I agree. Language models are good at codegen, in some sense they are just another codegen tool, except instead of transforming a structured language (like a config file or markdown) into code, they can convert natural language into code. Genuinely useful for the repetitive boilerplate grunt work. If that's all you do, then I can see fearing getting replaced. Thankfully by handling the drudgery, it frees us up to work on more complex and cutting edge work.

Like, it's not surprising that the developers who frequently talk about +90% of their work being delegated to LLMs are web developers. That is a field with very little innovative or complex code, it's mostly just grunt work translating knowledge of style rules and markup to code, or managing CRUD. I'm really thankful I can have a language model do that drudgery for me.

But compare that to eg. writing a multithreaded multiplayer networking service in Rust, they fall woefully short at generating code for me. They can be used in auxiliary aspects, like search or debugging, but the code it produces without substantial steering is not usable. It's often faster for me to write the code myself, because it's not a substantial amount of low impact code required, but a small amount of complex high impact code which needs to satisfy many invariants. This is fast to type, the majority of the work is elsewhere. At the end of the day, they work really well to replace typing the boilerplate, which is much appreciated.

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ngruhn 2 days ago | parent [-]

Try to get an animation just right without human guidance. It's difficult to give the agent feedback on its work. With browser MCP the agent can only make screenshots and see a single frame of the animation. Also agents are quite slow with browser handling. If the animation starts when a button is clicked, the animation is usually over before the agent has taken the screenshot.

All behavior of backend code can at least be described with automated tests.

	▲	slopinthebag 2 days ago \| parent [-]
		Yeah like I don't mean to demean front end work because there is a lot of stuff that isn't gruntwork or boilerplate, especially in the artistic fields or UI that is actually really complex. I actually made my initial career off of UI/UX. And a lot of the CRUD backend stuff really is literally just shuffling data in the most boring and replicated way as well. I guess my point is more that we have a lot of code being written that probably should have been automated already in some way, but it was simply more practical to just have people writing it. I dont see much harm in automating it with AI - the people doing the grunt work are largely capable of more, but at the end of the day someone has to dig the ditches. Now that we have a backhoe they can go do more interesting stuff. However when I see people who were largely writing meaningless boilerplate now claiming that software development is dead because they've become automated, I think it's important that people are being realistic about the different contexts in which AI is either useful or not. There is a wide range of experiences, some people believe AI is useful in completely automating their jobs and others feel it's mostly useless, and of course most people are in the middle somewhere. They're all correct, but the context is crucial. As far as I'm concerned it's just another tool in the toolbox.