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.

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.

Duplicate?

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

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."