125 karma · joined June 9, 2023
But the current one seems really good, tested it for quite a bit with multiple kind of inputs.
In my mind we’re switching to a workflow where code review at the end will be the most important part.
If it’s recording 15 seconds, how often are you doing that? Once every 15m as the analysis interval is 15m?
But besides that I am totally on your side, usability is great.
In the best case you would have to feed every important information into the context. These are my indexes, this is my function, these are my models. After that the model can find problematic code. So the main problem is go give your model all of the important information, that has to be fixed if the user isn’t doing that part (Obviously that doesn’t mean that the LLM will find a correct problem, but it can improve the results).
so either you put the whole codebase into the context (will mostly lead to problems as tokens are limited) or you have some kind of summary with your current features etc.
Or you do some kind of "black box" iterations, which I feel won’t be that useful for new features, as the model should know about current features etc?
What’s the way here?