by Dan Shipper in Chain of Thought Midjourney/Every illustration. I’m writing a book about the worldview I’ve developed by writing, coding, and living with AI. Last week I published the third piece from it, about how AI will impact business. Here’s the fourth, about how AI will impact creative work. It’s a synthesis of my previous writing on the topic, along with some updated thinking.—Dan Shipper Was this newsletter forwarded to you? Sign up to get it in your inbox. In 2023, I was at a low point in my journey with Every. I'd been running the business for several years but our growth was stagnant. My writing felt stagnant, and my co-founder had just left to run another company. I dreaded walking into a party because I knew I was going to be asked about what I do. And when I was asked about it, it would stick in my throat, like a first-time actor frozen backstage after hearing their cue. I needed to figure out what to do with myself—with my life, with my work, with my company. I'd always struggled with the tension between being an entrepreneur and being a writer. For the previous several years, I had leaned more towards the entrepreneur side of things. It felt more legible, lucrative, and prestigious. My last company had been a startup, too, so I was used to being able to walk into a room and talk about myself as a founder. I realized that if I was really honest with myself, I actually wanted to be a writer. But I also wanted to have a great business—or maybe a few great businesses. And the two seemed mutually exclusive. I had no examples to turn to. Most of Silicon Valley lore says that a CEO doesn’t have time for personal writing or any other form of creative work. My own experience confirmed as much. Being a CEO was both time-consuming and emotionally taxing. It wasn’t conducive to the space required to be really creative. This was in the very early days of ChatGPT, when the model was still GPT-3. Hoping to resolve my existential dilemma, I decided to ask for a list of writers who also had great businesses—in other words, a list of people to look up to. It immediately spat out a few great answers. One was Sam Harris, a writer, philosopher, and neuroscientist who has published many books, has a really popular podcast, and also has an extremely popular meditation app called Waking Up. I'd known about Harris for a long time, but I'd never really connected the dots—that he'd built the kind of career and business that I aspired to. Another example that came up was Bill Simmons, the famous sportswriter and podcaster who started Grantland and later founded The Ringer, which he sold to Spotify for around $200 million. Again, I'd heard of Bill Simmons, but I'd never thought about him in this way. ChatGPT came back with a bunch of other names: Ezra Klein, and Nate Silver, and John Green. All writers who I knew about and loved, but who, suddenly, I was seeing in a different light. In the Google era, I would only have been able to Google for “writers who are also great business people” and hope that someone else had thought to create an article or blog post naming those people. In my case, no one had really done that. My path in life was not yet well-defined. How technology reshapes creative work Most discussions about how AI will affect creative work revolve around fears that it might completely replace it. We imagine a doomsday world where AI agents autonomously creating tasty slop push real artists to the side. I don't think that's going to happen. But AI will change art, creativity, and creative work. Technology doesn't tend to eliminate artists or art forms, but it does tend to change art forms and the skills required to be an artist. TV, radio, and the Internet didn't eliminate books. But it did turn books from a mass medium, the primary way in which educated people learned about the world, to something more niche and aspirational. The same thing happened with musicals. Once the dominant form of popular entertainment in America, musicals still exist, and the aspirational nature of being on Broadway is still a part of popular consciousness. But musicals are more expensive, more special, compared to, say, TikTok videos where young people sing and dance for the camera. Concerns around AI and art largely boil down to the fear that AI can reproduce exactly any work that an artist does. Taking any paragraph of text from a writer, an AI could probably write that. It’s the same thing with a given painting or film clip. But if you look closely, this is the same old rationalist concern. It identifies art and its value as just the text on the page or the pixels in the image—completely divorced from context and history. But as we've seen in science and business, context is king. The context within which an AI-generated work is created is necessarily different from that of a human creative, and while in certain circumstances those works will be interchangeable, in many other ones they never will be. Moreover, I think that AI will be a boon to creativity and creative work for those who embrace it. Most groundbreaking art is taboo at first. And the cultural taboo around using AI for art signals that it is fertile ground for the brave creatives who embrace it to produce novel works. Let's talk about what that looks like. Become a paid subscriber to Every to unlock this piece and learn about: Why everyone needs to learn manager skills (even if you're not managing people) How pattern collecting becomes your creative superpower Six ways to use AI as a creative tool Upgrade to paid Click here to read the full post Want the full text of all articles in RSS? Become a subscriber, or learn more.

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by Dan Shipper in Chain of Thought Midjourney/Every illustration. I’m writing a book about the worldview I’ve developed by writing, coding, and living with AI. Last week I published the second piece from it, about how AI will impact science. Here’s the third, about how AI will impact business.—Dan Shipper Was this newsletter forwarded to you? Sign up to get it in your inbox. As a young entrepreneur, I once thought of myself as an information processing machine. I got interested in mental models like Clay Christensen’s disruption theory and Ray Dalio's Principles. I took copious notes and spent countless hours organizing them; I felt tremendous pressure to memorize these “rules” so that I could apply them in my business life. But in doing all this intellectual work, I had a nagging feeling: How would I remember to apply them in the situation that demanded it? I also saw entrepreneurs around me trying to apply similar rules, with mixed success. It sounds like a bad joke: A Wharton student goes to their first class on negotiation and learns about anchoring, then walks into their next negotiation proposing a price that's 10 times too high because they think it'll properly anchor the potential customer when instead it just pisses them off. We’re not the only entrepreneurs and capitalists who envy science and rationality and try to apply it to business. In the late 1700s, Adam Smith, explicitly inspired by Isaac Newton, attempted to discover universal laws of economics—and popularized the idea of the market’s invisible hand. In the early 20th century, Frederick W. Taylor attempted to optimize businesses scientifically, proposing that workers should be studied like machines, with every motion analyzed and improved for maximum efficiency. In the 1970s, Michael Porter’s “Five Forces” framework tried to explain business success as a factor of elementary forces like the bargaining power of suppliers and the threat of new entrants. Christensen’s disruption theory attempted to explain how startups unseat incumbents; his jobs-to-be-done framework is something like an atomic theory for appealing startup opportunities. Eric Reis’s The Lean Startup framed startups as laboratories and entrepreneurs as scientists testing product hypotheses. We’ve even come to simple, “universal” definitions for the goal of business—maximizing shareholder value—and the fundamental value of businesses: their expected future cash flows. Why has this way of looking at business been so appealing? First, it is undeniably helpful. Rigorous analytical thinking, reduction, and abstraction are critical to new products and technologies, and to the coordination of people and matter required to operate any kind of business—especially large ones. Second, the total elimination of uncertainty is, for some, the holy grail of business. Guaranteed return, no risk—that would be a great business indeed. An infinite money machine, where all you have to do is pull the lever. If that’s what you’re looking for—elimination of uncertainty—it is appealing to look for some form of authority to tell you what to do. Science and logic carry the most authority in the modern world. And just like nobody ever got fired for buying IBM, nobody ever got fired for being too scientific, rigorous, and analytical in their thinking. But as much as reduction and rigorous thinking can be helpful—or even critical—in business, our attempts to turn it into a science like physics are mostly window-dressing, just like our attempts with social sciences in academia. Many paths to the same result, the same paths to different results Complex systems like neural networks or human psychology exhibit what’s called equifinality—where many paths can lead to the same result—and multifinality—where the same path can lead to very different results. This applies to business as well. Take Christensen’s theory of disruption. It mapped quite well to disk drives and steel mills in the late 1980s and early 1990s, where established companies focused on high-end customers while new entrants captured the low end before moving upmarket. However, this pattern doesn't always hold true. Apple's iPhone, for instance, entered at the high end of the market and maintained that position. Netflix started by competing directly with Blockbuster's core business. Disruption theory is useful, but it's less a universal law like gravity and more of a helpful heuristic. Conversely, copying successful strategies often fails. When JC Penney hired Apple's retail chief Ron Johnson, they attempted to replicate Apple's retail strategy—but the same approach that worked brilliantly for Apple led to disaster for JC Penney. Business principles are usually anecdotes presented as axioms. Anecdotes—stories—are incredibly valuable. But they get misused when they are assumed to be general laws. In business, what’s most important is to be able to see the landscape clearly for yourself. It’s helpful to know theory and to know history—to take bits and pieces of what has worked for others and apply them to your situation—but usually the best businesses are hard to explain in terms of the past, just like paradigm-shifting scientific ideas are hard to explain in terms of previous theories. Why is this? For one, controlled experiments are close to impossible in business. Sure, you can A/B test a headline or a product’s price, but what you choose to test is significantly more important than which test wins. You and I can both use the same A/B testing tool as Mr. Beast to find which YouTube thumbnails will perform better, but Mr. Beast’s will win because he knows the frame or context for a good experiment far better than we do—and what a good frame is must always be partially inexplicit and subject to change. Beyond that, you can't A/B test major strategic decisions. You can't simultaneously run a company with two different CEOs or expand into two different markets with the exact same resources. The complexity of business environments, with countless variables from market conditions to employee dynamics, makes true scientific experimentation impractical. As a result, cause and effect are very difficult to establish. For another, business systems exhibit what chaos theorists call “sensitive dependence on initial conditions”—the famous butterfly effect. A small difference in timing, a slight variation in market conditions, or a minor change in team dynamics can completely alter the trajectory of a business decision. These changes can be so small as to be imperceptible; what appears to be the same situation can evolve, over time, into an entirely different outcome. This points to an even deeper challenge with business laws and principles: They only hold under certain conditions, but those conditions can never be fully specified in advance. Not only does disruption theory not work in the case of the iPhone, but we can't create an exhaustive list of when it will or won't work. New factors and forces constantly emerge that can invalidate previously reliable principles. Sometimes these are dramatic—like how a global pandemic suddenly made remote-first companies viable in ways that defied conventional wisdom about organizational culture. But often the changes are more subtle: gradual shifts in consumer behavior, technological capabilities, or competitive dynamics that accumulate until, seemingly overnight, old rules no longer apply. Even more challenging is that the conditions that make a principle work or fail aren't just about external factors but complex interactions between multiple variables. Netflix succeeded by directly competing with Blockbuster because of the specific combination of its team's capabilities, Blockbuster's weaknesses, shifting consumer preferences, and the evolution of broadband infrastructure. Change any one of those variables slightly, and Netflix might not be the dominant streaming platform it is today. This is why business principles are simultaneously useful and dangerous. They help us make sense of patterns we observe, but the moment we treat them as universal laws, we become blind to what makes them work or fail in any given situation. The key is not to abandon principles entirely, but to hold them loosely—always ready to notice anomalies that signal the game has changed. Perhaps most challenging of all is the inherent subjectivity in business. Entrepreneurs are encouraged to think objectively about which problems to solve, to do customer research like scientists. But customers rarely tell you directly what to build. Figuring out what people want—really want—calls for grasping two principles from our new worldview: context as priceless and knowledge as participatory. The context of a customer's response is shaped powerfully by what you put in front of them. What you put in front of them is a creative act. And the participatory, creative nature of this process is as essential in business as it is in science, as it is in other areas of life. This difficulty in creating controlled experiments, sensitivity to initial conditions, vulnerability to hidden exceptions, and the essentially creative nature of new product innovation means that when we call something a “law” of business or a “force,” we’re talking about something inherently different than what we mean when we talk about laws in physics or chemistry. Business "laws" are more like patterns or tendencies that we observe, but they don't have the same predictive power or universal applicability. So how do we deal with this? Become a paid subscriber to Every to unlock this piece and learn about how business intuition develops like language models—through repeated exposure to context—and the eight paradigm shifts in the new worldview of business. Upgrade to paid Click here to read the full post Want the full text of all articles in RSS? Become a subscriber, or learn more.

Every new space mission runs into the same wall: physics and fragility. Physics, because the speed of light and contested spectrum make real-time decision-making from the ground impossible when you […] The post Beyond the downlink: Why Earth-independent AI is the next moat in space operations appeared first on SpaceNews.

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