> Unsurprisingly, participants in the No AI group encountered more errors. These included errors in syntax and in Trio concepts, the latter of which mapped directly to topics tested on the evaluation

I'm wondering if we could have the best of IDE/Editor features like LSP and LLMs working together. With an LSP syntax errors are a solved problem, if the language is statically typed I often find myself just checking out type signatures of library methods, simpler to me than asking an LLM. But I would love to have LLMs fixing your syntax and with types available or not, giving suggestions on how to best use the libraries given current context.

Cursor tab does that to some extent but it's not fool proof and it still feels too "statistical".

I'd love to have something deeply integrated with LSPs and IDE features, for example VSCode alone has the ability of suggesting imports, Cursor tries to complete them statistically but it often suggest the wrong import path. I'd like to have the twos working together.

Another example is renaming identifiers with F2, it is reliable and predictable, can't say the same when asking an agent doing that. On the other hand if the pattern isn't predictable, e.g. a migration where a 1 to 1 rename isn't enough, but needs to find a pattern, LLMs are just great. So I'd love to have an F2 feature augmented with LLMs capabilities

An important aspect of this for professional programmers is that learning is not something that happens as a beginner, student or "junior" and then stops. The job is learning, and after 25 years of doing it I learn more per day than ever.

Go Anthropic for transparency and commitment to science.

Personally, I’ve never been learning software development concepts faster—but that’s because I’ve been offloading actual development to other people for years.

Another study from 2024 with similar findings: https://www.mdpi.com/2076-3417/14/10/4115 -- a bit more preliminary, but conducted with undergrad students still learning to program, so I expect the effect would be even more pronounced.

This similarly indicates that reliance on LLM correlates with degraded performance in critical problem-solving, coding and debugging skills. On the bright side, using LLMs as a supplementary learning aid (e.g. clarifying doubts) showed no negative impact on critical skills.

This is why I'm skeptical of people excited about "AI native" junior employees coming in and revamping the workplace. I haven't yet seen any evidence that AI can be effectively harnessed without some domain expertise, and I'm seeing mounting evidence that relying too much on it hinders building that expertise.

I think those who wish to become experts in a domain would willingly eschew using AI in their chosen discipline until they've "built the muscles."

It makes sense - juniors are coding faster but not understanding anything. Ironically it'll stop them getting more experienced despite feeling good. What I'm interested in is if the same applies for Senior+ developers. The soft signals are that people are feeling the atrophy but who knows...

Duplicate?

Submission about the arXiv pre-print: https://news.ycombinator.com/item?id=46821360