In 1977, Charles and Ray Eames released a short film called Powers of Ten. It begins with a couple at a picnic in a Chicago park. Every ten seconds, the camera pulls back by a factor of ten. The blanket becomes a field, the field becomes a city, the city becomes a continent, until Earth itself is just a speck. Then it reverses, diving inward, past skin, into cells, into molecules, into atoms, until everything dissolves into particles. The whole journey takes nine minutes. It quietly rewires how we see the world.
The Eames’ insight was deceptively simple. Our perspective depends entirely on where we stand. I think about this constantly, in board meetings, founder conversations, and decision-making. Zoom out a little, and we see a horizontal platform opportunity. Zoom out further, and we see a paradigm shift reshaping an entire industry. Zoom in, and we see the specific user, the specific pain point, the wedge that makes the whole thing actually work.
The problem looks completely different at every altitude, and so does the solution. Most strategic errors are not failures of intelligence or effort. They are failures of altitude. We solve the wrong problem brilliantly because we look at it from the wrong distance.
When facing a complex physics problem that seems unsolvable at the start, Richard Feynman would often retreat to a toy problem, a stripped-down version simple enough to solve by hand. The toy problem wasn’t the ultimate problem, but it contained the essential structure of the real problem, and by solving it first, Feynman could build intuition before scaling up to the full complexity. He wasn’t simplifying out of laziness. He was navigating to the right altitude.
Amazon didn’t start as the everything store. It started with books. Books were the toy problem for all e-commerce. They were uniform in shape, easy to ship, had a massive catalog that no physical store could match, and customers didn’t need to touch or try them before buying. Books let Bezos build the logistics, the interface, the customer trust, and the operational muscle that would eventually generalize to everything else. The toy version was the altitude from which the entire architecture became clear.
Apple understood this instinct as well. The iPod was the toy problem for a much larger ambition. At launch, it was just a music player, a category that already existed and that critics said Apple had no business entering. At the same time, the iPod wasn’t really about music. It was about building a pocket-sized computer with an iconic interface, a seamless content ecosystem, and a direct billing relationship with hundreds of millions of consumers. Music was the wedge. When the iPhone launched in 2007, Steve Ballmer laughed and said there was no chance it would gain significant market share. By any enterprise or telecom standard, the iPhone was a toy without a keyboard, Exchange support, or 3G speed. The App Store came a year later and turned the toy into an ecosystem that generated more economic activity than most countries. At Apple, each product was a toy problem for the next, and each altitude revealed the architecture of what came after.
This pattern is evident across many industries. The personal computer was a hobbyist’s toy that IBM and DEC ignored until it ate their business. The original Macintosh was mocked as underpowered and overpriced compared to the IBM PC. The early internet was a playground for academics. Just a few years ago, AI was solving toy problems such as playing chess, Go, or video games. Then reinforcement-learning techniques were applied to other tasks, such as search and summarization, leading to ChatGPT. Soon after, reinforcement learning was applied to coding, leading to Cursor, Codex, and Claude.
When something looks like a toy, most people see its limitations. Outlier founders see its structure and imagine what more we can build. They recognize that the toy version reveals the core mechanic, the atomic unit of value, stripped of all the complexity that will eventually get layered on top. These toys start out cheaper, simpler, and less capable. They serve customers that mainstream players are happy to ignore. Incumbents see them as toys, but if these LoFi toys somehow capture the imagination of outlier founders and customers despite their limited capabilities, we might be onto something that could change the world. This is why the instinct to dismiss something as a toy should be treated as a signal. If you find yourself saying “that’s just a toy,” pause, because as Chris Dixon wrote in 2010, the next big thing will start out looking like a toy.
Tony Xu believes that a strong strategy requires understanding the smallest operational details, as these realities inform high-level decisions. The best founders have an unusual ability to shift altitude fluidly. They can zoom in on a single user’s frustration and zoom out to a market measured in the hundreds of billions. They can work on the toy problem on Monday morning and articulate the generalized vision on Monday afternoon. The best founders hold both altitudes simultaneously without collapsing into either one. They don’t get lost in the details or lost in the abstraction. They navigate between them deliberately.
The next time you encounter a problem, zoom in and zoom out, and start by solving a toy problem. If history is any guide, the toys are where the future begins.
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