Commenters split over whether the claim is provable or already obsolete
3 Sep 22 9:28 AM · 1d ago · 11 comments · 1 source · development 3 of 3
Hacker News commenters argued over whether maintainability can be measured at all, whether the essay's predictions are premature given how young agentic coding tools are, and whether resisting AI-written code is now a losing, 'conservative' position.
“We've had strong coding agents for less than a year. Anyone making such a definitive statement about how vibe-coded projects progress over time is basing it on guesswork, not evidence.”
sobioliteAlexandru Nedelcu Software developer, blog authordavedx Hacker News commenterNalNezumi Hacker News commenter
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What people said 24 voices · best of 41 · verbatim
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From what I understand, the things that empirically make code accessible to LLMs are the same things that make it accessible to humans - good documentation, consistent structure and style, robust test suites, use of well-known idioms, and so on. From the theoretical perspective, it also makes sense that many code maintenance benchmarks and…
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I believe many of us here knows that the idea of a simple prompt to make something more than a sketch or a prototype don’t really work.Unless you steer and understand what an LLM will produce, you will end up with something that possible ”works” that has no future plans baked in. Suno generated music has a very unpleasant feeling of sounding like…
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> In the future we will see more and more companies proudly boasting their “NO-AI” policy as a competitive advantage. And they will be right. I appreciate the prediction, but I think it’s definitely wrong, even though I’m not someone who advocates against reading the code. I don’t know how to make it testable, but I’m confident that the use of AI…
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I think (hope?) our industry will reach some equilibrium between fully agentic development and reviewing/hand tuning the code.Personally for my job I struggle to justify writing code by hand. Agents are much better at typing the code, reading the code, finding patterns and discovering bugs. They don't have my knowledge and my background so the…
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There are also objective measures, such as computational complexity of algorithms or lines of code, under which chatbots tend to emit bad code. We have a good explanation for this: chatbot output is definitionally mediocre and the median hunk of wild code has bad computational complexity.
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In the beginning of August 2026, I started a hobby project: building a MongoDB-like database. I have 20 years of industry experience and a master's degree in computer science, so I followed a disciplined, spec-driven development model using Claude, Kiro, Qwen Coder, and Cursor.The first version was built in about two weeks of part time work. Then…
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I think we were telling them that these metrics don't measure the performance of individual developers. I don't know anyone who would disagree that there is an optimal region for verbosity and complexity.
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As far as maintainability is concerned, have we all forgotten the 12 Factor App in the age of AI?https://12factor.net/ https://en.wikipedia.org/wiki/Twelve-Factor_App_methodologyKevin Hoffman expanded on that with the 15-factor app: https://developer.ibm.com/articles/15-factor-applications/Mind you I may be dating myself as I was first introduced…
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So what's your disagreement with the comment you replied to above, then…?
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The problem imo is the slow deterioration of institutional knowledge that offloading the mental task of wisdom gathering to AI is causing.One interesting comparison is to the history of manufacturing. West/America decided one day that manufacturing would be cheaper to outsource and better (short term) profit was to be made by outsourcing it all to…
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Nothing, because this isn’t really how LLMs work anymore. For some time, labs have been using coding tests in simulated environments for reinforcement learning as part of post-training. It would be easy to have the reinforcement learning prioritize shorter outputs. Computational complexity is more involved, but you could measure that and make it…
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Most software is not good, using these rules. And that is written by human developers. The problem is that most software developers have less than 5 years experience. The community doubles every 5 years. Experience is scarce. So AI, learning from all the stuff online, does not learn great code, it learns from available code. You can make it…
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Didn't we spent the last twenty years trying to explain to managers who wanted to quantify performance that these metrics don't matter?
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This analogy really only works assuming that maintaining [insert company]'s institutional expertise requires N engineers to maintain individual lines of code manually.This is already showing not to be true with AI. Institutional knowledge is not the same as knowing how to implement low-level software details. Even today, every company does not…
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I'm extremely bullish about AI-assisted development in general, so take that as a grain of salt. I do agree with the foundational premise that AI is not very good at writing _human_-maintainable code. I put _human_ in italics because the author does not state this but it is heavily implied that is what they mean. But writing code that both AI and…
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Maybe I've just given up, or maybe I'm a realist? But I fully believe AI will just...catch up with everything?There's so much money in it right now. There's such a momentum. There are zero incentives to slow down for those that are in charge.I've accepted that in 5-10 years, the vast majority of human devs. and engineers will not touch a single…
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I find the basic argument slippery because it's generic: we all agree that there's an optimum between quality and verbosity. But that's like saying we like _beautiful things_. Where is this optimal range in the spectrum? Does it overlap for the vast majority of programmers? I doubt it. ps. There's a quote to which I was alluding to in my previous…
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> I feel like you could take all the handwavy comment that are made today to dismiss this caution, and find equal dismissal back then when companies were actively outsourcing the manufacturing.Absolutely people were extremely dismissive to anyone saying that we're losing the ability to make things in this country!There were all these theories like…
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https://discourse.haskell.org/t/how-to-keep-enjoying-programming-in-a-world-of-llms/14705 was an interesting post on trying to get the good parts of llm assisted coding without losing that wisdom. Seems like it requires discipline though (so hopefully the slot machine theory of llms is wrong)
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I've read a lot of posts similar to this recently and keep asking myself if the past 20 years of my professional experience was that atypical.I’m sure there are companies who are writing “perfectly maintainable and highly scalable code”. However, for half of my career I’ve been brought into startups to clean up the mess created by engineering…
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Hm. True that, if these metrics are outside the bell curve, they **do** matter. I agree. My initial statement is wrong, in absolute terms.
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Was expecting to read something along the lines of:"Knowing what you don't know is the beginning of wisdom", and a new take on AI reasoning, but didn't actually use the word wisdom in the text.Anyway, I think we're increasingly finding the old adage "garbage-in, garbage-out" still applies.The question I would ask is: Does anyone first ask the AI…
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We tried to explain that simpler is better, since it saves on CPU time and RAM; and shorter is better, since it is easier to maintain and definitionally accrues less technical debt. Managers have not stopped operating feature factories, though; as long as they don't have to understand computational complexity, they will merely complain that their…
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>People are actually terrible at making predictions. I believe the future will surprise all of us. But, I’m going to make a prediction of my own…>In the future we will see more and more companies proudly boasting their “NO-AI” policy as a competitive advantage. And they will be right.I will very happily take the other side of this bet. Maybe if…
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