The Glass Dome Of AI Productivity

July 23, 2026

My dad taught me how to program. He taught me how to think about problem solving. One of his key lessons, still with me today after 20 years, was to teach oneself by reading out loud. A lesson, when read out loud, became much more understandable almost magically. This was partly because I read slower aloud and partly because by hearing, I am processing it again through the hearing pathways in my brain.

Reading my own code, just like reading a chapter, or this piece, makes the topic clearer in my head. I often used to review my own code on Github before giving it to another human. I’d find that I see improvements I just couldn’t in my own editor. This fundamental aspect of how I used to write code has now changed with AI.

Writing code by hand has the implicit upside of having spent time thinking about it. The classic book “Thinking Fast and Slow” talks about this: the cognitive process of complex thoughts is necessarily slow. That’s just how we are wired. Having to type the code, write the test, refactor the source, I implicitly spend more time thinking about the topic. With AI, the time I spend on any piece of code is shortened, if not entirely eliminated. It works for a while, for the repeating, mundane aspects of coding, but because our brain has to switch so quickly from one topic to the next, I just stop thinking at that speed. I can’t even read every line of generated code, let alone think about it.

That would have been fine. After all, I don’t read the final executable binary in machine code either. Except, there is one tiny caveat: AI is probabilistic. There is a false dichotomy here that we have come to accept - either AI is always right or it is sometimes right. If it’s the first, why bother about code at all? If it’s the second, we need to understand what AI writes, and that requires us, at the very least, to read the code.

AI’s probabilistic productivity can only be grounded by having a human in the loop, which would require making AI work more at the speed of human cognition, nullifying much of the productivity that AI was thought to have brought in the first place. If we want to really review AI-written code as we did with human-written code, the whole system would become slower and the selling points of AI generated code would be severely diminished. What I tend to do most often is trust (hope) that AI is right. I find myself using AI to summarize AI-generated code, just so I can keep up with it. The flaw in that way of working is dangerously obvious.

We are living under a glass dome of productivity. Because AI is right most of the time, we expect to rely on it all of the time. If we don’t understand how AI is changing in our systems, soon the system will become unrecognizable to us. That’s a cost I would not want to pay. The surface area of the average change is increasing faster than our human brains can keep up with. Eventually that cost will have to be paid or we would have to slow down. The sky is not the limit, the glass dome is. Thinking slow, these days, is already a lost art it seems.

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