[ajjenkins]

AI can definitely produce a deletion. In fact, I commonly use AI to do this. Copy some code and prompt the AI to make the code simpler or more concise. The output will usually be fewer lines of code.

Unless you meant that AI won’t remove entire features from the code. But AI can do that too if you prompt it to. I think the bigger issue is that companies don’t put enough value on removing things and only focus on adding new features. That’s not a problem with AI though.

[Freedom2]

I'm no big fan of LLM generated code, but the fact that GP bluntly states "AI will never produce a deletion" despite this being categorically false makes it hard to take the rest of their spiel in good faith.

As a side note, I've had coworkers disappear for N days too and in that time the requirements changed (as is our business) and their lack of communication meant that their work was incompatible with the new requirements. So just because someone achieves a 10x speedup in a vacuum also isn't necessarily always a good thing.

[fifilura]

I'd also also be wary of the risk of being an architecture-astronaut.

A declarative framework for testing may make sense in some cases, but in many cases it will just be a complicated way of scripting something you use once or twice. And when you use it you need to call up the maintainer anyway when you get lost in the yaml.

Which of course feels good for the maintainer, to feel needed.

[ryandrake]

I messed around with Copilot for a while and this is one of the things that actually really impressed me. It was very good at taking a messy block of code, and simplifying it by removing unnecessary stuff, sometimes reducing it to a one line lambda. Very helpful!

[buggy6257]

> sometimes reducing it to a one line lambda.

Please don't do this :) Readable code is better than clever code!

[KurSix]

AI can refactor or trim code. But in practice, the way it's being used and measured in most orgs is all about speed and output

[Lutger]

So its rather that AI amplifies the already existing short-term incentives, increasing the harder to attribute and easier to ignore long-term costs.

The one actual major downside to AI is that PM and higher are now looking for problems to solve with it. I haven't really seen this before a lot with technology, except when cloud first became a thing and maybe sometimes with Microsoft products.

[specialist]

This is probably just me projecting...

u/justonceokay's wrote:

> The solution to bad code is more code.

This has always been true, in all domains.

Gen-AI's contribution is further automating the production of "slop". Bots arguing with other bots, perpetuating the vicious cycle of bullshit jobs (David Graeber) and enshitification (Cory Docotrow).

u/justonceokay's wrote:

> AI will never produce a deletion.

I acknowledge your example of tidying up some code. What Bill Joy may have characterized as "working in the small".

But what of novelty, craft, innovation? Can Gen-AI, moot the need for code? Like the oft-cited example of -2,000 LOC? https://www.folklore.org/Negative_2000_Lines_Of_Code.html

Can Gen-AI do the (traditional, pre 2000s) role of quality assurance? Identify unnecessary or unneeded work? Tie functionality back to requirements? Verify the goal has been satisfied?

Not yet, for sure. But I guess it's conceivable, provided sufficient training data. Is there sufficient training data?

You wrote:

> only focus on adding new features

Yup.

Further, somewhere in the transition from shipping CDs to publishing services, I went from developing products to just doing IT & data processing.

The code I write today (in anger) has a shorter shelf-life, creates much less value, is barely even worth the bother of creation much less validation.

Gen-AI can absolutely do all this @!#!$hit IT and data processing monkey motion.

[gopher_space]

> Can Gen-AI, moot the need for code?

During interviews one of my go-to examples of problem solving is a project I was able to kill during discovery, cancelling a client contract and sending everyone back to the drawing board.

Half of the people I've talked to do not understand why that might be a positive situation for everyone involved. I need to explain the benefit of having clients think you walk on water. They're still upset my example isn't heavy on any of the math they've memorized.

It feels like we're wondering how wise an AI can be in an era where wisdom and long-term thinking aren't really valued.

[bitwize]

> Can Gen-AI, moot the need for code?

No, because if you read your SICP you will come across the aphorism that "programs must be written for people to read, and only incidentally for machines to execute." Relatedly is an idea I often quote against "low/no code tooling" that by the time you have an idea of what you want done specific enough for a computer to execute it, whatever symbols you use to express that idea -- be it through text, diagrams, special notation, sounds, etc. -- will be isomorphic to constructs in some programming language. Relatedly, Gerald Sussman once wrote that he sought a language in which to discuss ideas with his friends, both human and electronic.

Code is a notation, like mathematical notation and musical notation. It stands outside prose because it expresses an idea for a procedure to be done by machine, specific enough to be unambiguously executable by said machine. No matter how hard you proompt, there's always going to be some vagueness and nuance in your English-language expression of the idea. To nail down the procedure unambiguously, you have to evaluate the idea in terms of code (or a sufficiently code-like notation as makes no difference). Even if you are working with a human-level (or greater) intelligence, it will be much easier for you and it to discuss some algorithm in terms of code than in an English-language description, at least if your mutual goal is a runnable version of the algorithm. Gen-AI will just make our electronic friends worthy of being called people; we will still need a programming language to adequately share our ideas with them.

[futuraperdita]

> But what of novelty, craft, innovation?

I would argue that a plurality, if not the majority, of business needs for software engineers do not need more than a single person with those skills. Better yet, there is already some executive that is extremely confident that they embody all three.