Commenters highlight new engineering challenges AI introduces
6 Sep 15 7:27 AM · 12d ago · 5 comments · 1 source · development 6 of 6
ModernMech and walrus01 pointed out that while LLMs can write code, they introduce novel problems: building inefficient interpreters, 300k-line scaffolding, and CI systems that fail constantly. walrus01 noted that experienced engineers who know how to constrain LLM behavior are building better products than amateurs attempting one-shot projects.
“Agentic engineering faces all kinds of new problems that couldn't exist before, and need experienced engineers to solve them.”
ModernMech_ZeD_ Student programmer and FOSS app maintainerF-Droid project Open-source mobile app repository
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What people said 24 voices · best of 26 · verbatim
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https:// tintotint.eu/whacky-corner/f-d roid_slop/ Only apps from one # FDroid cycle were analysed? Was that easy? What will it take to follow each cycle or scan all >4.3K # Android apps? And a poll: How did you find the report conclusions?
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The author says "Any kind of agentic infrastructure automatically lands an app in this tier as I do not believe it is possible to use AI responsibly from within a coding harness." Which seems like kinda a weird take to me. I can understand a general sentiment of wanting to know how much slop to expect in a project. I can understand a principled…
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This reminds me of another time... Let's travel back to 1980 and interview a local grey beard:Everything these days is shell scripts! They are even selling them like they have the same value as a C program! csh will never be real C. The kids have no idea what a stack is or how to optimize system calls. The performance is awful and they barely…
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I feel this problem grows out of one of the long term limitations of F-Droid: the only metadata the client gives users trying to find apps is how recently the app version was uploaded, and which Free Software "anti-features" the app might contain. In the pre-LLM era this already meant many of the apps which appeared first were people's pet…
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I have been working on a sub 1500 line rust init system for over a week. Hundreds of prompts. All with a local LLM running on my own GPUs because I expect to build with total sovereignty but also zero dependencies, no libc, no alloc, no std, and a test suite that proves the 20 implemented raw syscalls all use the right values by comparing against…
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I guess a different model would to be to try and make a FOSS app store that's more like a Linux distro: app authors don't upload their own apps but instead there's a group of volunteer "app store developers" who do this part. (Don't know if that's been tried before, free idea for anyone who wants to!)
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The AI machine can write better code, it can also write an interpreter which implements function calls by instantiating a new interpreter + entire standard library per function call. Or it will build a 300kloc cathedral of scaffolding and maintain that forever, never writing actual code. Or it will create a CI system that takes 2 hours to run and…
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This can be done in F-Droid even. Just have to create an alternative repository that is maintained this way.
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With the "intelligence" of code focused and capable llm in the last six months, the main problem I'm seeing now is where some total amateur who has no previous knowledge of coding tries to one shot a project. People who have previous experience and know how to architect things (and when to stop an LLM from doing something wrong that will cause…
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F-Droid has always had an app quality problem in general if you ask me. I'm talking broken apps, apps only working on old versions, unmaintained apps, abandon ware, outdated versions up for weeks (that last one is technically due to F-Droid's own build schedule iirc).
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how did critics become suddenly concerned with virtue and beauty with AI? Wouldn't it be better to judge these apps on their utility?The authors are sharing their creativity, and spending time & money to publish apps with a free license.I have disdain for how entitled open source consumers are. Before AI, demanding free accounts, support…
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I agree mostly, but you lose me a bit here: > If the agent is bringing in some quality, rigor, or just action to those things where it wouldn't have existed at all in its absence, I'm not sure I'd object to that. Quality and rigor are not interchangeable with "just bringing some action" which reads as "doing anything is better than nothing." It…
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For me the usefulness of a survey like this has nothing to with how effective LLMs are themselves. It's more that when someone's able to produce an app in an afternoon, and submitting the app to F-Droid becomes a checkbox, how confident can you be that they'll continue maintaining the app? Sure if it's open source you can have your own LLM…
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From my understanding of the text, the underlying thought seems to be that slop comes from laziness, and from that perspective I can see it. If you have an "agentic" setup the output will likely be better, but that also makes it more likely you'll accept it as is, without review, and to lower standards than if you would've written it yourself…
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Every codebase that is being actively worked on (closed/open source) will contain code that's AI generated. With the rising abilities of agents, expectations are sky rocketing in terms of productivity.If you're as productive as an engineer in 2016, you're not at the level that's expected. A 7 day workflow back then should take you maybe a day or…
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I've been a bit disappointed in the f-droid app itself... it seems to almost actively hide things you'd want to know before installing something. I've always made a habit to research apps on their website, which has been a bit more forthcoming with details, before installing.
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It's an emotional problem. I love writing code to solve intricate problems. But knowing that a faster, and maybe better LLM solution is just a prompt away? Somehow that takes the joy out of it. Why spend hours, when you can get an equivalent result in minutes?I will be curious to see how I feel about AdventOfCode this year...
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I'm somewhat surprised about PipePipe. I had a look on the commits of the various components and nothing looks out of place to me. Commits look rather reasonable, comments look useful and don't show obvious LLMisms.What are the AI smells there?It would be nice to expand a bit on the reasoning behind the verdicts.
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If they work, does it matter?Separate from building your own code, ,of course you may have your own standards to apply.But for apps, well, I never had a chance to see how good or bad the code was before AI was about, so why should I care now, so long as what I paid for does what it says it does (and nothing nefarious..)
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My first startup job after college I was astonished to find that one of our most productive engineers was a deaf furry who used Windows Notepad as his dev environment. His code always compiled first time and was nearly always right. It really was something to behold."The way that works for you is the right way."
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Even before AI, I just looked at file size to determine whether an app was worth installing. There used to be tool to search the Google Play Store and sort by size. If it's a basic utility and more than a few MB, it's probably riddled with bloated libraries and ads.
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What stops a bad actor from buying a bunch of these apps on fdroid adding malware to them and then having fdroid handle the distribution for you? I people did something similar with a bunch of plugins in the wordpress plugin archive.
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The don’t tread on me person is fascinating. I wonder if they wrote the software from their phone using github codespaces in browser?
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Many of the projects here predate 2022, so they wouldn't be "ai-generated" in that sense.
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