The Orchestrator
vs. The Wheel Spinner

There's a famous Steve Jobs idea; he called computers a "bicycle for the mind." In an interview, he referenced a study about the efficiency of locomotion across different species: how much energy does it take for different animals to travel a given distance? The condor was at the very top of the list; it was insanely efficient. Humans were not great. But if you gave that human a bicycle, a completely man-made invention, suddenly we were ridiculously efficient. It wasn't even close. The machine, through our own ingenuity, amplified our effort.

"The machine, through our own ingenuity, amplified our effort."

For decades, that's what computers were. A mechanical advantage, better gears for your brain. You had spell check, copy-paste. If you were a programmer, you had an IDE. If you liked to text, you had autocomplete. But the physics still stayed linear.

Computers very quickly became integrated into society and the workforce as just another tool, this time for your brain. Just like how the drill or the automobile made screwing in a screw or transportation more efficient, computers made tasks like writing and math much, much easier. And though some jobs changed, productivity quickly increased. Accountants didn't go out of business because they no longer had to bookkeep by hand; quite the contrary, they used the same expertise they always had, and spreadsheets made them much more precise, much more efficient, and much quicker.

But the fact remained: even with the best word processor in the entire world, if you stopped typing, the essay didn't get written. Even with the best IDE in the entire world, if you stopped coding, your feature didn't ship. You had better gears, but you were still the force that pedaled to move the bicycle that was your mind.

AI changes the physics entirely. AI is the electric motor. You push a button, and the bike moves. Pedaling, the raw labor, has been decoupled from output itself and is now powered by LLMs rather than your brain. But all this power with no control creates the most common failure mode of 2026, and I call it "The Oscillation Trap."

Why does your brain start to treat AI like Google? Well, it comes down, as always, to UX. Here's the first problem: the initial interface we all learned to love for AI, the ChatGPT-style chat, looks so much like a Google search box. It's the direct path from AI to your brain as you first knew it. So 20 years of conditioning kicks in: Text box equals query equals answer. And that's why so many people never unlock AI beyond "search and summarize" or "generate me this."

Think back to 2004: Janet Jackson, the Super Bowl, the whole internet melting down. There were two kinds of searches. The noobs would type questions like a human into Google: "What happened at the Super Bowl with Janet Jackson and Justin Timberlake and why are people upset?" Accordingly, they got garbage results: random music forums, random noise, random 404s. The power users knew what to do. They typed in: "Janet Jackson Super Bowl video filetype:mpg," and they got exactly what they were looking for.

Back then, being smart meant learning how to speak "Keyword-ese" in order to talk to what was essentially a dumb machine. In 2026, we have the opposite problem. We're talking to a powerful machine like it's a dumb one. We'll ask for vague outputs like "research on X", "a plan to do Y", which you wouldn't dream of giving as complete instructions to your real human coworkers. You understand that they don't have access into the inner machinations of your mind, so you go into more detail. And somehow, for all the inappropriate anthropomorphization we apply onto AI, we still expect LLMs to figure out what we meant?

Here's the new split. If you want to use AI to get things done, you do not ask for nouns. You don't ask for "the answer", "the summary", "the best strategy", "the code". You're just the searcher. The Orchestrator asks for verbs and creates pipelines. Compare these three documents, extract contradictions, and format them as a table. Then draft a recommendation memo.

And here's the uncomfortable truth, I'm sorry to say: As much as it would be nice, AI does not replace your brain. It scales your brain. So if you don't know what "good" looks like, you're going to ask vague questions with vague expectations and get vague sludge in response. The model, if given the right input, can execute a process precisely and beautifully, at least by the end of 2025. But you still have to describe that process, often in excruciating detail. That is the 'work' that comes with being an Orchestrator.

To understand why this leverage of the bicycle looks so different now, you need the last three years in perspective.

Let's bring it back to the bicycle. The biggest misunderstanding of 2026 is confusing power with autonomy. The Wheel Spinners go hands-off and crash. Then they spend hours pushing the bike uphill manually. Manual labor is the penalty for not steering.

Orchestrators understand they need to steer. The motor does the pedaling, that's why you get paid. You get to relax a little bit because the heavy lifting is gone. But you stay engaged. You do micro-corrections, route planning, and break when it drifts. You structure the workflow so it can't fail silently. You always want observability.

Once you internalize all of that, you're going to stop Googling with AI and start building with it.