Categories
AI Programming Software Work

The Scarcest Thing

Garry Tan woke up at 8 a.m. after sleeping at 4. Not because he had to. Because he wanted to see what his workers had done overnight.

The workers are AI agents. Ten of them, running in parallel across three projects. And something about that sentence โ€” wanted to see what theyโ€™d done โ€” keeps stopping me. Thatโ€™s not the language of someone using a tool. Thatโ€™s the language of someone managing a team.

Tan gave a name to the state this puts him in: โ€œcyber psychosis.โ€ He said it as a joke. But the joke has an insight in it. Heโ€™s not describing addiction to a productivity app. Heโ€™s describing a shift in what it means to do creative work โ€” the strange vertigo of becoming a director when youโ€™d always been a laborer.

Iโ€™m retired. I watch this from the outside now, which is its own kind of vantage point. For most of my career, the path from idea to working product ran through people โ€” through hiring and managing and the slow accretion of execution capacity. You had the vision or you didnโ€™t, but either way you needed the team. The idea and the means of making it real were, structurally, separate things. The gap between them was where companies lived.

What Tan is describing is that gap closing.

The thing he built โ€” gstack, his open-sourced Claude Code configuration โ€” got dismissed in some quarters as โ€œjust prompts.โ€ And it is just prompts, in the same way that a conductorโ€™s score is just notation. The abstraction is the invention. What he encoded is a model of how a startup team thinks: the CEO who interrogates the why before a line of code gets written, the engineer who builds, the paranoid staff reviewer who looks for what breaks. Each role blocks a different failure mode. Blurring them together produces, as his documentation puts it, โ€œa mediocre blend of all four.โ€

Thatโ€™s an organizational insight. It has nothing to do with code.

Tan described being a โ€œtime billionaireโ€ โ€” not because his biological clock had slowed, but because he can now purchase machine-consciousness-hours. The bottleneck of implementation, which has governed every creative project since the beginning of creative projects, is dissolving for those who know how to direct.

The scarcest thing is shifting. Itโ€™s no longer the hours of execution. Itโ€™s the clarity of intent โ€” knowing what you want to build and why the journey matters, before any of the workers start moving. Thatโ€™s harder than it sounds. For decades, most of us could muddle through in the making of it. The act of building taught you what you were building. Now the making is cheap, and that shortcut is gone.

For someone watching from retirement, thatโ€™s not a small thing to absorb. The model I internalized over a long career โ€” that ideas become real through sustained organizational effort, through teams and timelines and the grinding work of execution โ€” is being revised faster than I expected. Not invalidated. Revised. The judgment still matters. The taste still matters. The why matters more than ever.

Itโ€™s just that the how has found new hands. Many of them. More than any team I ever assembled, available the moment the intent is clear enough to direct them, gone when the work is done. The constraint was always the hands. It turns out it was always the knowing.

Categories
AI Business Work

The Curator of Intent

I have always found a certain comfort in the “clatter” of a digital workday. Itโ€™s that specific, rhythmic hum of a mind in motionโ€”the clicking of a mechanical keyboard, the invisible friction of parsing a difficult paragraph or balancing a complex budget. For years, weโ€™ve treated this white-collar grind as our intellectual sanctuary.

But Mustafa Suleyman, now steering Microsoft AI, recently laid out a timeline that suggests the sanctuary walls are evaporating.

From an article in the Financial Times:

โ€œWhite-collar work, where youโ€™re sitting down at a computer, either being a lawyer or an accountant or a project manager or a marketing person โ€” most of those tasks will be fully automated by an AI within the next 12 to 18 months,โ€ Suleyman said.

This isn’t just about efficiency; itโ€™s about a fundamental shift in the “professional grade.” We are entering the era of the autonomous agentโ€”AI that doesn’t just wait for a prompt but “coordinates within workflows,” learns from its environment, and acts. Just ask any programmer that you know how AI is impacted their daily grind.

If Suleyman is correct, the “knowledge worker” is about to undergo a forced evolution. When the “doing” is handled by an agent that can learn and improve over time, what remains for the human? Will the models actually be able to learn from each of us in a personalized way – like an intern learns from her mentor?

โ€œCreating a new model is going to be like creating a podcast or writing a blog,โ€ he said. โ€œIt is going to be possible to design an AI that suits your requirements for every institutional organisation and person on the planet.โ€

It seems like our primary job description shifts from “Expert,” but “Curator of Intent.” We aren’t the ones finding the answers anymore; we are just the ones responsible for asking the right questions.

The next 18 months won’t just be a test of our technology, but a test of our egos. We have to learn to find our value not in the work we produce, but in the vision we hold and the questions we ask. We are shedding the “task” to save the “craft.” I just hope we remember the difference.


As we move toward this curated future, Iโ€™m left with a few questions I canโ€™t quite shake. Iโ€™d love to hear your thoughts:

  1. The Wisdom Gap: Can you truly be a “Curator of Intent” without having ever been a “Doer of Tasks”? If we skip the apprenticeship of the mundane, where does our intuition come from?
  2. The Metric of Value: If output becomes “free,” how should we measure a human’s value in a professional setting?
  3. The Line in the Sand: Is there a part of your workflow you would refuse to automate, even if an AI could do it better?