alt Hacker NewsI love this train of thought. Code quality is critical, but I don’t think we’re correctly evaling it at the moment. If we could get solid benchmarks measuring the quality of generated code, we might see the models climb those benches fast.
I believe that the era of “ai writes tons of slop code” will be a stepping stone in the longer story, and is simply a current gap in the reward functions.
Per the author - if we can get strong measurements of what good code is, we can train against it and close the gap fast. Excited to see more thinking in this area
Replies
Sooooo much of what is considered "code quality" today is irrelevant when robots are writing the code. We've been largely optimizing for things like composability/unit testability in the past 15 or so years, and that's primarily a human concern that's unrelated to the final output.
Totally agreed that we're not looking at the correct metric right now. Increasingly, code quality will be determined by outcomes.
If you could easily benchmark the quality of code then models would be trained on these benchmarks/metrics.