Comment by dakolli
10 hours ago
I disagree, fundamentally.
I see little value in throwing a ton of context at an llm and waiting 10-20 minutes for a coin flip on whether or not its going to produce junk. I'd rather do quick 60 second turns, get most of the way there and fix the rest myself if I have to. I'd rather honestly just not use them.
Well the point was that id rather spend 30 seconds doing it myself then formulate a prompt with enough context for the model to implement it within 60 seconds. Also these numbers are unrealistic.
Everyone that I've ever interacted with and claims to prompt in "seconds" actually needs multiple minutes to think about the solution they want the model to implement - and then need twice as long to formulate that into a sentence which provides the model enough context to actually do that
So the more realistic estimates are "I'd rather spend the 2 minutes just implementing the minor change myself, instead of spending 1.5 minutes thinking about it, then 2.5 minutes writing the prompt and then waiting 1 minute for it to finish"
I would agree with all those points, and my numbers are a little off. I really just don't want to use any of it. I'm more excited about fast FIM autocomplete that works well, something like cursor tab without cursor. If something can increase my wpm and take strain off my fingers that would be nice. At this point latency and accuracy is terrible though.
The trick is to do something else in those 20 minutes (or, ideally, even longer).
That's the main value I've been getting out of coding agents. I have them do (comparatively) simpler tasks or explorative tasks in the background while I'm in a meeting, doing code reviews, or otherwise working on something else.
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