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119 points lsharkey602 | 2 comments | | HN request time: 0s | source
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reedf1 ◴[] No.44423223[source]
I think it is possible that the widespread introduction of ChatGPT will cause a brief hiatus on hiring due to the inelasticity of demand. For the sake of argument, imagine that ChatGPT makes your average developer 4x more productive. It will take a while before the expectation becomes that 4x more work is delivered. That 4x more work is scheduled in sprints. That 4x more features are developed. That 4x more projects are sold to clients/users. When the demand eventually catches up (if it exists), the hiring will begin again.
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TSiege ◴[] No.44423440[source]
I am not asking this as a gotcha, but a genuine curiosity for you or other people who find AI is helping them in terms of multiples. What is your workflow like? Where do you lean on AI vs not? Is it agentic stuff is tab by cursor?

I find AI helpful but no where near a multiplier in my day to day development experience. Converting a csv to json or vis-versa great, but AI writing code for me has been less helpful. Beyond boiler plate, it introduces subtle bugs that are a pain in the ass to deal with. For complicated things, it struggles and does too much and because I didn't write it I don't know where the bad spots are. And AI code review often gets hung up on nits and misses real mistakes.

So what are you doing and what are the resources you'd recommend?

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1. ninetyninenine ◴[] No.44423843[source]
Don’t ask the agent to do something complex. Break it down into 10 manageable steps. You are the tester and verifier of each step.

What you will find is that the agent is much more successful in this regard.

The LLM has certain intrinsic abilities that match us and like us it cannot actually code 10,000 lines of code and have everything working in one go. It does better when you develop incrementally and verify each increment. The smaller the increments the better it performs.

Unfortunately the chain of thought process doesn’t really do this. It can come up with steps, sometimes the steps are too big and it almost never properly verifies things are working after each increment. That’s why you have to put yourself in the loop here.

Like allowing the computer to run test and verify an application works as expected on each step and to even come up with what verification means is a bit of what’s missing here and I think although this part isn’t automated yet, it can easily be automated where humans become less and less involved and distance themselves into a more and more supervisory role.

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2. alyandon ◴[] No.44423881[source]
Spot on - that is exactly my experience when working with LLMs.