I like Aider but I've turned off auto-commit. I just can't seem to let the AI actually commit code for me. Do you regularly let Aider commit for you? How much do you review the code written by it?
I originally was against auto commit as well, but now I can’t imagine not using it. It’s essentially save points along the way. More than once, I’ve done two or three exchanges with Aider only to realize that the path that we were going down was not a good one.
Being able to get reset back to the last known good state is awesome. If you turn off auto commit, it’s a lot harder to undo one of the steps that the model takes. It’s only a matter of time until it creates nonsense, so you’ll really want the ability to roll it back.
Just work in a branch and you can merge all commits if you want at the end.
The auto-commits of Aider scared the crap out of me at first too, but after realizing I can just create a throwaway branch and let it run wild it ended up being a nice way to work.
I've been trying to use Sonnet 3.7 tonight through the Copilot agent and it gets frustrating to see the API 500 halfway through the task list leaving the project in a half baked state, and then and not feeling like I have a good "auto save" to pick up again from.
I create a feature branch, do the work and let it commit. I check the code as I go. If I don't like it, then I revert to a previous commit. Other times I write some code that it isn't getting right for whatever reason.
The beauty of git is that local commits don't get seen by anybody until you push. so you can commit early and commit often, since no one else is gonna see it, which gets you checkpoints before, during, and after you dive into making a big breaking change in the code. once you've got something you like, then you can edit, squash, and reorder the local commits and clean them up for consumption by the general public.
You've beautifully put what swirls vaguely in my mind. They're useful, fallible tools with extraordinary function when operating within known and reasonable tolerances of error
They can also reason, but the reasoning is limited and unreliable.
Q:How many playing cards are needed for a pyramid that is 3 layers high? Show reasoning and number of cards for leach layer.
Q: Chess. You have a King and 8 pawns. Your opponent has a King and 16 pawns. Your opponent plays white and can start, but you can position both your pawns and your opponents pawns any way you like before game starts. Kings are where they are normally. How do you do it? Explain your reasoning.
How excellent for a quantized 27GB model (the Q6_K_L GGUF quantization type uses 8 bits per weight in the embedding and output layers since they're sensitize to quantization)
and many of these people havent debugged messages more complex than a Python error message. tastelessly jabbing at needing to earn your marks by slamming into segfaults and pushing gdb