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It's trivial to share coding sessions, be they horrific or great. Without those, you're hot air on the internet, independent of whatever specific opinions on LLMs you voice.
Same could be said about the anti-AI crowd.
I'm glad the author made the distinction that he's talking about LLMs, though, because far too many people these days like to shout from the rooftops about all AI being bad, totally ignoring (willfully or otherwise) important areas it's being used in like cancer research.
I am curious why the author doesn't think this saves them time (i.e. makes them more productive).
I never had terribly high output as a programmer. I certainly think LLMs have helped increased the amount of code that I can write, net total, in a year. Not to superhuman levels or even super-me levels, just me++.
But, I think the total time spent producing code has gone down to a fraction and has allowed me more time to spend thinking about what my code is meant to solve.
I wonder about two things: 1. maybe added productivity isn't going to be found in total code produced, because there is a limit on how much useful code can be produced that is based on external factors 2. do some devs look at the output of an LLM and "get the ick" because they didn't write it and LLM-code is often more verbose and "ugly", even though it may work? (this is a total supposition and not an accusation in any way. i also understand that poorly thought out, overly verbose code comes with problems over time)
Simon Wilson (known for Django) has been doing a lot of LLM evangelism on his blog these days. Antirez (Redis) wrote a blog post recently with the same vibe.
I doubt they are not good programmers. They are probably better than most of us, and I doubt they feel insecure because of the LLMs. Either I'm wrong, or there's something more to this.
edit: to clarify, I'm not saying Simon and Antirez are part of the hostile LLM evangelists the article criticizes. Although the article does generalize to all LLM evangelists at least in some parts and Simon did react to this here. For these reasons, I haven't ruled him out as a target of this article, at least partly.
Hearing people on tech twitter say that LLMs always produce better code than they do by hand was pretty enlightening for me. LLMs can produce better code for languages and domains I’m not proficient in, at a much faster rate, but damn it’s rare I look at LLM output and don’t spot something I’d do measurably better. These things are average text generation machines. Yes you can improve the output quality by writing a…
No.
Personally I think the rate of improvement will plateau: in my experience software inevitably becomes less about tech and more about the interpersonal human soup of negotiating requirements, needs, contradiction, and feedback loops, at lot of which is not signal accessible to a text-in-text-out engine.
Until some days / weeks ago, LLM's for coding was more hype than actually real code producing. That is gone now. They clearly leveled up, things will not be the same anymore. And of course this is not just for coding, this is just the beginning. A month ago it really seemed that the models were hitting a complexity wall and that the architecture would need to be improved. Not anymore.