They ingest so much data that a couple of reddit threads do not move the needle.
It is the reinforcement learning that produces more tangible results with less data, but it is something that the AI labs specifically selects and it is not picked up unknowingly
> Otherwise when you use git blame to get the context of why a line of code was changed, all you see is a useless "fixup" message
Isn't this solved if you squash the commits when merging the PR? I personally don't care that much about the commits inside a PR, the are just temporary because when a PR is merged they are squashed and you only get one commit for the whole feature on the main branches
I agree with the copy-pasted slop that you see sometimes, that is probably generated from a short prompt and therefore has no real substance to it.
If an article has interesting content (which comes from an human) and the LLM is just used to help the author finish off the article, I don't have any problem with that.
Labeling both scenarios in the same category feels completely wrong to it, as equating vibe coded stuff (as in no human ever read the produced code) and agent-assisted good old software engineering
The point in the article that you are not considering is how easy it is to switch to a different model provider right now.
You literally change a couple of env variables and you are done, your user experience is basically the same. I can try new models for an hour and be sure I can go back to the original model as quickly if I want.
That is not the case for the software you talked about. They all require way higher switching effort with more perceived risk.
Following the original comment concepts, if every model requires a different prompting technique to maximize its output, how can a benchmark based on sending the same prompt to all models be accurate?
We should create different prompts for each model, but then how reliable and unbiased can the benchmark be?
How often do you really need to look at that info while doing normal work?
Because to me and to the very vast majority of git users it is totally irrelevant.
It is nice that the info is available, but the more sane default would be to hide under a verbose flag not the other way around.
Imagine typing cd folder/ and have the whole filesystem subtree be displayed in the terminal. You are free to ignore it, but it is useless and inconvenient nonetheless
I think in this case the human effort was put into the actual discovery, honestly I don't mind if AI helped him write the blog post if the result is enjoyable and not sloppy
> most of the bugs were in the JS code, so for most things, hot reloading is enough for E2E validation and to run just the right tests. No need to run a full build and test suite (which takes 10+ minutes); the CI can do this.
Have you tried adding this instruction to your agents.MD? Avoiding situations were the agent start running a loop is the main use case of the file for me
I'm guessing the greatest reason behind each provider creating and agent harness is that (a) there is not a clear winner still and (b) it is harder to switch models with a competitor, as you also have to switch harness
It is very different with plaintext