| ▲ | logicchains 2 hours ago | |
From what you said it sounds like the conclusion should be "you still need to design the architecture yourself", not necessarily "you still need to write your own code". | ||
| ▲ | parliament32 2 hours ago | parent | next [-] | |
But he did design the architecture: > even though Memory.md has the AWS EC2 instance and instructions well defined I will second that, despite the endless harping about the usefulness of CC, it's really not good at anything that hasn't been done to death a couple thousand times (in its training set, presumably). It looks great at first blush, but as soon as you start adding business-specific constraints or get into unique problems without prior art, the wheels fall off the thing very quickly and it tries to strongarm you back into common patterns. | ||
| ▲ | dvt 2 hours ago | parent | prev [-] | |
Yeah, I actually wanted to write an addendum, so I'll just do it here. I think that going from pseudocode -> code is a pretty neat concept (which is kind of what I mean by "write your own code"), but not sure if it's economically viable if the AI industry weren't so heavily subsidized by VC cash. So we might end back up at writing actual code and then telling the AI agent "do another thing, and make it kinda like this" where you point it to your own code. I'm doing it right now, and tbh working on greenfield projects purely using AI is extremely token-hungry (constantly nudging the agent, for one) if you want actual code quality and not a bloated piece of garbage[1][2]. | ||