> The main concern I have with frameworks is the inversion of control of the code logic, the lack of composition, the complexity of handling edge cases outside the scope of the framework. Frankly writing apps is not my thing typically. PyTorch is moderately unobtrusive, but other tools on top make tons of assumptions and break more often than they help in the long term.

100%; lived that story. In my experience this is usually the result of some poor design assumptions on part of the framework. Other times people want to use something for which it wasn't designed for. In the case of Burr, we still have a few things to iron out, but given our platform backgrounds, we're trying to be cognizant of things that have annoyed us in the past, e.g. two big ones: ability to customize parts given esoteric deployment needs (e.g. persistence layer); adding in observability without it coupling you/getting in the way of logic.

> the LLMs get better, you might want to focus on detailed documentation so that the future AIs can master your framework and help your users

Even without LLMs I think this is required ;)