money, or opportunities, aspiring to share in your advanced position and capabilities. This dynamic can create unexpected partnerships and accelerate progress in ways that benefit everyone involved.

    When interviewing potential team members, I often share a crucial insight: if you’re seeking a job where you work 9-to-5 solving problems so you can go home feeling satisfied, this might not be the right fit.

    We tackle challenges of a different magnitude. Our projects rarely have quick solutions. Instead, we focus on making steady progress towards ambitious goals. Because of that, I sometimes joke that our motto should be: “We suck less.” Nevertheless, the underlying truth is more profound. It’s about understanding your ultimate objective and recognizing that each step that moves you in the right direction, no matter how small, is still progress.

    This approach aligns with our belief in playing a different game. We don’t just compete; we redefine the rules of engagement, creating our own metrics for success and pushing boundaries in ways that traditional thinking often overlooks. Kind of like this quote:

    I have not failed. I’ve just found 10,000 ways that won’t work.  – Thomas Edison

    Play to Win!

    Business does not happen in a vacuum. You have to be aware of the playing field, the players, and asymmetric advantages. In other words, don’t compete with giants at their own game.

    Choose to play a game you both want and expect to win.

    Playing a different game is a theme at Capitalogix. We believe that you control the game you’re playing, the rules, how you keep score, and even how you evaluate success. These things inform where to spend time, where to invest money, and even what you see as an opportunity. 

    Wouldn’t you rather compete in areas where you can create a unique, sustainable competitive advantage? Personally, I want to invest in the things that extend the edges that let us win.

    Why? Because the alternative — competing on someone else’s terms — is expensive in ways that don’t show up until it’s too late.

    Mediocrity Is Expensive!

    What you lack in size or computer power, you can make up for in creativity, agility, and innovation. 

    We built our edge in the investment industry through unique approaches to age-old problems, not raw computing power.

    We have an incredibly narrow and consistent focus. Within that area, we are willing to take on problems others avoid and pursue goals that others say are impossible. 

    Our niche limits risk and lets us fail faster … and learn faster. This allows us to take confident action while others are tentative. 

    Most big companies – and most of our competitors – are afraid to be wrong. They have to protect their infrastructure, cash cows, and short-term performance metrics. It makes sense (from their perspective) that playing it safe means they’re secure. – but that’s not how it works. 

    You can’t challenge the status quo when you are the status quo. 

    10X vs. 10%

    Pursuing moonshots (rather than incremental change) leads to a counterintuitive shift in belief … Improving something ten times is often easier than improving it ten percent. Astro Teller — who runs Alphabet’s moonshot factory, X — put it well in this TED talk:

    Astro Teller via TED

    In 1962 at Rice University, JFK told the country about a dream he had, a dream to put a person on the moon by the end of the decade.The eponymous moonshot. No one knew if it was possible to do, but he made sure a plan was put in place to do it if it was possible.That’s how great dreams are. Great dreams aren’t just visions, they’re visions coupled to strategies for making them real.” – Astro Teller

    Incremental change is hard – it’s finding new ways to do the same thing, and you often end up competing in very red oceans – saturated markets where you’re competing on price.

    Moonshots sound harder, but you create your own niche, and the constraints of a new idea force creativity and energy. If you’re going after a goal that no one has accomplished before, it’s impossible to be in a red ocean, and it’s easier to mobilize a team around something exciting and new than decreasing some arbitrary metric by 2%. 

    There are a couple of important lessons to keep in mind when pursuing the unknown. Usually I like to say that it’s better to have a map before you get lost in the woods, but in pursuing the unknown, you often don’t have a map. If that’s the case, the first thing I think of is to focus on process rather than outcomes. In the unknown, following a trusted framework is a good place to start. In addition, here are a few ideas to get you started.

    • Forget what you know – self-reported “experts” are limited by their worldview. If you’re trying to get a different result, you won’t do it by playing by the same rules your predecessors followed. Heuristics are great for making life easier – but they’re very limiting when trying to create something new. 
    • Attack the hardest problems first – your biggest problems are your biggest opportunities. If you don’t deal with the big problems now, you’ll never get around to them, and you’ll waste time and energy, only to realize you have to pivot much too late.  
    • Be comfortable being uncomfortable – most people find failure taboo and are deathly afraid of it. Tony Robbins talks about our tendency to avoid pain more actively than we pursue pleasure, and it’s true in business. But failure is a part of business. The people I consider most successful got there through incredible pain tolerance and increasingly intense problems that they continued to conquer. 
    • Have a short memory for pain – Focus on the gain, not the pain. People often focus on not having enough money, not enough time, or simply not having enough. That scarcity mindset is dangerous and can lead to getting lost in pain and fear. Acknowledging the pain/fear and moving forward from a place of abundance and opportunity helps create opportunities. 

    A clear identity is also important. You have to understand what you’re pursuing and how you want to attack the problem. At Capitalogix, we’ve gotten very in tune with our goals. 

    We invent techniques that identify and adapt to what happens. We apply the lessons learned from past experiences, data science breakthroughs, and hard work to eliminate the fear, greed, and discretionary mistakes that are the downfall of most decision-makers.

    Small businesses don’t have a monopoly on these mindsets and opportunities, but companies like Y CombinatorHeroX, or X (and no, I don’t mean the company formerly known as Twitter) are few and far between. Speaking of the other X, Elon Musk is famous for moonshots such as Tesla, SpaceX, Starlink, Neuralink, and XAI. Google and Microsoft pursue moonshots as well. 

    Good news … the future is big enough for them and you. 

    Choose something that lights you up and leverages what you already know and who you already are.

    If you’re the one writing checks instead of the one in the arena, the question isn’t whether a team has an edge today — it’s whether they’re building one nobody else wants to build.

    Sometimes the best opportunity is the one others don’t want to pursue, not because it’s crowded, but because it seems hard.

    Yogi Berra was joking about a restaurant. He wasn’t wrong about markets. The crowded road is the one everyone already found.

    So what’s your moonshot?

  • The Pace of Change: How Far Tech Has Come Since 1994

    When my youngest son was born in 1993, cassette tapes and the Sony Walkman were popular. I had a brick-sized phone hardwired into my car, and we had a Macintosh-II in the study. We take a lot of today’s technology for granted — it’s evolved so fast it’s hard to remember any of that wasn’t so long ago.

    Here is a throwback picture showcasing the cool tech we had back then. 

    Everything in that photo now exists in the cheapest of smartphones. And the features and functions available now far exceed my wildest expectations back then.

    For a blast from the past and a look back at what used to be top-of-the-line … here’s a video of people buying a computer in 1994. 

    via David Hoffman

    Video transfer and playback. 160-megabyte hard drive. 32 megahertz. All for the low price of $2,000. 

    I can remember back further than 1993, because I’m old enough that I didn’t have my first computer until after I graduated college. My first Macintosh had floppy disks measured in K, not megs or gigs. For context, my first job out of school was at a law firm where the only people who used computers were in the typing pool. And when I said I wanted a computer, the lawyers said “No!” because it would look bad.

    It’s pretty cool to see how far we’ve come! 

    This week’s other piece is a reflection on moonshots. Just as a reminder, even the things that seem like moonshots today will someday look “primitive” and “quaint”.

    Now, that’s cool! I can’t wait!!

  • The New AI Advantage: Context Reigns King

    For the past two years, “prompt engineering” has been treated as the defining AI skill. There were endless guides on magic phrases, secret prompt structures, and elaborate templates that promised dramatically better results.

    In the early days, they often made a meaningful difference. They were the differentiator. They’re still an important part of my framework around AI.

    But the landscape and the models have changed.

    Today’s frontier models are remarkably good at understanding intent. Give them a reasonable request, and they’ll often infer the structure, ask clarifying questions, or even build the framework themselves. A prompt that once required a page of careful instructions can now be written in a sentence or two with surprisingly similar results.

    Prompt engineering still matters. Good communication will always matter. But it’s no longer where the biggest advantage lies.

    The new advantage is context.

    From Better Prompts to Better Systems

    The organizations getting the most value from AI aren’t necessarily writing better prompts. They’re building better systems or ecosystems.

    They’ve documented their business. They’ve organized institutional knowledge. They’ve defined their voice, customers, products, and decision-making frameworks. They’ve connected their AI to the information that actually matters … and only what matters.

    In other words, they’ve spent months building an ecosystem instead of minutes writing a prompt.

    A company that’s actually done this has a living record of who owns which decision, a memory of why past calls were made and what happened afterward, and a standing way to tell its AI “here’s what’s changed since you last looked.”

    A Recipe For Slop

    The absence of that information and context is why so much AI-generated content still feels generic, and you see those artifacts of AI-construction.

    It’s not because the models aren’t capable. It’s because they’re operating without context — their defaults come from the sum of the internet’s knowledge, not your organization’s actual preferences.

    When an AI knows nothing about your company, your customers, your history, your goals, or your standards, it fills in the gaps with averages. It sounds like everyone else because, statistically speaking, everyone else is all it knows.

    That’s where the telltale AI signs come from: generic introductions, predictable transitions, vague conclusions, and writing that feels polished but somehow empty. The model isn’t being lazy. It’s doing exactly what it should with incomplete information.

    Think about hiring a new employee.

    You could hire the smartest person in the world. Still, if you sat them at a desk with no onboarding, no documentation, no understanding of your customers, no explanation of your culture, and no access to the institutional knowledge your team has built over the years, you wouldn’t expect exceptional work on day one. You’d expect educated guesses.

    AI is the same.

    A clever prompt might take five minutes to create.

    Someone else can copy it in five seconds.

    They can reverse engineer it, ask another AI to improve it, or find dozens of versions online. Prompts have become increasingly commoditized.

    Context isn’t.

    Context is months of documentation. It’s years of accumulated knowledge. It’s your operating procedures, meeting notes, customer conversations, product documentation, brand standards, strategy papers, and the thousands of small decisions that make your organization unique.

    No two companies will build exactly the same context.

    That’s why context has become a competitive moat.

    Perhaps the word “moat” overclaims slightly. A moat is static — dig it once, it defends forever. What the piece actually describes is closer to a flywheel that decays if you stop turning it. Institutional knowledge rots the same way any documentation rots if nobody keeps it current.

    Context has to be maintained, not just accumulated.

    The Next Competitive Divide

    The gap today isn’t simply between companies that use AI and those that don’t.

    It’s between organizations that have methodically onboarded AI into their businesses — creating systems where intelligent agents understand the company almost like a new employee—and organizations that are still opening a chatbot and typing random questions into a blank text box.

    Those companies are technically using the same technology.

    They’re just not getting the same results.

    Twenty years ago, the differentiator might have been whether your business had a website. Ten years ago, until recently, it was social media presence … then social authority and podcasts. Recently, it was whether you had AI at all. Increasingly, that won’t be enough. The companies that pull ahead will be the ones that invest in building an AI ecosystem: one where knowledge is captured, context is preserved, and intelligent agents are equipped with the same information your best employees rely on every day.

    The next phase of AI won’t be won by whoever writes the cleverest prompt. It will be won by whoever builds the best-informed systems.

    Start with the one thing your best person knows that’s never been written down.

    Onwards!