Regardless of how you feel about using LLMs or using products that are developed with LLMs, it is a good idea to have an ecosystem of open source projects with differing levels of LLM involvement, including pristine software written entirely by humans.

The pragmatic argument for hard no-LLM projects: if models are to be useful, they need good input. Hand-written software that has been carefully audited is free from the kinds of feedback errors that will eventually weaken LLM code generation. Otherwise, a bad pattern gets copied. In the next generation, this bad pattern is seen a bit more often as stochastic models converge on it and more open source code adopts it. This is reinforced in the next generation and it becomes a common pattern. Then, in the next generation, this pattern is seen all over. This could be inert "non-coding DNA" like weird naming conventions or pointless comments. Or, it could be bad edge cases that become commonly exploitable.