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> All of a sudden I have seen people do some really impressive stuff with DWARF files, eBPF, custom network drivers, custom crypto and really old computing hardware. Many of these things were previously off-limits for lots of developers. In some cases (eg: crypto) you were even pushed away because those things were intentionally gatekept by the people in the know.

Before at least some of us were forced to understand stuff, because without understanding it was not possible to do stuff that we really wanted to do, and some those got passionate and kept digging, and some of us even made even better stuff based on their experience.

Now no one needs to understand anything, and now we will never have better stuff.



> now we will never have better stuff.

I disagree. Some of us love tinkering and learning and experimenting. AI can help with that. People like us will always do it. Hobbyist will continue to innovate even if others don’t.


>I disagree. Some of us love tinkering and learning and experimenting.

Which means that instead of millions forced to learn and get good as part of their job, it would be a much smaller percentage of "hobbyists who love to tinker" doing it.

And even that tinkerer subset would be smaller than before in the future, since now many that would have turned into tinkerers would be tempted to just use AI, or never develop the taste and skills to be good tinkerers to begin with.

So what you wrote proves what the parent wrote, and is not an argument against it. You're basically saying "huge problem isn't a problem because there will always be some small number of people it won't affect".


> Which means that instead of millions forced to learn and get good as part of their job, it would be a much smaller percentage of "hobbyists who love to tinker" doing it.

Plus a growing number of completely new jobs dedicated to research and exploring new directions in software. Just think about another technology that was revolutionary when it appeared: automobiles. At first, you (or your driver) pretty much had to be a mechanic, a metalworker and a "tinkerer" to maintain the car; but the majority of people just need a car to take them from one place to another. But research and development of new automotive technologies didn't stop, on the contrary.


Or everyone will find AI development incredible boring over time because everything already exists and is easy to make and will turn to going deep into their own hobby because of it.

I don't think we really know the second and third order effects here.


> everyone will find AI development incredible boring over time

A lot of us already does. Some people feel that they enjoy it because they already enjoy creating via programming from past experience. But these people, while they get to create more, I think they actually enjoy doing it less. And overtime, they will actually do it less and less until there is no "Wow AI did it" factor wears off...

I think we know from how Internet changed things. Internet actually made it a lot easier to do stuff without actually understanding things. Even before Internet computer magazines contained code listings that you can type into the computer to "make" stuff. I never did that because I did not enjoy it because it took the joy out of figuring out it on your own. From this experience I know that just making it happen, is not the thing that gives the greater joy. And without that greater joy, without crossing that threshold, one is not going to keep coming back to it.

I know this with near certainty.


I hope you are right.


>Now no one needs to understand anything, and now we will never have better stuff.

Even worsr in that those starting out during this time, wouldn't even understand enough to guide and evaluate the AI output, or even even to know what to ask for.


I'm not saying you're entirely wrong, but LLMs can actually be a way to create even better things than those better things. I've seen it in action.


How do you judge "better" if you don't understand the LLM output?


By quantifying the result.


What are you talking about?


You want to solve a family of problems using some tool. You measure the relevant solutions performance metrics.

Now, you or someone else vibe-coded a new tool. You created new solutions and measure again.

You have just quantified the result of using the new tool.


How do you measure them if you don't understand what you're doing? A shitty benchmark or small test suite is not how solid software gets made.


You measure results, you benchmark what you care about. It works often enough to be useful


Good, you achieved a 10% speedup for a particular workload that some users said they care about. But how do you find out that was really the feature that should have been built next? How do you prevent adding badly factored code? How to make sure you don't pile on top of existing tech debt in the codebase, that you are solving the most fundamental issues first?


> some users said they care about

But how could they possibly know what they should care about if they don't understand the code?

> how do you find out that was really the feature that should have been built next?

Phew right they don't know. Only the devs understand what software should do.


I actually explained well enough why this requires to a large degree a competent developer to judge.


I think a sufficiently smart non-competent developer can still do this to great effect, but it definitely helps if someone is both a competent developer, smart, and a seasoned user of LLMs.


Just because AI is not yet a god that is better than all humans at creativity and product decisions and design does not mean it is not a huge accelerant right now.


Before: millions of web programmers and only an elite few that dug all the way down to metal

After: millions of vibe coders and only an elite few that dig all the way down to metal

I'm not sure the world will be all that different. The people who want to dig will still exist, they'll just be using excavators instead of shovels.

Source: https://x.com/mark_k/status/2090842540870074806


No one wants to dig for diggings sake. bad example.


This sounds like you don't like to dig for digging's sake and are projecting.


I disagree, some people lie in wait, hoping for a really good problem to tackle because they just want the excuse to dig.

Do you think Linus needs to write any code anymore? What kind of problems do you think a guy like Linus chooses to work on, the easy ones or the hard ones?

Tools change, people stay the same. Some people have never felt the rush of solving a really hard problem that no one else was able to solve. Such people can't understand that the fun is in the work not just the outcome. They can't understand that some people love to work. And for a person who loves to work, new tools are a joy.


>who loves to work, new tools are a joy

Not if the tool takes the joy out of work, and no one get a chance to learn that it is possible to have joy in the work...


we are on "hacker news"

in a long forgotten past, this used to be the crowd that digged.




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