I would argue that if flipping a feature flag isn't faster than doing a rollback, your feature flags are not functional. They should be essentially instantaneous and the first thing to reach for as soon as you've identified a problem.

> Also sometimes flipping feature flags can be faster than doing a rollback, especially if multiple systems are involved.

This I totally agree with. Using feature flags well requires some discipline on the team's part to stay on top of them and remove them once they've served their purpose.

Every time ORMs get discussed, it seems to be dominated by people who are like "but my app has 5 billion concurrent users doing 2 million requests per second and if there's an extra 5ms on my requests, it will all explode!" and can't comprehend that not everyone is building the same kind of systems all the time. Great, maybe an ORM isn't appropriate for your situation.

How long ago was this? I feel like unicode has kind of been a solved problem in Python since python3 came out. In the python2 days it was, indeed, miserable.

I didn't use Fable (just Opus and Gemini) but I recently ported the `djlint` Python library to Rust, also relying heavily on LLMs (but not trying to one-shot it). `djlint` is a library to lint and reformat HTML and Django template files (and some other formats but I haven't tackled them yet as I don't really have any need). It's currently unmaintained (for a couple years at least) but was part of our CI/CD and the reformat in particular is very slow on a large codebase with thousands of templates. For our code, it took about 4 minutes to run. I generated a Rust port in a similar way, aiming for byte-for-byte output compatability. The Rust version runs on the same code in a fraction of a second; fast enough to put in a pre-commit hook. Some of that was the raw Python->Rust conversion, but a lot was some optimization work that I did afterwards. The Python version was heavily regexp-based, basically running a big slow regexp for every rule that it implements, sometimes running the regexp in a loop starting with each tag it encounters as it goes through each file. For the Rust version, I switched it to properly tokenize the files and then match rules on the AST in a single (or relatively few in some cases) pass. Honestly, there's still a lot of low hanging fruit to make it faster but it's already such a big improvement that I'm pretty happy with it. I'm sure those optimizations could've been done in Python but if I'm the one maintaining the code now, I'd much rather deal with Rust than Python with or without LLM assistance.