LLMs reward expertise

Maybe LLMs don't usher in the end of software engineering but they definitely end the whole "made with love (and coffee) in X". Nobody cares if you put effort into something software related. "Does it work? Yes? Ok build the next thing." Its the same with the notion of "taste" (see "sometimes tasteless computer code" from the Goedecke article), your colleague who is also a SE might respect your choices as good taste. But it ends there. This was also the case pre-LLMs I would argue. What is worse now is that communicating any uncertainty in decisions related to implementation will result in an immediate "Have you asked Claude?".

What's this LLM's generated yapping?

Yes. This is called the Matthew Principle:

> For to every one who has will more be given, and he will have abundance; but from him who has not, even what he has will be taken away.

LLMs reward architecture knowledge of how to structure things and how to not just say "Claude, make me Microsoft Flight Simulator, make no mistakes".

Terminology is a crazy lever with AI

The fact that Claude knows I wrote the Virgil compiler makes it be on its best behavior when working on it. I force it to not write too much code, and to write more tests. I push back on slop and just adding another special case. It has a surprisingly deep understanding of floating point.

Not the best way to test this, but I am working on a blog post, where I'll implement a problem statement with the dumbest/cheapest AI model while someone non technical person will vibe code end to end and compare both of them.

I'm surprised nobody mentioned (including the author) the Gell-Mann Amnesia Effect [1]... Just substitute "LLM" for "journalist" and there you have it.

And to be honest, I have seen it, as I'm sure (almost) everyone has, who has demonstrated experience/expertise in their own fields, and correct the LLM's responses one time or another...

[1] https://en.wikipedia.org/wiki/Michael_Crichton#%22Gell-Mann_...

LLMs are like fire: great servant, terrible master

Same thing I personally am not a front end guy but I have dabbled with it in the past but I am writing a front end app and a chrome extension, but besides a few pages of code I have reviewed I really do not know what the fck is written (its for an MVP I am building) and I am feeling really conflicted as to what the fuck do I do. At work, the stuff I write has a decent mix of my code, AI code and a few things I do the old way of copying from stackoverflow and seeing what works/doesn't work.

The entire issue is that when you ask it to do something, you are leaving it to chance they may or may not do it properly, either on look/feel, performance, security, scalability etc. It compounds as you layer a new prompt output over that project.

For example, if you write iOS apps, you ask it to do some animations. It will do it for you, but you are at it's mercy of writing complete custom code or you can specify they use a certain apple supplied API for a native experience. It's one of thousand things that will get a vibe coder if they don't ask. Or you may get lucky and LLM chooses to use a native method.

LLMs are good on things I know little about, but fall short on things I'm good in.

The LLM industry is deliberately consuming human expertise on a grand scale, so that eventually knowledge work is delegated to any machine, yet I have to gain some sense of comfort knowing that for the present point in time it still rewards personal skill?

Regardless of whether you agree with the claim or not, it's definitely not the endgame.

What a nothing-burger. Garbage in garbage out. Hasn't everyone who worked with LLM's experienced this?

Now everyone who feels rewarded by LLMs will conclude that it demonstrates their expertise. ;)

Wow

Is someone keeping a list of the excuses and varying instructions on how to hold it right? It would be fascinating historic documentation

Yes. If you use the right technical terms together it’s lights up more specific feature spaces to your task.

Specificity matters to LLMs a lot.

You got to know how to use the model+harness+prompt to achieve the results you want, but honestly for many projects and questions all the models already pump out their same best version of an answer.

Sometimes it is really akin to a git clone, although it was a LLM request.

This rewarding expertise is somewhat wishful thinking.

At the end of a day, it feels and is more like gambling, even with the recommended expertise and a good approach, don't delude yourself you're simply pulling the lever too, as any novice.

Cows

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