1,566 karma · joined May 23, 2013
I think it's not an option. The benefits are just too large for me.
>I do know we will never go back to mainly programming through code again, that’s for sure.
I think, in some niches, i.e. where there's something not well represented in the training set, it still makes sense to write code by hand. But I am not sure that it will continue.
IMO, the goal should be to outsource as much work to the model, as possible, while minimizing effort required to understand and review what is did. For example: ask the model to find out why a bug happens, figure out proof of concept for thing X, incrementally optimize something, do a well specified refactoring with some guide, and similar things.
IMO, what people say about creating loops is a very similar thing. You maximize the work done by the model, while minimizing the amount you need to do to control it.
Could you share what tells about it? I.e. where he was wrong about it?
Do you think it's not slowing? Do I miss anything really important?
My understanding is that we have now is incremental improvement on thinking models which appeared more than a year ago. Of course, a breakthrough might happen, but I don't see one yet.
Could you explain this?
Currently, the difference is substantial, but what happens if capabilities saturate?
Could you please share more about this
If the project I work on is large enough, it takes me some time to get everything I need to understand for review into the short term memory. If it's small enough, it's less of a problem for me.
How do they do it? (My own record is 5 agents, but it is not typical). Do they use gastown or something?