▲ | cmdli 3 days ago | |||||||||||||||||||||||||||||||||||||||||||||||||
My experience has been entirely the opposite as an IC. If I spend the time to delve into the code base to the point that I understand how it works, AI just serves as a mild improvement in writing code as opposed to implementing it normally, saving me maybe 5 minutes on a 2 hour task. On the other hand, I’ve found success when I have no idea how to do something and tell the AI to do it. In that case, the AI usually does the wrong thing but it can oftentimes reveal to me the methods used in the rest of the codebase. | ||||||||||||||||||||||||||||||||||||||||||||||||||
▲ | zarzavat 3 days ago | parent | next [-] | |||||||||||||||||||||||||||||||||||||||||||||||||
Both modes of operation are useful. If you know how to do something, then you can give Claude the broad strokes of how you want it done and -- if you give enough detail -- hopefully it will come back with work similar to what you would have written. In this case it's saving you on the order of minutes, but those minutes add up. There is a possibility for negative time saving if it returns garbage. If you don't know how to do something then you can see if an AI has any ideas. This is where the big productivity gains are, hours or even days can become minutes if you are sufficiently clueless about something. | ||||||||||||||||||||||||||||||||||||||||||||||||||
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▲ | teaearlgraycold 3 days ago | parent | prev [-] | |||||||||||||||||||||||||||||||||||||||||||||||||
LLMs are great at semantic searching through packages when I need to know exactly how something is implemented. If that’s a major part of your job then you’re saving a ton of time with what’s available today. |