It’s fine to use LLMs to answer questions, analyze, distill, refine, check, suggest, review. But not to create.
Using LLMs for assistance is fine, but any non-trivial contributions (code, comments, documentation, review etc.) are expected to originate from a human.
I really like this approach. It enables the use of LLMs but protects everyone else (especially reviewers) from the burdens associated with that (such as having to parse excessive LLM-written text).
When I contribute to the Crystal language, I usually use LLMs to write the first draft of my pull requests. For this reason, I do not want a complete ban on LLM-generated code.
In the past one or two weeks, several very powerful AI models from China have been released. Kimi K3 and Qwen3.8-Max are two examples. At the same time, mid-level models with surprisingly low prices have also appeared. DeepSeek V4 Flash 0731 is one of them.
I tested these models myself. I used OpenRouter together with GitHub Codespaces, and I also used Perplexity. In my tests, Kimi K3 was still not as capable as ChatGPT or Codex, and it had no clear advantage in cost. However, Kimi was willing to help with computational biology research. Claude is known for limiting its capabilities in this area. I think this difference is worth noting.
The model that impressed me most was Xiaomi’s MiMo. Its price is surprisingly low, and it can keep working on a task for a long time. The model itself is not very powerful. Even so, the final output was better than I expected.
Until now, most discussions about AI-generated code have assumed a choice among three services: Claude, Codex, or Gemini. That assumption is now starting to change. I am watching to see how this change will affect the debate about AI and open source, or whether it will affect it at all.