Torvalds: "100% of Their Code Is Written by Compilers" Too. The Linux creator argued that AI-written code claims are misleading — and warned that a wave of low-quality, AI-generated bug reports is quietly burning out the maintainers who keep open source running.
I understand the spirit of what he means, but I still don’t know how an LLM can be used efficiently as a precise tool like this. If I can describe a problem narrowly enough to guide an LLM to give a useful output, I’ve already solved it myself and may as well just type it out.
Exactly same thinking. I can usually type it out faster than AI (when taking into account latency, context building, prompt writing, prompt fixing, AI hallucination review) if I know what exactly needs to be done.
When you’re out of your depth, it shines in providing beautifully confident and a botanical garden of a code piece that wil most likely be broken and break in new and exciting ways. Great for incompetent sycophantically-challenged managers that forgot how to code, or never actually had any experience.
Large-scale code transformations, taking into account the bigger picture of the repository are most likely hallucination free (not generative, just transformative, as per the actual LLM model) and a very exciting use-case.
Also it’s currently a very nice pragmatic tool for checking for any mistakes, because it can connect the larger context of the repository quickly to the diff. Terrible if done by a manager without understanding of copilot and workflow, but a great tool if done through claude and cli as a pre-commit step with just quick checklists. Makes plenty of mistakes, but allows to catch your own big mistakes nicely quickly.
I understand the spirit of what he means, but I still don’t know how an LLM can be used efficiently as a precise tool like this. If I can describe a problem narrowly enough to guide an LLM to give a useful output, I’ve already solved it myself and may as well just type it out.
Exactly same thinking. I can usually type it out faster than AI (when taking into account latency, context building, prompt writing, prompt fixing, AI hallucination review) if I know what exactly needs to be done.
When you’re out of your depth, it shines in providing beautifully confident and a botanical garden of a code piece that wil most likely be broken and break in new and exciting ways. Great for incompetent sycophantically-challenged managers that forgot how to code, or never actually had any experience.
Large-scale code transformations, taking into account the bigger picture of the repository are most likely hallucination free (not generative, just transformative, as per the actual LLM model) and a very exciting use-case.
Also it’s currently a very nice pragmatic tool for checking for any mistakes, because it can connect the larger context of the repository quickly to the diff. Terrible if done by a manager without understanding of copilot and workflow, but a great tool if done through claude and cli as a pre-commit step with just quick checklists. Makes plenty of mistakes, but allows to catch your own big mistakes nicely quickly.