An extrapolation to these make me think that programmers becoming like Tony Stark telling Jarvis what to do, and it gets it done. Or Minority Report style interfaces, where people will inform their intent (prompt?) and get the answers.
AI in software engineering at Google: Progress and the path ahead
201–210 of 245 posts
Re: AI in software engineering at Google: Progress and the path ahead
#202Earlier quoted context omitted.
If it works and it never needs a human, does it matter?
It works until it doesn't at which point you have a massive, useless pile of uninterpretable garbage.
Then you ask another LLM to explain it to you lol, like - I don’t think people are thinking hard enough about what this future is likely to look like.
Re: AI in software engineering at Google: Progress and the path ahead
#203Earlier quoted context omitted.
I totally agree. Reviewing the solution is limited. What you don’t get are the myriads of other ways that didn’t work out. Elegant solutions are the result of weeding out dozens of other messy ways. So what gets perpetuated here then is the Dunnimg Kruger effect. While it might be speed things up in many normal circumstances, it devalues hard work in the long run. Not good.
The Dunning-Kruger effect, and its many misspellings, might be the most overused term on this website.
Lol, 100%, it's overeducated for "dumb"
Re: AI in software engineering at Google: Progress and the path ahead
#204Earlier quoted context omitted.
Source? This is unintuitive to me, I can't come up with a rationale.
I know of no review process that produces the same level of understanding as does authorship, because the author must build the model from scratch and so must see all the details, while the reviewer is able to do less work because they're fundamentally riding on the author's understanding. In fact, in a high-trust system, e.g. a good engineering culture in a tech company, the reviewer will learn even less, because th…
> "the author must build the model from scratch and so must see all the details"
This is not true. With any complex framework, the author first learns how to use it, then when they build the model they are drawing on their learned knowledge. And when they are experienced, they don't see all the details, they just write them out without thinking about it (chunking). This is essentially what an LLM does, it short-circuits the learning process so you can write more "natural", short thoughts and have the LLM translate them into working code without learning and chunking the irrelevant details associated with the framework.
I would say that whether it is good or not depends on how clunky the framework is. If it is a clunky framework, then using an LLM is very reasonable, like how using IDEs with templating etc. for Java is almost a necessity. If it is a "fluent", natural framework, then maybe an LLM is not necessary, but I would argue no framework is at this level currently and using an LLM is still warranted. Probably the only way to achieve true fluency is to integrate the LLM - there have been various experiments posted here on HN. But absent this level of natural-language-style programming, there will be a mismatch between thoughts and code, and an LLM reduces this mismatch.
Re: AI in software engineering at Google: Progress and the path ahead
#205Earlier quoted context omitted.
Who learned stuff from stack overflow? In my own case, it was all books, plus a few videos. Stack Overflow was mostly to know why things has gone (errors not explicit enough) or very specific patterns. And there was a peer review system which lent credibility to answers.
“In my own case...” something worked for you. So what? Are you sure that would work for others? And that other approaches might not be more effective? I’ve learned lots of things from SO. The top voted answers usually provide quite a bit of “why” content which have general utility or pointers to more general content. Yes, there are insufferable people on there, but there are gatekeepers and self-centered people every…
I’ll add to their anecdote, with my own. I don’t think I’ve ever learned anything from SO. It is books and occasional videos for me too.
Re: AI in software engineering at Google: Progress and the path ahead
#206What I've learned is that a video play/pause button in the far right corner is horribly unintuitive.
Re: AI in software engineering at Google: Progress and the path ahead
#207Re: AI in software engineering at Google: Progress and the path ahead
#208Earlier quoted context omitted.
“In my own case...” something worked for you. So what? Are you sure that would work for others? And that other approaches might not be more effective? I’ve learned lots of things from SO. The top voted answers usually provide quite a bit of “why” content which have general utility or pointers to more general content. Yes, there are insufferable people on there, but there are gatekeepers and self-centered people every…
I’ll add to their anecdote, with my own. I don’t think I’ve ever learned anything from SO. It is books and occasional videos for me too.
Maybe I am being snarky, but saying “I don’t like that” or “that’s not how I did it” just isn’t that interesting. I’d love to hear why books are so much effective, for instance, or which books, or what YT channels were useful.
Re: AI in software engineering at Google: Progress and the path ahead
#209Earlier quoted context omitted.
You don't receive AI suggestions in code review, you receive suggestions from your reviewers. If they are providing bad recommendations, regardless of the source, I suggest providing them feedback. I agree this may not be how they are used, but honestly, code review is a skill and many people are bad at it. Blindly suggesting things because an AI (or a presubmit) suggests it is bad form regardless of the source. Peop…
> You don't receive AI suggestions in code review, you receive suggestions from your reviewers If a reviewer makes a comment, Critique will create an AI suggestion based on their comment, even if they didn’t explicitly do so (unless they turn off giving AI suggestions on their end, but there’s no way to stop from seeing it from the other). > not by ruling out AI tools just because they're AI tools. This was not my po…
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Re: AI in software engineering at Google: Progress and the path ahead
#210Earlier quoted context omitted.
> entirely optional Optional. I'll bet.
What would it mean for code suggestions to be non-optional? Like, you can't edit the code file yourself but have to talk to a chatbot to ask it to make the edits for you? I think that's fairly obviously a ridiculous notion.
I meant for straight opting out of even having it.