People. Process. Product.

AI provenance is here. We’ve never had easier access to something that convincingly looks like information.

Ask the robot a question and it: searches, summarizes, synthesizes, and hands back an answer. The whole thing feels magical. So naturally, everyone is ingesting the obvious, grabbing the first plausible result, jamming it into the product. Problem solved!

But magic commoditizes quickly…

Soon, everyone will be able to produce a plausible answer. The important question moves upstream: Where did it come from?

How was the data collected? What kind of data is it? What was omitted? Can the source be checked? Can it be defended? Is the source trustworthy?

AI products don’t have satisfying answers yet. For the moment, they don’t need them. There is so much obvious information waiting to be ingested that access itself is valuable.

Eventually the obvious gets exhausted. The models converge. Everyone has the same magic trick. That’s when differentiation moves to the ingredients: proprietary research, trusted relationships, unusual archives, carefully maintained datasets, real expertise, and information gathered with permission and context.

Welcome to artisanal, free-range, organic data.

There’s an essay called “The Bitter Lesson.” The gist is that human cleverness loses to raw computation. Every time. So, let’s take compute seriously.

The person with the most compute wins. The company with the most compute wins. The government with the most compute wins…You’ve seen this movie…

We learned to turn rocks into gas, spin them through tens of thousands of centrifuges, refine them into spicy metal, bolt it to a missile, and bury it underground on 24/7 standby. Then we put the same bombs on planes that never land and submarines in every ocean.

If compute equals victory, everyone is already building an AI Manhattan Project. Look around — it’s already here. So everyone races to hoard compute, and everything orbiting that economy becomes irrationally(?) valuable.

The moment anyone can fake anything, nobody can believe anything. Do you believe what you read these days? The next five years are going to be turbulent, unfair, and loud. Oh wait... That’s now.

…Here is where the story turns…

When everything can be faked, you do what humans did before institutions: you ask someone you trust. Ryan Findley calls it “SSL for people”: chains of human beings who can vouch for one another. Not because a blue check or a giant platform says so, but because they share history. Repeated interaction. Reputation. Mutual risk. A relationship can be impersonated. But the history behind that relationship is much harder to fake (for now).

Fable is nothing short of sensational. On max mode, what it pulls off is genuinely wild. It's a direct replacement for developers. Not all — but many.

Yeah but… it’s not going to replace bad management.

We've poured billions into building AGI, and management loves it. Of course they do! Management has the dollars, and AI is the shiniest thing those dollars have ever bought. It makes everyone underneath them “faster”, “cheaper”, more “replaceable.”

What we have not done…not with billions, not with millions, not with one serious dollar…is try to fix bad management.

Sit with that asymmetry. We'll happily automate the engineer, the analyst, the writer, the support rep, and spend a small nation's GDP doing it. But the manager who can't run a meeting, can't make a call, can't tell you what good looks like?

It's funny. At the end of the day, bad management is still bad management. No model is coming to fix it, because no one has been paid.