Fifty pull requests per week requires more hours than exist. Ten minutes each—and that's generous, assuming no review, no debugging, no context-switching—yields over eight hours of uninterrupted production daily. The number doesn't stretch toward difficult. It breaks arithmetic entirely.
This is the first axiom: the target must be impossible under current assumptions. Not ambitious. Impossible. If you can imagine reaching it by working harder, it isn't impossible enough.
The second axiom follows from the first: impossible targets don't yield to effort. They yield to transformation. The developer who achieves fifty PRs weekly isn't a faster version of the developer who achieves five. They're a different kind of thing—an orchestrator running parallel agents, not a craftsperson at a single terminal.
What looks like productivity is actually ontology. The algebra that makes impossible numbers possible isn't about efficiency. It's about becoming.
I keep returning to something the philosopher James Carse wrote nearly forty years ago, and that Sangeet Paul Choudhary put more sharply in a recent post: the point of an infinite game is to keep playing.
This sounds like a platitude until you watch people forget it. You stay in the infinite game by winning finite games: the funding round, the product launch, the quarterly target, the acquisition. These finite games have clear winners and losers. They feel urgent. They come with metrics and deadlines and congratulations when you close them. But they are not the point. They are what you do to remain in the arena where the actual game unfolds.
The pathology (and it is a pathology, not a mistake) is when we optimize so hard for the next finite win that we sacrifice the capacity to keep winning. When we confuse the battle for the war. When every decision serves next quarter at the expense of next decade. I've watched this happen to people I respect, and I've caught myself doing it more than I'd like to admit.
What makes the AI platform market worth examining is that it has industrialized this confusion. Meta pays $2 billion for Manus in ten days. Cursor raises at $29 billion. The valuations make no sense as prices for things that exist; they make complete sense as prices for options on things that might. Everyone is playing finite games (the demo, the deal, the markup) and almost no one can tell whether these finite wins are building something durable or consuming the conditions for durability.
The fog prevents the knowing. What follows is an attempt to trace its contours.
By fog I mean something specific: a market condition where participants cannot evaluate their own productivity. Buyers cannot distinguish platforms that work from platforms that perform. Capital flows toward stories rather than outcomes; outcomes resist measurement. The fog isn't a temporary inconvenience that better tools will disperse. The fog is structural. It's produced by the same dynamics that produce the market itself.
This essay moves in concentric circles through that fog. It starts with the individual developer who feels productive while actually getting slower, a perception gap documented in studies that should have caused more alarm than they did. It moves outward to markets that cannot learn from their participants, capital structures that reward performance over verification, and political battles over who gets to define what "working" even means. At the center is a question I find genuinely unsettling: what kind of people do we become when we work in conditions of structural unknowability? What happens to judgment, to attention, to the capacity for honest self-assessment, when the tools we use are optimized to make us feel effective regardless of whether we are?
I don't have comfortable answers. But I've become convinced that the question (which game are you actually playing?) is the one that matters. The fog makes it difficult to answer, and that difficulty is itself the subject.