In an ideal world there is a tool that moves your schema into an analytical store “as is” with a single click. Then the same tool lets you add arbitrary transformations of the data. Surprisingly I have not come across such a tool. It is earthier “one click to move your data” or “any transformation you want” but only after a significant upfront investment :(

One reason why you want warm air in the car is defrosting your windows.

I have set temperature to 21 C in Tesla when I bought it and never changed since. Why would anyone frequently change a thermostat set temperature?

This is not how the process went. This is how Jarred thinks it went, a huge difference.

>my guess is that the LLM wrote a transpiler to do the job

My guess is different. I think one agent translated code, another compiled it, feeding errors back into translator to fix. Then last agent modifies code to fix tests. All governed by a set of md files.

I took tests as an example. There are so many other things that can go wrong. Rust and Zig standard libraries may have different semantics not picked up by AI. Like one guarantees insertion order of a dictionary and other does not. Differences in how runtimes react to Linux signals, how they do file IO, etc.

If I were a Bun user I would be moving off from bun unless it has excellent test coverage (which I think it does not). During a normal release cycle I offered a small increment of functionality with small number of issues. Here I’ve been offered a complete rewrite, potentially having thousands of issues. I don’t want to be a guinea pig in this experiment.

I’m genuine curious how this will unfold.

>It already has been proven that LLM's can maintain such codebases.

Proven is a strong word. In my experience AI fails miserably at anything beyond junior level tasks. We will see soon, once bun goes into production.

I also admit that the blogpost is lacking in many respects.

Having 90k LoC of tests for 50k LoC codebase also a problem. At least in my experience LLM generate too many tests. It does not evolve test suite but throws more code into it as development happens. Unless I aggressively refactor tests I quickly end up with a test suite that I don’t understand. Then LLM modifies tests to “make code work” and I have no idea if this is a legit edit or LLM cheats. I wonder if the same thing is happening or about to happen with this codebase.

The blog post mentioned the project is 130k LoC multiple times. Where 45/50k LoC comes from?

>Rust makes no promise of being terser than C++

True, but Rust has no header files, this alone is a great LoC saver.

In the end it is just a lot of unmaintainable code quickly generated by AI.

Original RSL library has 36 KLoC across C++ source and headers files. Rust supposed to be more expressive and concise. Yet, AI generated 130k LoCs. I guess nobody understands how this code works and nobody can tell if it actually works.