The recurring dream of replacing developers

The problem is that a sufficient black box description of a system is way more elaborate then the white box description of the system or even a rigorous description of all acceptable white boxes (a proof). Unit tests contain enough information to distinguish an almost correct system from a more correct one, but there is way more information needed to even arrive at the almost correct system. Also even the knowledge which traits likely separate an almost correct one from the correct one likely requires a lot of white box knowledge.

Unit tests are the correct tool, because going from an almost correct one to a correct one is hard, because it implies the failure rate to be zero and the lower you go the harder it is to reduce the failure rate any further. But when your constraint is not infinitesimal small failure rate, but reaching expressiveness fast, then a naive implementation or a mathematical model are a much denser representation of the information, and thus easier to generate. In practical terms, it is much easier to encode the slightly incorrect preconception you have in your mind, then try to enumerate all the cases in which a statistically generated system might deviate from the preconception you already had in your head.

I am an AI hater (atleast in some of its current context precisely used for this) and you have worded some things I like to say in a manner I hadn't thought of and I agree with all you said and appreciate what you said man!

Now, I do agree with you and this is why I feel like AI can be good at just prototyping or for internal use cases, want to try out something no idea, sure use it or I have a website which sucks and I can quickly spin up an alternative for person use case, go for it, maybe even publish it to web with open source.

Take feedback from people if they give any and run with it. So in essense, prototyping's pretty cool.

But whenever I wish to monetize or the idea of monetize, I feel like we can take some design ideas or experimentation and then just write them ourselves. My ideology is simple in that I don't want to pay for some service which was written by AI slop, I mean at that point, just share us the prompt.

So at this point, just rewrite the code and actually learn what you are talking about (like I will give an example, I recently prototyped some simple firecracker ssh thing using gliderlabs/ssh golang package, I don't know how the AI code works, its just I built for my own use case, but If I wish to ever (someday) try to monetize it in any sense, rest assured I will try to learn how gliderlabs/ssh works to its core and build it all by my hands)

TLDR: AI's good for prototyping but then once you got the idea/more ideas on top of it, try to rewrite it in your understanding because as others have said the AI code you won't understand and you would spend 99% time on that 1% which AI can't but at that point, why not just rewrite?

Also if you rewrite, I feel like most people will be chill then buying even Anti AI people. Like sure, use AI for prototypes but give me code which I can verify and you wrote/ you understand to its core with 100% pinning of this fact.

If you are really into software projects for sustainability, you are gonna anger a crowd for no reason & have nothing beneficial come out of it.

So I think kind of everybody knows this but still AI gets to production because sustainability isn't the concern.

This is the cause. sustainability just straight up isn't the concern.

if you have VC's which want you to add 100's of features or want you to use AI or have AI integration or something (something I don't think every company should or their creators should be interested in unless necessary) and those VC's are in it only for 3-5 years who might want to dump you or enshitten you short term for their own gains. I can see why sustainability stops being a concern and we get to where we are.

Or another group of people most interested are the startup entrepreneur hustle culture people who have a VC like culture as well where sustainability just doesn't matter

I do hope that I am not blanket naming these groups because sure some might be exceptions but I am just sharing how the incentives aren't aligned and how they would likely end up using AI 90% slop and that's what we end up seeing in evidence for most companies.

I do feel like we need to boost more companies who are in it for the long run/sustainable practices & people/indie businesses who are in it because they are passionate about some project (usually that happens when they face the problem themselves or curiosity in many cases), because we as consumers have an incentive stick as well. Hope some movement can spawn up which can capture this nuance because i am not anti AI completely but not exactly pro either

I went back because of course I could've just pointed out one picture but still wanted to give the whole picture.

my conclusion is rather the fact that this is a very high stakes project (both emotionally and mentally and economically) and AI are still black boxes with chances of being much more error prone (atleast in this context) and chances of it missing something to cause the -75 million and deaths of many is more likely and also that in such a high stakes project, LLM's shouldn't be used and having more engineers in the team might be worth it.

> I doubt you have a clue regarding my suitability for any project, so I’ll ignore the passive l-aggressive ad hominem.

Aside from the snark presented at me. I agree. And this is why you don't see me in a project regarding such high stakes project and neither should you see an LLM at any costs in this context. These should be reserved to the caliber of people who have both experience in the industry and are made of flesh.

> You cannot escape the details. You must engage with them and solve them directly, meticulously. It's messy, it's extremely complicated and it's just plain hard.

Of course you can. The way the manager ignores the details when they ask the developer to do something, the same way they can when they ask the machine to do it.

> As engineers, scientists, researchers, etc our literal job is to break down problems into many smaller problems and then solve them one at a time.

Our literal job is also to look for and find patterns in these problems, so we can solve them as a more common problem, if possible, instead of solving them one at a time all the time.