Cognitive Debt: When Velocity Exceeds Comprehension

The core of the article is “ AI-assisted development potentially short-circuits this replenishment mechanism. If new engineers can generate working modifications without developing deep comprehension, they never form the tacit knowledge that would traditionally accumulate. The organization loses knowledge not just through attrition but through insufficient formation.”

But is it possible this phenomenon is transient?

Isn’t part of the presumed value add of LLM coding agents in the meta-realm around coding; e.g. that well-structured human+LLM generated code (green field in particular) will be organized in such a way that the human will not have to develop deep comprehension until needed (e.g. for bug fix/optimization) and then only for a working set of the code, with the LLM bringing the person up to speed on the working set in question and also providing the architectural context to frame the working set properly?

* thinking about the big picture * knowing how you can verify that the code match the big picture.

In both case, somtimes you are happily surprised, sometimes you discover that the things you told 3 times the one writing code to do was still not done.

- legacy guys - super 10x guys who say no to u all the time - students - even more legacy - open source

I got to a point where I honestly care so little about all these guys' damn architectural decisions, which to me - a practitioner, scientist, researcher and academics teacher - made similarly very little sense.

Really, top coders, and veteran Java enterprise copy-pasters, I care so little about your damn code, it is very wrong most of times. I care very little about architectural decisions most of the opensource people took, as they very often come from weird backgrounds and these decisions do not match mine. Needless to say - they often know their architectural decisions are already wrong 10 years later (a great example is the QGIS crowd in this regard). I don't care about somebody's greatly designed ProC code. Neither do I care if Twitter was doing 1000 of API calls, which it seems to have been doing in reality, as even though I despise the Elon guy - well, his new X is arguably faster and more stable.

I don't care about how great your docker scales, if you need to scale to 1m VMs and back again, there is a fair chance you're Google, so I don't care about you either, as you are not the good guys anymore.

Likewise, I very much would bet 99% of visitors here don't really care what architectural decisions YC took when they decided to showcase Algolia's search. Very little interest in this.

The whole idea that there is a right way to do architecture or code is in total and direct contradiction with the history of computing, which has a good record of many successful projects not having great architecture (MySpace for example) and great projects that did not fly, even though they were top notch.

What I care is about is people and what people they are. Are they fakers? Are they smart? Are they in love with their code, or they simply see it as a tool. Are they smart enough to make a step back. Are they calm enough, are they inspiring. And of course - am I getting paid to do it.

So this massive outcry is super misplaced, and you know what - I don't care if you created your code with Claude or by threading it one char at a time, because eventually it's going to be me, with close to little knowledge, that will be forced to untangle this wonderful mess of yours.

And, no, you cannot teach people how to code. You can show them the way, and they learn their approach to it. Leave 5 people alone in 5 rooms, you'll get 5 architectures, perhaps all of them very solid.