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by gck1
66 days ago
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Agreed, but it's a bit nuanced. I'm working on a fairly complex project now in a domain where I have no technical experience. The first iteration of the project was complete garbage, but it was garbage mainly because I asked for things to be done and never asked HOW it should be done. Result? Complete, utter garbage. It kinda, sorta worked, but again, I would never use it in anything important. Then we went through ~10 complete rewrites based on the learnings from previous attempts. As we went through these iterations, I became much more knowledgeable of the domain - because I saw failure points, I read the resulting code and because I asked the right questions. Without AI, I would likely have given up after iteration 2, and certainly would not do 10 iterations. So the nuance here is that iterating and throwing away the entire thing is going to become much cheaper, but not without an engineer being in the loop, asking the right questions. Note: each iteration went through dual reviews of codex and opus at each phase with every finding fixed and review saying everything is perfect, the best thing on earth. |
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The problem is that vanishingly few people actually understand the code and are asking the agents to do all of the interpretation and reasoning for them.
This code that you've built is only maintainable for as long as you are still around at the company to work on it -- it's essentially a codebase that you're the only domain expert in. That's not a good outcome for companies either.
My prediction is that the companies that learn this lesson are the ones that are going to stick around. LLMs won't be in wide use for features but for throwaway busy-work type problems that eat lots of human resources and can't be ignored.