281–290 of 580 posts
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When their performance reviews stop depending upon them not doing that. Microsoft's stock price is dependent on them proving that this is a success.
What happens when they can't prove that and development efficiency starts falling, because developers spend 50% of their time battling copilot?
Seeing Microsoft employees argue with an LLM for hours instead of actually just fixing the problem must be a very encouraging sight for businesses that have built their products on top of .NET.
You don't want them to experiment with new tools? The main difference now is that the experiment is public.
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At least we can tell the junior developers to not submit a pull-request before they have the tests running locally. At what point does the human developers just give up and close the PRs as "AI garbage". Keep the ones that works, then just junk the rest. I feel that at some point entertaining the machine becomes unbearable and people just stops doing it or rage close the PRs.
When their performance reviews stop depending upon them not doing that. Microsoft's stock price is dependent on them proving that this is a success.
Perhaps this explains the recent firings that affected faster CPython and other projects. While they throw money at AI but sucess still doesn't materialize, they need to make the books look good for yet another quarter through the old-school reliable method of laying off people left and right.
Beyond every other absurdity here, well, maybe Microsoft is different, but I would never assign a PR that was _failing CI_ to somebody. That that's happening feels like an admission that the thing doesn't _really_ work at all; if it worked even slightly, it would at least only assign passing PRs, but presumably it's bad enough that if they put in that requirement there would be no PRs.
I feel like everyone is applying a worse-case narrative to what's going on here.. I see this as a work in progress.. I am almost certain the humans in the loop on these PRs are well aware of what's going on and have their expectations in check, and this isn't just "business as usual" like any other PR or work assignment. This is a test. You can't improve a system without testing it on real world conditions. How do we…
>> This is a test. You can't improve a system without testing it on real world conditions.
Software developers know to fix build problems before asking for a review. The AIs are submitting PRs in bad faith because they don't know any better. Compilers and other build tools produce errors when they fail, and the AI is ignoring this first line of feedback.
It is not a maintainers job to review code for syntax errors, or use of APIs that don't actually exist, or other silly mistakes. That's the compilers job and it does it well. The AI needs to take that feedback and fix the issues before escalating to humans.
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I feel like everyone is applying a worse-case narrative to what's going on here.. I see this as a work in progress.. I am almost certain the humans in the loop on these PRs are well aware of what's going on and have their expectations in check, and this isn't just "business as usual" like any other PR or work assignment. This is a test. You can't improve a system without testing it on real world conditions. How do we…
>> I see this as a work in progress.. I am almost certain the humans in the loop on these PRs are well aware of what's going on and have their expectations in check, and this isn't just "business as usual" like any other PR or work assignment. >> This is a test. You can't improve a system without testing it on real world conditions. Software developers know to fix build problems before asking for a review. The AIs ar…
rah, we might be in trouble here. The primary issue at play is that we don't have a reliable means of measuring developer performance, outside of subjective judgement like end of year reviews. This means its probably quite hard to measure the gain or the drag of using these agents. On one side, its a lot cheaper than a junior, but on the other side it pulls time from seniors and doesn't necessarily follow instruction…
I’m not even sure if this is true when considering training costs of the model. It takes a lot of junior engineer salaries to amortize the billions spent building this thing in the first place.
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why does every engineer keep talking about it like it’s more than marketing hype? why do you actually accept this is a real narrative real people believe? have you talked to the executives implementing these strategies? redbull does not give you wings. it’s disconcerting to see the lack of nuance in these discussions around these new tools (and yeah sorry this isn’t really aimed at you, but the zeitgeist, apologies)
Because this “marketing hype” is affecting the way we do our job. Some of us are being laid off due to the hype; some are assigned to babysit the AI; and some are simply looked down on by higher ups who are eagerly waiting for a day to lay us all off. You can convince yourself as much as you want that it’s “just a hype”, but regardless of your beliefs are, it has REAL world consequences.
engineers are testing promising new technology. a mob (of probably half or more bots) is having a [redacted] perpetuating the anti-narrative they huffed themselves up into believing. and now we’re in a meta-[redacted] as if either A) redditors and armchair engineers here have valid opinions on this tech and B) marketers and founders with massive incentives to overpromise are telling a true narrative
why? we don’t have to do it. we could actually look at these topics with nuance and not react like literal bots to everything
(sorry I’m just losing my faith in humanity and taking it out in this thread)
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I feel like everyone is applying a worse-case narrative to what's going on here.. I see this as a work in progress.. I am almost certain the humans in the loop on these PRs are well aware of what's going on and have their expectations in check, and this isn't just "business as usual" like any other PR or work assignment. This is a test. You can't improve a system without testing it on real world conditions. How do we…
I was looking for exactly this comment. Everybody's gloating, "Wow look how dumb AI is! Haha, schadenfreude!" but this seems like just a natural part of the evolution process to me. It's going to look stupid... until the point it doesn't. And my money's on, "This will eventually be a solved problem."
AI can remain stupid longer than you can remain solvent.
1. Working out in the open
2. Dogfooding their own product
3. Pushing the state of the art
Given that the negative impact here falls mostly (completely?) on the Microsoft team which opted into this, is there any reason why we shouldn't be supporting progress here?