Given that Python tends to produce fewer hallucinations when generated by LLMs I wonder if former Django developers using AI tools are secretly having a blast right now.

I think another ace up Django's sleeve is that it has had a remarkable stable API for a long time with very few breaking changes, so almost all blogposts about Django that the LLM has gobbled up will still be mostly correct whether they are a year or a decade old.

I get remarkably good and correct LLM output for Django projects compared to what I get in project with more fast moving and frequently API breaking frameworks.

Whenever I saw people complain about LLMs writing code, I never really understood why they were so adamant that it just didn’t work at all for them. The moment I did try to use LLMs outside of Django, it became clear that some frameworks are just much easier to work with LLMs than others. I immediately understood their frustrations.

What a lot of people don’t know is that SWE-bench is over 50% Django code, so all of the top labs hyper optimize to perform well on it.

If Python produces less hallucinations it's not because of the syntax, it's because there's so much training data.