AI Is Turning Us All Into Cheetahs

AI is fast. I am fast. You are fast. We are all fast. But are we going somewhere?

The acceleration is real and extraordinary. What took teams weeks now takes hours. What took a designer days — comps, prototypes, iterations — now takes minutes. The tools are genuinely remarkable, and I use them every day. But speed, as a value, is incomplete. Speed only matters if you know where you’re going. And right now, much of the tech industry is running very fast without a shared destination.

The pattern I keep seeing: teams adopt AI tools, output increases dramatically, and then… nothing compounds. More gets shipped. More gets produced. But the product doesn’t get meaningfully better. The team doesn’t get meaningfully smarter. The organization doesn’t get meaningfully clearer about what it’s building or why.

This is because AI, in its current form, selects for a very specific cognitive style: fast, focused, output-driven, always in motion. It rewards the cheetah. And it’s quietly reshaping every team in its image.

Think about what gets celebrated in an AI-accelerated org. Who shipped the most. Who iterated fastest. Who adopted the new tool first. Who produced the most options, the most prototypes, the most pull requests. The metrics of speed have become the metrics of value. But speed is not the only kind of thinking that matters.

A jungle made only of cheetahs isn’t an ecosystem. It’s an arid monoculture.

In many teams, the cognitive ecosystem is flattening. The tortoise, the systems thinker, gets pressured to move faster. The otter, the designer, gets told to just ship something. The owl, the strategist, gets asked for quick takes instead of deep insight. The lion, the visionary, gets pulled into tool demos and prompt libraries. Everyone is expected to produce faster, iterate faster, decide faster, and ship faster. Different thinking styles are no longer assets; they’re friction. So the system quietly selects for one kind of behavior: the cheetah — fast, focused, efficient, always in motion. But a jungle made only of cheetahs isn’t an ecosystem. It’s an arid monoculture.

Much of the current AI conversation is about roles disappearing. That may happen. But there’s another, quieter risk. We may still have our jobs, but we’ll show up to them as thinner versions of ourselves: less reflective, less curious, less patient, less well-rounded. More reactive. More output-driven. More optimization-focused. Constantly in motion. Some will argue that AI gives us more time, but history suggests otherwise. Efficiency gains rarely turn into time on a beach. They usually turn into higher expectations, tighter cycles, and more output packed into the same space.

And to be clear, this isn’t a rejection of AI. Some people will read this as resistance, as someone clinging to the past or refusing to adopt the tools. That’s not the point. I use AI every day. I see its power. I understand why companies are racing to adopt it. But we also have to admit something uncomfortable: we’re moving incredibly fast without a shared understanding of where this is all supposed to land. No company, politician, or thought leader has clearly articulated the end state. What we mostly hear are numbers — thousands of layoffs attributed to AI, billions invested into AI infrastructure, trillion-dollar valuations built on future expectations. The story is always about the scale of the change, never the shape of the destination. We’re told to run faster, but rarely told where the finish line is.

So I keep coming back to a different set of questions. What am I missing while I’m running this fast? Where is this actually taking me? What is the final destination I’m trading for the slower, more diverse ways of thinking that used to surround me? If the entire jungle becomes a sprint, who actually wins? Right now, it often feels like the biggest winners are the companies building the AI infrastructure. The faster we run, the more we feed their systems. The more we optimize for their models, their workflows, and their platforms.

So what do we win? If I trade curiosity, patience, and cognitive diversity for speed, what is the actual prize at the end of the race? What am I becoming more of? And what parts of being human am I quietly giving up in exchange?

We’re not just automating tasks. We’re slowly standardizing the human behaviors around those tasks. And the more we all run at the same speed, in the same direction, with the same tools, the less diversity of thought remains.

The cheetah is a beautiful animal — elegant, powerful, perfectly designed for speed. But it only survives because the rest of the jungle exists. The tortoise stabilizes the ecosystem. The elephant carries its memory. The otter keeps it playful and alive. The owl sees what others miss. Even the overconfident lion keeps things moving when everyone else hesitates. Speed alone doesn’t sustain a system. Balance does. The jungle doesn’t survive because everything moves fast. It survives because, eventually, everything slows down at the watering holes. That’s where we recharge, where direction gets clarified, where instincts get challenged, where ideas get tested against reality. It’s where the system feeds itself.

AI is not going away, and speed is not the enemy. But speed without orientation is dangerous. The real question is no longer how fast can we go. It’s why are we going this fast, and where are we actually headed? That might mean protecting time for deep thinking, valuing slower and more deliberate voices on teams, designing workflows that include pause, not just output, and rewarding clarity, not just velocity.

AI can help us run faster. It might even show us where the water is. But it cannot tell us why the water matters. Only humans can do that. And if we’re not careful, we may sprint right past it.