AI slows down open source developers. Peter Naur can teach us why • Hacker News Board

Re: AI slows down open source developers. Peter Naur can teach us why

#91

Post by afro88 » Mon, Jul 14, 2025, 5:13 PM UTC

I said this when the linked paper was shared and got downvotes: it's based on early 2025 data. My point isn't that it should be completely up to date, but that how we need to consider it in that context. This is pre Claude 4, Claude Code. Pre Gemini 2.5 even. These models are such a big step up from what came previously.

Just like we put a (2023) on articles here so they are considered in the right context, so too this paper should be. Blanket "AI tools slow sown development" statements with a "look this rigorous paper says so!" is ignoring a key variable: the rate of effectiveness improvement. If said paper evaluated with the current models, the picture would be different. Also in 3 months time. AI tools aren't a static thing that either works or don't indefinitely.

Re: AI slows down open source developers. Peter Naur can teach us why

#92

Post by Vegenoid » Mon, Jul 14, 2025, 5:14 PM UTC

Navarr wrote: post #67

Vegenoid wrote: post #45

Earlier quoted context omitted.

I have had similar experiences as you, but this is not the kind of work that the study is talking about: “When open source developers working in codebases that they are deeply familiar with use AI tools to complete a task, they take longer to complete that task” I have anecdotally found this to be true as well, that an LLM greatly accelerates my ramp up time in a new codebase, but then actually leads me astray once I…

> I have anecdotally found this to be true as well, that an LLM greatly accelerates my ramp up time in a new codebase, but then actually leads me astray once I am familiar with the project. If you are unfamiliar with the project, how do you determine that it wasn't leading you astray in the first place? Do you ever revisit what you had done with AI previously to make sure that, once you know your way around, it was d…

In some cases, I have not revisited, as I was happy to simply make a small modification for my use only. In others, I have taken the time to ensure the changes are suitable for upstreaming. In my experience, which I have not methodically recorded in any way, the LLM’s changes at this early stage have been pretty good. This is also partly because the changes I am making at the early stage are generally small, usually not requiring adding new functionality but simply hooking up existing functionality to a new input or output.

What’s most useful about the LLM in the early stages is not the actual code it writes, but its reasoning that helps me learn about the structure of the project. I don’t take the code blind, I am more interested in the reasoning than the code itself. I have found this to be reliably useful.

Re: AI slows down open source developers. Peter Naur can teach us why

#93

Post by jdiff » Mon, Jul 14, 2025, 5:23 PM UTC

piker wrote: post #37

My main two attempts at using an “agentic” coding workflow were trying to incorporate an Outlook COM interface into my rust code base and to streamline an existing abstract windows API interaction to avoid copying memory a couple of times. Both wasted tremendous amounts of time and were ultimately abandoned leaving me only slightly more educated about windows development. They make great autocompletion engines but I…

They make great autocompletion engines, most of the time. It's nice when it can recognize that I'm replicating a specific math formula and expands out the next dozen lines for me. It's less nice when it predicts code that's not even syntactically valid for the language or the correct API for the library I'm using. Those times, for whatever reason, seem to be popping up a lot in the last few weeks so I find myself disabling those suggestions more often than not.

Re: AI slows down open source developers. Peter Naur can teach us why

#94

Post by blake1 » Mon, Jul 14, 2025, 5:24 PM UTC

I think a reasonable summary of the study referenced is that: "AI creates the perception of productivity enhancements far beyond the reality."

Even within the study, there were some participants who saw mild improvements to productivity, but most had a significant drop in productivity. This thread is now full of people telling their story about huge productivity gains they made with AI, but none of the comments contend with the central insight of this study: that these productivity gains are illusions. AI is a product designed to make you value the product.

In matters of personal value, perception is reality, no question. Anyone relying heavily on AI should really be worried that it is mostly a tool for warping their self-perception, one that creates dependency and a false sense of accomplishment. After all, it speaks a highly optimized stream of tokens at you, and you really have to wonder what the optimization goal was.

Re: AI slows down open source developers. Peter Naur can teach us why

#95

Post by Kim_Bruning » Mon, Jul 14, 2025, 5:29 PM UTC

I think different people use these tools differently. I've got mine set up to start in "rubber duck" mode, where I do rubber duck programming, before asking the AI to help me with certain tasks (if at all). Low impact utility scripts? The AI gets let off the leash. Critical core logic? I might do most of the work myself (though having a rubber duck can still be good!)

Re: AI slows down open source developers. Peter Naur can teach us why

#96

Post by threetonesun » Mon, Jul 14, 2025, 5:29 PM UTC

sodapopcan wrote: post #90

lsy wrote: post #76

Typically debugging, e.g., a tricky race condition in an unfamiliar code base would require adding logging, refactoring library calls, inspecting existing logs, and even rewriting parts of your program to be more modular or understandable. This is part of the theory-building. When you have an AI that says "here is the race condition and here is the code change to make to fix it", that might be "faster" in the immedia…

This is always my thought whenever I hear the "AI let me build a feature in a codebase I didn't know in a language I didn't know" (which is often, there is at one in these comments). Great, but what have you learned? This is fine for small contributions, I guess, but I don't hear a lot of stories of long-term maintenance. Unpopular opinion, though, I know.

I guess it's a question of how anyone learns. There's some value in typing code, I suppose, but with tab complete that's been gone for a long time. Letting AI write something and then reading it seems as good as copying and pasting from some other source.

Re: AI slows down open source developers. Peter Naur can teach us why

#97

Post by ringeryless » Mon, Jul 14, 2025, 5:29 PM UTC

not to mention the annoyance of AI assisted issues being opened, many times incorrectly due to hallucinations. these tickets hammer human teams with nonsense and suck resources away from real issues.

Re: AI slows down open source developers. Peter Naur can teach us why

#98

Post by alganet » Mon, Jul 14, 2025, 5:29 PM UTC

This idea that some developers have some "mental model" and others not is an extraordinary claim, and I don't see extraordinary evidence.

It sounds like a good thing, right? "Wow, mental model. I want that, I want to be good and have big brain", which encourages you to believe the bullshit.

The truth is, this paper is irrelevant and a waste of time. It only serves the purpose of creating discussion around the subject. It's not science, it's a cupholder for marketing.

Re: AI slows down open source developers. Peter Naur can teach us why

#99

Post by jampa » Mon, Jul 14, 2025, 5:30 PM UTC

antimora wrote: post #50

I'm one of the regular code reviewers for Burn (a deep learning framework in Rust). I recently had to close a PR because the submitter's bug fix was clearly written entirely by an AI agent. The "fix" simply muted an error instead of addressing the root cause. This is exactly what AI tends to do when it can't identify the actual problem. The code was unnecessarily verbose and even included tests for muting the error.…

> I suspect their motivation was just to get a commit on their record. This is becoming a troubling trend with AI tools.

It has been for a while, AI just makes SPAM more effective:

https://news.ycombinator.com/item?id=24643894

Re: AI slows down open source developers. Peter Naur can teach us why

#100

Post by cogman10 » Mon, Jul 14, 2025, 5:34 PM UTC

dawnerd wrote: post #69

antimora wrote: post #50

I'm one of the regular code reviewers for Burn (a deep learning framework in Rust). I recently had to close a PR because the submitter's bug fix was clearly written entirely by an AI agent. The "fix" simply muted an error instead of addressing the root cause. This is exactly what AI tends to do when it can't identify the actual problem. The code was unnecessarily verbose and even included tests for muting the error.…

That's what I love about LLMs. You can spot it doesn't know the answer, tell it that it's wrong and it'll go, "You're absolutely right. Let me actually fix it" It scares me how much code is being produced by people without enough experience to spot issues or people that just gave up caring. We're going to be in for wild ride when all the exploits start flowing.

My favorite LLM moment. I wrote some code, asked the LLM "Find any bugs or problems with this code" and of course what it did was hyperfocus on an out of date comment (that I didn't write). Since the problem no longer existed identified in the comment, the LLM just spat out like 100 lines of garbage to refactor the code.