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  RGS1811
  I've been vibecoding a ton for the past 9 months, built a bunch of cool little apps for myself with AI, ran experiments, built an entire SDLC on skills, did the agent orchestration harness thing, etc. In the past few weeks I've hit a wall where I'm just tired of it. Each model becomes more independent but also harder to direct in detail. They produce massive, tedious, sloppy text outputs with very little input. They're bad at socializing knowledge and communicating design forks.The places where I've seen unequivocal wins with AI are repetitive tech debt tasks that apply the same transformation across a large amount of code or refactor under a pre-existing test suite with good coverage. It's great for initial research, brainstorming, and can be good (despite the sycophancy) as a rubber duck conversation partner. I use AI constantly, for work and in my personal time, but we've hit a ceiling where I no longer find it helpful for the models to absorb more of the intellectual labor. They get things wrong more aggressively, and more elaborately. They're inadequately curious. I cannot keep up with the endless bad technical writing, and it makes it harder to spot factual errors and bad reasoning.Here's what I want: I want AI as an assistant that helps me make decisions, and ensures that I'm in the driver's seat. AI as an over-confident prodigy on speed is what we're getting lately, and it's losing me.
• hahahaa
  You develop a taste as to what details you can skim and what you need to dive on. We are all trained on this due to doing 10000 wax on wax off movements, called a "PR Review". I used to scrutinize. Now I think "yep that bit looks good and tests will catch errors plus I can manually test. This bit over here looks scary will spend time more deeply understanding".With AI you don't need to understand every line in depth but it does need good judgement to decide which.
• johnfn
  But surely at some point you need to stop, right? Most web developers are perfectly capable without understanding the intricacies of the file system or OS, even though the browser sits on top them. Most engineers don’t know assembly, or transistors or electrical engineering. Steve Jobs didn’t know every line of Objective-C that went into OSX. I don’t think Michelangelo collected all his paint materials by hand when painting the Sistine Chapel. In some sense I don’t understand a lot of the panic around AI when the entire career progression of what it means to be a software engineer has simply been to deal with ever-increasing levels of abstraction.
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  canthonytucci
  All details are not created equal.Some details are boring.My AI dream (that I’m living happily) is getting to focus on the details that I find interesting and ignoring all the boilerplate details that modern software requires.
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  oh_my_goodness
  Yeah, I think the peak expectation for AI is that the user gets to be the manager of a very smart team. But we've all seen that. If the manager is clueless about the technology, the results are disappointing.
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  lifeisstillgood
  It reminds me of “magic”. I say “expelliamus” and the wand flies out the other guys hand, not his hat, or wallet or the person behind’s sandwiches.The details always matter. There is a (fairly) good book series where it turns out we are living in the matrix and someone finds a config file and effectively becomes a Wizard, and of course problems ensue with details (like flying by adjusting one’s position one feet up every second is just vibrating a lot)I think ultimately AI is “do what I mean” and the only reason it looks like it’s working is because AI has read all the same books as us
• hangrybear666
  To make a meathead analogy: you all know the people in the gym who apply the strategy of least resistance by taking shortcuts, skipping the hard parts or following some hype new training regimen while forgetting about the fundamentals. None of those people look like they lift and a lot of them remain in the same shape their entire life.Same with AI. if you use it to skip all the hard parts you will not grow and mature and waste your potential.
• chungusamongus
  Yes, it is. Working on a sega genesis homebrew game. I focus on visuals, dialogue, narrative logic, music, etc., and GPT worries about the rest. It works for me. I couldn't care less if works for others. I'm working on the part I enjoy.
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  iepathos
  This post ignores that verifying something works doesn't require you to fully understand it. This is easily observable in products we use everyday. We don't need to understand them to be able to verify they work correctly. The cost of verification is often cheaper than the cost of production.It present delegation as absence of power/agency. While I think there is some kernel of truth in here, the claim "it's not empowering to hand off the details" quickly falls apart when we consider real examples. If it were true, it would mean any leader who coordinates an organization isn't empowered through delegation. We know that's false. The general claim doesn't hold at all. Somewhere in there is an argument for engineers losing something in the hand off, but it isn't clearly articulated.
• brid
  Anyone that sells you on empowering anything is preying on your pride. Don't be a sucker.
• luciana1u
  we optimized the part of programming that was fun and made the part that was hard even harder. writing code was never the bottleneck. understanding it was.
• arbirk
  It is all about abstraction, and basic English is a quite bad abstraction
• anditherobot
  AI can generate what a company makes. Can it generate what a company is?Producing artifacts: media, code, documents, the visible output has clearly gotten easier. But the other things, like knowing what's worth building in the first place and making the right judgment call, still seem to be left to the humans.
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  bitwize
  We're living in the glorious future where software engineers don't have to worry about nitty-gritty stuff like actually making software and can focus on the really important work: administrative and managerial tasks!
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  metalcrow
  > to become good at the thing in the first place requires a complete reversal of the mindset that would lead one to having wanted to hand it offIs this true? I can be good at something and be happy to not have to do it anymore I feel
• naushniki
  Is it true that you are only as good a programmer with AI as you are without?
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  jclardy
  This is what a lot of people miss. People think, "Oh we won't need software soon, AI can just build interfaces when we need them" but in reality, the software was built to solve a problem, usually by people invested in solving that problem. Saying "Build me a todo app" will give you the sum of averages, a completely average todo app that works fine, but it isn't great in any measure.The details are what separates the slop from the craft.
• dnnehgf
  it depends on what you mean by power and details and handing off and whom you are handing them to and what you are getting handed in return and your counterparty's relationship to these things and the extent to which you measure things in the same way as one another.
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  sharts
  Why people continue to treat AI as though it’s not just an intern or recent grad? That alone will solve 90% of problems people have.
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  cheevly
  Every word of this seems objectively false. AI is more than capable of handling the details. I have generated countless tools for myself without needing to know or care about the details.
• blitzar
  CEOs, serial entrepreneurs, managers etc all seem to find it pretty empowering.I treat my Ais like employees, pizza party and all.
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  iamleppert
  This same argument could be applied to anything. Layers of abstraction exist for a reason, because at a certain point, we can only deal with so many things at once. We have to be able to delegate "the details" to others -- be that a person, a company, or an AI model.Does "not getting into the details" mean you have to understand how the GCC compiler works when you write C code? Do you need to be an expert in machine code, or how SSE and pipelined instruction caches work to write your little bit of code? Do you need to understand how Ethernet frames work to write an API route for a web server?Knowing how these things work can be helpful in a broader sense, and perhaps when encountering weird edge cases or dealing with exotic implementation but are generally not required to get the job done. The details, simply put, don't matter because someone else has already thought through the problem and solved it in a way that is good enough for the vast majority of use cases.The same goes with AI. It's helpful to know how things work, but as the models continue to get better and better, it doesn't matter. As long as they are trained properly by someone who does know the details, that's a far better place to be than training a million different people on it who will each have their own biases, levels of understanding and misconceptions.
• varispeed
  The biggest pet peeve is that you never know whether your request is dealt with by Opus and not Sonnet or Haiku or even something else and you still pay for Opus. You have to ask the model some difficult question and gauge which one is doing the work, but often they switch halfway the task when it goes downhill (they might say it is because of context window) but still charge you full price and you have to start the session again (them making even more money). This should be more regulated and externally audited, what exactly you are paying for.
• anon
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• customguy
  > I think behind a lot of the enthusiasm around AI is a dream of being able to manifest things into reality without having to get into the details.Ironically, that I don't have to skip the details is the one thing I like. Mind you, what I use LLM for is toy stuff compared to what people who use them at their jobs for big projects.But FWIW, I wrote this comment recently: https://news.ycombinator.com/item?id=49049006 And then I figured I should actually do that, I wanna see what it looks like. So I described it to the best of my abilities, and was polite about it: https://pastebin.com/sAbPzi05 Claude did not ask for clarification, it just knocked it out of the park, free tier, Sonnet, medium effort. https://i.imgur.com/YPwr6aT.png The only changes I made since then are not worth talking about.Today I made another little tool, one I'll actually use but that is too specific and boring to explain, and because of that previous experience I spent nearly an hour writing that prompt, rereading it, making sure to use the same terms for the same concepts everywhere, moving things around so what logically belongs together actually is together, instead of a stream of consciousness, and the result is exactly what I had in mind. It was like imagining something and then seeing that exact thing, except the colour scheme had a nice topical little quirk even.The plan now is to keep chatting about the result as I make experiences with it in practice, make notes for version 2.0, and then update and extend that first prompt and use it in a fresh context. And that is very fun, actually, and it's still a puzzle. What do I even want, exactly, and how do I describe it? That's not trivial, and there is hardly a "skill ceiling" here, though of course there are diminishing returns. I also assume that if I put some vague amount "less effort" into it, the result would be the same, but I don't care, because I enjoy using this brain muscle.And directing the effort towards just a prompt, not a whole "system" around it pleases me too, since I generally don't like vendor lock-in, and prefer things to just be a "a bunch of files" that run almost anywhere. A clear English description is as close as it gets to that, and I don't mind that I roll the dice with every LLM I give a specific prompt to, since at least it doesn't mutate the prompt.I hate the formatting of the the LLM code of course, I wouldn't have named many variables that way, so I still look forward to and love making things where I put every character myself. But since I code voluntarily I see it as two separate activities that don't really encroach upon each other unless I make them.