> It's not about the typing, it's about the understanding.

Well, it's both, for different people, seemingly :)

I also like the understanding and solving something difficult, that rewards a really strong part of my brain. But I don't always like to spend 5 hours in doing so, especially when I'm doing that because of some other problem I want to solve. Then I just want it solved ideally.

But then other days I engage in problems that are hard because they are hard, and because I want to spend 5 hours thinking about, designing the perfect solution for it and so on.

Different moments call for different methods, and particularly people seem to widely favor different methods too, which makes sense.

> LLM coding is like reading a math textbook without trying to solve any of the problems. You get an overview, you get a sense of what it's about and most importantly you get a false sense of understanding.

Can be, but… well, the analogy can go wrong both ways.

This is what Brilliant.org and Duolingo sell themselves on: solve problems to learn.

Before I moved to Berlin in 2018, I had turned the whole Duolingo German tree gold more than once, when I arrived I was essentially tourist-level.

Brilliant.org, I did as much as I could before the questions got too hard (latter half of group theory, relativity, vector calculus, that kind of thing); I've looked at it again since then, and get the impressions the new questions they added were the same kind of thing that ultimately turned me off Duolingo, easier questions that teach little, padding out a progressions system that can only be worked through fast enough to learn anything if you pay a lot.

Code… even before LLMs, I've seen and I've worked with confident people with a false sense of understanding about the code they wrote. (Unfortunately for me, one of my weaknesses is the politics of navigating such people).

Lately I've been writing DSLs with the help of these LLM assistants. It is definitely not vibe coding as I'm paying a lot of attention to the overall architecture. But most importantly my focus is on the expressiveness and usefulness of the DSLs themselves. I am indeed solving problems and I am very engaged but it is a very different focus. "How can the LSP help orient the developer?" "Do we want to encourage a functional-looking pipeline in this context"? "How should the step debugger operate under these conditions"? etc.

  GET /svg/weather
    |> jq: weatherData
    |> jq: `
      .hourly as $h |
      [$h.time, $h.temperature_2m] | transpose | map({time: .[0], temp: .[1]})
    `
    |> gg({ "type": "svg", "width": 800, "height": 400 }): `
      aes(x: time, y: temp) 
        | line() 
        | point()
    `

We've been hearing this a lot, but I don't really get it. A lot of code, most probably, isn't even close to being as challenging as a maths textbook.

It obviously depends a lot on what exactly you're building, but in many projects programming entails a lot of low intellectual effort, repetitive work.

It's the same things over and over with slight variations and little intellectual challenge once you've learnt the basic concepts.

Many projects do have a kernel of non-obvious innovation, some have a lot of it, and by all means, do think deeply about these parts. That's your job.

But if an LLM can do the clerical work for you? What's not to celebrate about that?

To make it concrete with an example: the other day I had Claude make a TUI for a data processing library I made. It's a bunch of rather tedious boilerplate.

I really have no intellectual interest in TUI coding and I would consider doing that myself a terrible use of my time considering all the other things I could be doing.

The alternative wasn't to have a much better TUI, but to not have any.

> LLM coding is like reading a math textbook without trying to solve any of the problems.

Most math textbooks provide the solutions too. So you could choose to just read those and move on and you’d have achieved much less. The same is true with coding. Just because LLMs are available doesn’t mean you have to use them for all coding, especially when the goal is to learn foundational knowledge. I still believe there’s a need for humans to learn much of the same foundational knowledge as before LLMs otherwise we’ll end up with a world of technology that is totally inscrutable. Those who choose to just vibe code everything will make themselves irrelevant quickly.