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Comment by dgellow | Hacker News Reader

I generally do have that mindset, but over the past 1y of Claude code I do notice that I’m clearly losing my understanding of the internals of projects. I do review LLM generated code, understand it, no problem reading/following through. But then someone asks me a question, and I’m like… wait, I actually don’t know. I remember the instructions I gave and reviewing the code but don’t actually have a fine-details model of the actual implementation crystallized in my mind, I need to check, was that thing implemented the way I thought it was or not? Wait, it’s actually wrong/not matching at all what I thought! It’s definitely becoming uncomfortable and makes me reconsider my use of Claude code pretty significantly

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> I’m like… wait, I actually don’t know.

reminds me of the experience of reading a math text without doing the exercises, thinking that you've understood the material, and then falling flat on your face when you attempt to apply your "understanding" to a novel problem. there's a significant difference between passively reading something and really putting active effort into it. only the latter leads to actual understanding ime

Same experience. I've been writing code for many decades, but that experience doesn't mean I can remember what I read when reviewing generated code. I write small, focused commits, but I have to take a day off each week to make changes by hand just to mentally keep up with my own codeset knowledge, and I still find structures that surprise me. It's not necessarily that the code quality is poor, but it's not like I (thought) I had designed it. It's lead to a weakening of my confidence when adding to or changing existing architecture.

I've had this issue too, and I feel it was an important lesson—kind of like the first time getting a hangover.

On the other hand, LLM-generated code comments better than I do, so given a long enough time horizon, it could be more understandable at a later time than code I've written myself (we've all had the experience of forgetting how things work).

It's not. Invariably, the code is locally fine and globally nonsense.

  > On the other hand, LLM-generated code comments better than I do, so given a long enough time horizon, it could be more understandable at a later time than code I've written myself (we've all had the experience of forgetting how things work).

Writing and rewriting piece of software performs what is called "spaced repetition" [1].

[1] https://en.wikipedia.org/wiki/Spaced_repetition

You ask questions about code when you implement something and if you cannot answer these questions, you go to code to find answers out and refresh your understanding of it.

For this to work you have to be interested in the understanding of the code and code should be created at the pace you can keep up.

Software engineers usually do create code economically because they need to remember and understand it. Vibe coders do not have this particular constraint, they just do not aim for most understandable code possible. Even if there are more comments in code.

I do think that this is natural. When you use LLM coding tools, you're becoming a lot more like an architect/staff/manager, rather than the direct coder. You're setting out the spec, coming up with the design, and coming up with the high level structure of the project.

However, this comes at the cost of losing track of the minute details of the implementation because you didn't write it yourself. I find it a bit analogous to code I've reviewed vs code I've written.

However, I've found using AI for code structure summary and questioning tends to be a good way to get around it. I might forget faster, but I also pick it up faster.

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