> How well do existing VCSs integrate with it? It might be because the author focuses too much on technical details and fixing Git's shortcomings, instead of taking a step back and rethinking what a modern VCS tool should look like today. Nothing jumped out at me like a killer feature that would make me want to give it a try. I just finished watching the presentation, and Pijul seems like an iterative improvement over Git. Or, since it's more than likely that humans won't be writing code or text in the near future, we'll skip the next revolution in VCS tools, and AI will be able to version its own software. If AI can write code for me, it could surely understand what I'm trying to do, and help me so that version control is entirely hands-free, instead of having to fight with it, and be constantly aware of it, as I have to do now. Nowadays, with all the machine learning advances, the ideal VCS should also use ML to understand the change at a deeper level, and maybe even suggest improvements. There has been some research in this area, and there are a few semantic diffing tools, but I'm not aware of this being widely used in any VCS. This would allow them to show actually meaningful diffs, and minimize the chances of conflicts, and of producing a corrupt file after an automatic merge. For binary files, they need to be aware of the file format and its binary structure. In the case of code bases, they need to be aware of the language and the AST of the program. Instead, the tools should be smarter and work on the level of functions, classes, packages, sentences, paragraphs, or whatever primitive makes sense for the project and file that is being changed. Merge conflicts are an issue because our tools are agnostic about the actual content they're tracking. I'm not familiar with Pijul, and haven't finished watching this presentation, but IME the problems with modern version control tools is that they still rely on comparing lines of plain text, something we've been doing for decades.
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