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Comment by sothatsit | Hacker News Reader

The entire mistake you are making is comparing using AI to skimming textbooks, or taking shortcuts. Your entire premise is wrong.

People who care about craft will care about the quality of what they produce whether they use AI or not.

The code I ship now is better tested and better thought through now than before I used AI because I can do a lot more. That extra time goes into additional experiments, jumping down more rabbit holes, and trying out ideas I previously couldn’t due to time constraints. It’s freeing to be able to spend more time to improve quality because the ROI on time spent experimenting has gone up dramatically.

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I care deeply about craft, but:

a) I cannot effectively review more than 2000 lines of code a day. The LLMs can produce much more than that. b) Even if I accepted my reading throughput limitations as the cost of being in the loop, reading is not enough to keep cognitive debt in check: my skills will atrophy if I do not participate in the writing ("What I cannot create I cannot understand").

So, to me, it seems like we, humans, either have to come up with higher (and deterministic) abstractions than code to communicate with LLMs or resign ourselves to letting the LLM guess what we want from English and then banging on the output to see if it sort of works. This later state of affairs seems to be what the current trend is and I find that absolutely revolting.

I think the distinction is that for experiments and prototypes the behaviour of the final system is what we are trying to design. We can experiment and see the tradeoffs and explore the design space before committing to a direction. And then we can sit down and produce the final code to a quality we are happy with. If you are serious about this process, there is no way you are producing 1000s of lines of code a day, unless it is trivial boilerplate.

In terms of higher-level abstractions, I agree this is one particularly treacherous rung on the ladder of abstractions. Previous abstractions like compilers or garbage collectors have at least had more structure/rules to rely upon. I don't know exactly how that will look but I don't think we will solely be relying on banging on the output, we will also be spot-checking the source code, using profilers or other tools to inspect the behaviour of systems, and asking the agent to explain the architectural decisions made. I'm not sure exactly how this will look, but I do believe that people who care will still find ways to do good work.

You can keep telling yourself that. I have seen the results from others making the same arguments. The result is invariably trash.

Well you have obviously already made up your mind, so have fun with your confirmation bias. We'll all be over here having a good time, getting more work done. Feel free to come over when you put down your grudge.

My agentic workflow probably differs somewhat from the majority of others here, but I can positively guarantee you that both the quality and quantity of my output is significantly higher than it has ever been, in my 20-something years of writing code. And at least 90÷ of the code I've written this year was output by an LLM. You can keep sticking your head in the sand, in the end it will only be to your own detriment.

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