| ▲ | vouwfietsman 15 hours ago | |||||||||||||||||||||||||||||||
I think it would make sense to have these issues bubble up into the public consciousness of hackernews. I've never used AI to code, I'm a software architect and currently assume I get little value out of an LLM. It would be useful for me if this debate had a vaguely engineering-smelling quality to it, because its currently just two groups shouting at eachother and handwaving criticism away. If you actually deal with AI generated problems, I love it, please make a post about it so we have something concrete to point to. | ||||||||||||||||||||||||||||||||
| ▲ | insin 11 hours ago | parent | next [-] | |||||||||||||||||||||||||||||||
PRs where somebody who clearly doesn't know the tech being used well enough, or enough about how the complex app they're working on really works, thus isn't able to determine a good design from a bad one for the feature they're working on, but has AI*-assisted themselves to something which "works", can become an absolute death spiral. I wasted so much work time trying to steer one of these towards the light, which is very demotivating when design and "why did you do this?" questions are responded to with nothing but another flurry of commits. Even taking the time to fully understand the problem and suggest an alternative design which would fix most of the major issues did nothing (nothing useful must have emerged when that was fed into the coin slot...) Since I started the review, I ended up becoming the "blocker" for this feature when people started asking why it wasn't landed yet (because I also have my own work to do), to the point where I just hit Approve because I knew it wouldn't work at all for the even more complex use cases I needed to implement in that area soon, so I could just fix/rewrite it then. From my own experience, the sooner you accept code from an LLM the worse a time you're going to have. If wasn't a good solution or even was the wrong solution from the get-go, no amount of churning away at the code with an LLM will fix it. If you _don't know_ how to fix it yourself, you can't suddenly go from reporting your great progress in stand-ups to "I have nothing" - maybe backwards progress is one of those new paradigms we'll have to accept? | ||||||||||||||||||||||||||||||||
| ▲ | JackSlateur 14 hours ago | parent | prev [-] | |||||||||||||||||||||||||||||||
Here is a sample We are talking about a "stupid" tool that parses a google sheet and makes calls to a third-party API So there is one google sheet per team, with one column per person One line per day And each day, someone is in charge of the duty The tool grabs the data from the sheet and configures pagerduty so that alerts go to the right person Very basic, no cleverness needed, really straightforward actually So we have 1 person that wrote the code, with AI. Then we have a second person that checked the code (with AI). Then the shit comes to my desk. To see this kind of cruft:
And then, we have 5 usage like this:
No HTTP keep-alive, no TCP reuse, the API key is passed down to every method, so is the API's endpoint. Timeout is defined in each method.
The file is ~800 lines of python code, contains 19 methods and only deals with pagerduty (not google sheet). It tooks 2 fulltime days.These people fail to produce anything meaningful, this is not really a surprise given their failure to do sane things with such a basic topic Does AI brings good idea: obviously no, but we knew this. Does AI improves the quality of the result (regardless of the quality of the idea): apparently no Does AI improves productivity: again, given this example: no Are these people better, more skilled or else: no Am I too demanding ? Am I asking too much ? | ||||||||||||||||||||||||||||||||
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