I’ve been talking to many of my peers about how it feels to be working in the AI Era. Everyone’s response is nearly identical:
“I’m working harder than ever, but I don’t feel like I’m getting ahead. My company is grinding us to the bone to avoid becoming an AI loser. I am exhausted.”
How can that be?
AI is supposed to make us more productive by automating all of the drudgery from our lives. We are supposed to feel like knowledge workers wearing an Iron Man suit. We were promised a more creative, dynamic future for the reasonable price of $20/mo.
Our companies are the self-proclaimed AI leaders. Our executives are on earnings calls proudly announcing an acceleration in AI revenue and increased employee productivity. They’re charging boldly ahead of the competition.
Yet we log into slack on Monday morning to brand-new OKRs concocted by these same executives, that read like they frantically asked Claude at 10 PM on Sunday night, “You are a consultant from McKinsey. Your goal is to create an executive-level AI transformation strategy. Build a robust year-long plan and generate aggressive yet attainable OKRs that I can assign to my team.”
Nobody is gaining an advantage despite running faster than ever.
There’s a scene in Alice in Wonderland that explains why everyone at your company is so exhausted:
‘Well, in our country,’ said Alice, ‘you’d generally get to somewhere else if you ran very fast for a long time, as we’ve been doing.’
‘A slow sort of country!’ said the Queen. ‘Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!’
Sounds familiar, doesn’t it? Like you might be running a Red Queen race inside a company that is also running a Red Queen race.
There’s a scientific theory for this phenomenon.
In 1973, evolutionary biologist Leigh Van Valen proposed a theory that he named after Alice’s Red Queen.
Van Valen’s insight was that species don’t just evolve in relation to their environment, they evolve against each other. Competitors and enemies aren’t static. They are evolving too, and the result is that everyone becomes fitter without gaining an advantage.
Your company isn’t the only business adopting AI. All of their peers and competitors are too. It feels like you are a gazelle who just found a hidden gear to escape the cheetah. But the cheetah has access to AI, too, and he was also up until 1:00 AM after putting the kids to bed.
That press release (written by AI, of course) that your business just published announcing their new AI agent? Your competitor will launch theirs next week. It will do the exact same things for your potential customers, cost the same amount, and be, more or less, completely indistinguishable.
Your boss sent you insane, AI-generated OKRs demanding a mid-quarter pivot because you are stuck in what I call the “Fractal of AI Panic.” There are three iterations in this fractal.
Individual: You are racing to become AI-pilled before your coworker turns you into a Claude skill. (No. Seriously. There is a viral Chinese GitHub repo you can use to map your coworker’s digital footprint to distill into a Claude skill.)
Company: Your company is fighting to become an AI winner, and to defend themselves against leaner, scrappier AI upstarts.
The Market: Public companies are seeing their stocks cut in half. Activist investors are pressuring your board and executives. Analysts are demanding answers.
The Fractal of AI Panic works like this.
The market (the environment) applies some force. An activist investor has built a 3% position and is pushing for change. They’ve contacted the board with a list of “suggestions” they would like to work on collaboratively. No public announcement yet. Or maybe ever, if they get their way.
Maybe your competitor just announced a new AI feature that’s getting a lot of buzz.
The CEO feels that pressure. Maybe the board starts leaning on her. Is she really the right person for the job?
The CEO cascades that pressure to their direct reports. And down it goes, in an increasingly urgent game of telephone, until it reaches…you.
You are the one who needs to drop everything to build or sell the feature that will save the business. You are the one who needs to transform your workflow to save your job. You are the one who needs to run twice as fast to stay in the same place.
In addition to that pressure you are feeling, AI actually made your average day harder, not easier.
AI made your day denser.
Before AI, your day involved much higher degree of mindless activity. Stuff like formatting, summarizing, entering and moving data, etc. This is the stuff you might throw on Spotify for and just zone out while you did the mechanical but necessary parts of your day. It was mental white space.
AI automated that white space away. And when it automated away this mechanical work, it replaced it with higher-stakes orchestration, strategic choices, and other activities with much higher cognitive requirements.
This increased cognitive density is not only tiring, it’s incredibly dangerous. It consumes all of your energy and attention beyond running the AI race.
The CEO has the same problem. So does the board.
Every level of the fractal is running so hard that nobody has the bandwidth to look up. You’re exhausted because your company is trying to win a competition it structurally cannot win, and by definition will never end. In fact, using all their resources on that competition is preventing them (and you) from running the race where they can actually emerge victorious.
The magnifying pressure of the AI Fractal of Panic forces everybody to sprint harder to adopt AI as quickly and thoroughly as possible. Tokenmaxxing is all the rage (maximizing AI usage). Meta even has a token consumption dashboard where people compete for the #1 spot.
Every iteration of the fractal is pushing so intensely they fail to see the historical pattern underneath that has played out in every technological revolution in history:
Every time a technological innovation commoditizes a major input, the winner was not the one who adopted the commodity the best or the fastest.
Instead, the winner realized that commoditization had changed the game on the field, and focused on building differentiated innovation further up or downstream.
In other words, the winners borrowed from another evolutionary theory: Niche construction.
Niche construction says that organisms don’t just adapt to their environment; they modify it, often in a way that changes the environment in their favor.
Consider these two historical examples where companies constructed environments that allowed them to escape the Red Queen dynamic:
Amazon and the Internet: As commerce moved online, everyone rushed to create the best web experience possible. They optimized their websites down to the pixel. Amazon took a different approach. They asked: What happens when digital distribution goes to zero?
Jeff Bezos wrote in the 2017 shareholder letter:
One thing I love about customers is that they are divinely discontent. Their expectations are never static – they go up. It may be because customers have such easy access to more information than ever before – in only a few seconds and with a couple taps on their phones, customers can read reviews, compare prices from multiple retailers, see whether something’s in stock, find out how fast it will ship or be available for pick-up, and more.
While everyone was focused on building a beautiful website and optimizing their Google ad spend, Amazon built the greatest flywheel in the history of retail (Amazon Prime) and poured billions of dollars into distribution infrastructure. They built warehouses, logistics networks, and doubled down on last mile delivery. While everyone was optimizing the digital world, Amazon was running a multi-decade race in the real, physical one. Even today, Amazon’s website would give your design team a heart attack. But they optimized for what was differentiated and scarce, constructed their own niche, and decades later everyone else (but Walmart) is sucking wind.
Automobiles and the Assembly Line: Before Ford took over, vehicles were essentially hand-built. Ford’s innovation was to standardize production into interchangeable parts. The Model T swept through America, and having a vehicle quickly became a commodity.
Alfred Sloan, CEO of General Motors, realized that running the current race against Ford was a losing battle. Instead, he asked: If everyone can own a car, then why not own a car that actually says something about you? Sloan created the laddered brands of Chevrolet, Pontiac, Oldsmobile, Buick, and finally, Cadillac. A car for every income level and aspiration. Then, on top of that, he added annual model changes and consumer financing - stacking innovations around the commodity to create identity, urgency, and improved access.
The final innovation in assembly-line manufacturing came from post-war Japan. With minimal capital and inventory, Toyota pioneered the Toyota Production System to eliminate every single form of waste from the manufacturing process. Scaled production had become a commodity, and that meant all the American car companies had become complacent in their production systems and quality control. Toyota capitalized on that complacency and became the biggest car company in the world.
In each instance (Ford, then GM, then Toyota), the winner recognized when a critical input had been commoditized and invested heavily in a differentiated, scarce variable. With each paradigm shift, the previous winner kept optimizing for the old input, not realizing the game had completely changed.
The Red Queen hypothesis explains the dynamic inside each regime. But new winners emerge between regimes, when a new technology commoditizes an existing input and a savvy competitor realizes a new business model is not only available, but superior.
Running a race in the exact area that is being commoditized is how you end up running twice as fast to achieve nothing. The winners innovate around the commodity input.
My honest advice to individuals? Conserve your energy. Now that you understand the dynamic, notice how cognitive density and the AI fractal of panic suck you of the attention required to find the right race to run.
The companies who are sprinting hardest on AI implementation and productization are optimizing for a world where intelligence is scarce. That world is going away. They are optimizing for fitness in a competition that is about to look very different.
What will humanity build in a world where intelligence is no longer the bottleneck? What is possible, and what becomes scarce, when intelligence is a commodity? That’s the race the winners are running right now.