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State of AI-assisted software development

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Re: State of AI-assisted software development

#51

Post by driverdan »

xgbi wrote: post #33

Rant mode on. For the second time of the week this morning, I spent 45 min reviewing a merge request where the guy has no idea what he did, didn’t test, and let the llm hallucinate a very bad solution to a simple problem. He just had to read the previous commit, which introduced the bug, and think about it for 1min. We are creating young people that have a very limited attention span, have no incentive to think about…

> We are creating young people that have a very limited attention span

This isn't about age. I'm in my 40's and my attention span seems to have gotten worse. I don't use much social media anymore either. I see it in other people too regardless of age.

Re: State of AI-assisted software development

#52

Post by akomtu »

xgbi wrote: post #33

Rant mode on. For the second time of the week this morning, I spent 45 min reviewing a merge request where the guy has no idea what he did, didn’t test, and let the llm hallucinate a very bad solution to a simple problem. He just had to read the previous commit, which introduced the bug, and think about it for 1min. We are creating young people that have a very limited attention span, have no incentive to think about…

When neuralink becomes usable, the same hordes of people will rush to install the AI plugin so it can relieve their brains from putting in any effort. The rest will be given a difficult choice: do the same or become unemployable in the new AI economy.

Re: State of AI-assisted software development

#53

Post by surgical_fire »

cloverich wrote: post #44

Its puzzling to me that people are still debating productivity after its been good enough to quantify for a while now. My (merged) PR rate is up about 3x since i started using claude code over the course of a few months. I correspondingly feel more productive and that i have a good grasp of what it can and cannot do. I definitely see some people use it wrong. I also see it fail on some tasks id expect it to succeed a…

Measuring commit rates is a bad metric. It varies depending on the scope and complexity of what I am doing, and the size of individual commits.

I can increase dramatically my number of commits by breaking up my commits in very small chunks.

Typically when I am using AI I tend to reduce a lot the scope of a commit to make it more focused and easier to handle.

Re: State of AI-assisted software development

#55

Post by thinkmassive »

Pannoniae wrote: post #8
pluc wrote: post #4

Every study I've read says nobody is seeing productivity gains from AI use. Here's an AI vendor saying the opposite. Funny.

There's a few explanations for this, and it's not necessarily contradictory. 1. AI doesn't improve productivity and people just have cognitive biases. (logical, but I also don't think it's true from what I know...) 2. AI does improve productivity, but only if you find your own workflow and what tasks it's good for, and many companies try to shoehorn it into things which just don't work for it. 3. AI does improve prod…

What's the difference between 1 & 5?

I've personally witnessed every one of these, but those two seem like different ways to say the same thing. I would fully agree if one of them specified a negative impact to productivity, and the other was net neutral but artificially felt like a gain.

Re: State of AI-assisted software development

#56

Post by tmaly »

xgbi wrote: post #33

Rant mode on. For the second time of the week this morning, I spent 45 min reviewing a merge request where the guy has no idea what he did, didn’t test, and let the llm hallucinate a very bad solution to a simple problem. He just had to read the previous commit, which introduced the bug, and think about it for 1min. We are creating young people that have a very limited attention span, have no incentive to think about…

there is a temptation to fight AI slop with AI slop

Re: State of AI-assisted software development

#57

Post by kemayo »

karakot wrote: post #54
kemayo wrote: post #32

I'm curious what their sample set for this survey was, because "90% of software developers use AI, at a median of 2 hours a day" is more than I'd have expected. (But maybe I'm out of touch!)

well, just assume it's an IDE with 'smarter' autosuggest.

That's fair -- the vibe of the post was making me think of the more "Claude, write a function to do X" style of development, but a bunch of people answering the survey with "oh yeah, Xcode added that new autocomplete didn't it?" would do a lot to get us to that kind of number.

Re: State of AI-assisted software development

#58

Post by xgbi »

Archelaos wrote: post #38
xgbi wrote: post #33

Rant mode on. For the second time of the week this morning, I spent 45 min reviewing a merge request where the guy has no idea what he did, didn’t test, and let the llm hallucinate a very bad solution to a simple problem. He just had to read the previous commit, which introduced the bug, and think about it for 1min. We are creating young people that have a very limited attention span, have no incentive to think about…

Why did you I spent 45 min reviewing instead of outright rejecting it? (Honest question.)

Cause the codebase wasn't in my scope originally and I had to review in emergency due to a regression in production. I took the time to understand the issue at hand and why the code had to change.

To be clear, the guy moved back a Docker image from being non-root (user 1000), to reusing a root user and `exec su` into the user after doing some root things in the entrypoint. The only issue is that when looking at the previous commit, you could see that the K8S deployment using this image wrongly changed the userId to be 1000 instead of 1001.

But since the coding guy didn't take the time to take a cursory look at why working things started to not work, he asked the LLM "I need to change the owner of some files so that they are 1001" and the LLM happily obliged by using the most convoluted way (about 100 lines of code change).

The actual fix I suggested was:

    securityContext:
  -    runAsUser: 1000
  +    runAsUser: 1001

Re: State of AI-assisted software development

#59

Post by xgbi »

JLO64 wrote: post #42
xgbi wrote: post #33

Rant mode on. For the second time of the week this morning, I spent 45 min reviewing a merge request where the guy has no idea what he did, didn’t test, and let the llm hallucinate a very bad solution to a simple problem. He just had to read the previous commit, which introduced the bug, and think about it for 1min. We are creating young people that have a very limited attention span, have no incentive to think about…

I'm not surprised to see reports like this for open source projects where the bar for contributing is relatively low, but am surprised to see it in the workplace. You'd imagine that devs like that would be filtered out via the hiring process... I'm a coding tutor and the most frustrating part of my job is when my students use LLM generated code. They have no clue what the code does (or even what libraries they're usi…

Same, I use LLMs to figure out the correct options to pass in the AZ or the AWS CLI, or some low-key things. I still code on my own.

But our management has drunk the Kool Aid and has now everybody obliged to use Copilot or other LLM assists.

Re: State of AI-assisted software development

#60

Post by fluoridation »

cogman10 wrote: post #14
wiz21c wrote: post #2

> This indicates that AI outputs are perceived as useful and valuable by many of this year’s survey respondents, despite a lack of complete trust in them. Or the respondents have hard times admitting AI can replace them :-) I'm a bit cynical but sometimes when I use Claude, it is downright frightening how good it is sometimes. Having coded for a lot of year, I'm sometimes a bit scared that my craft can, somtimes, be…

So long as you view AI as a sometimes competent liar, then it can be useful. I've found AI is pretty good at dumb boilerplate stuff. I was able to whip out prototypes, client interfaces, tests, etc pretty fast with AI. However, when I've asked AI "Identify performance problems or bugs in this code" I find it'll just make up nonsense. Particularly if there aren't problems with the code. And it makes sense that this is…

>AI has been trained on a mountain of boilerplate and a thimble of performance and bug optimizations.

That's not exactly it, I think. If you look through a repository's entire history, the deltas for the bug fixes and optimizations will be there. However, even a human who's not intimately familiar with the code and the problem will have a hard time understanding why the change fixes the bug, even if they understand the bug conceptually. That's because source code encodes neither developer intent, nor specification, nor real design goals. Which was cause of the bug?

* A developer who understood the problem and its solution, but made a typo or a similar miscommunication between brain and fingers.

* A developer who understood the problem but failed to implement the algorithm that solves it.

* An algorithm was used that doesn't solve the problem.

* The algorithm solves the problem as specified, but the specification is misaligned with the expectations of the users.

* Everything used to be correct, but an environment change made it so the correct solution stopped being correct.

In an ideal world, all of this information could be somehow encoded in the history. In reality this is a huge amount of information that would take a lot of effort to condense. It's not that it wouldn't have value even for real humans, it's just that it would be such a deluge of information that it would be incomprehensible.

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