12 ms·

It's not empowering to hand off the details

225 points by davnicwil 2mo ago

canthonytucci 2mo ago
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.
- breezybottom 2mo ago
  So what? Jobs aren't supposed to be fun. Lots of people depend on those boring details.
  - exe34 2mo ago
    Some of us just wouldn't work if it wasn't fun. I'd let myself starve in the streets. (I have some experience with starvation from an eating disorder phase in my twenties, it's only unbearable if you have to work).
    - breezybottom 2mo ago
      Easy to say when you're not at risk of starving.
      - exe34 2mo ago
        I like how you ignored the second part of my post. I specifically included it because I knew someone would respond like this to the first part. I think it's actually feasible when you have no other options - it's my retirement plan anyway.
  - canthonytucci 2mo ago
    I hope we can save “jobs aren’t supposed to be fun” for stuff like undertaker and grief counselor. My feeling is making things should be mentally stimulating, and as many tedious parts that can be automated should be, so we can spend precious human thought on thinking instead of recitation. I don’t know what you mean by the last part. Do you mean programmers depend on busy work to eat or the users depend on the human touch on the boring details?
    - bluefirebrand 2mo ago
      For me there is nothing less fun than using AI to generate code Then I have to do the boring bullshit work of reviewing it and making sure it's correct? Fuck that Writing code is way more fun than reviewing other people's code
  - xboxnolifes 2mo ago
    Saying jobs aren't supposed to be fun is akin to saying life should be dreadful. Work tends to be around half of your waking hours, usually your best and least tired half too. If anything we should be striving to make all kinds of work more enjoyable.
- bogometer 2mo ago
  You said what I was thinking. AI can do the things I always found mind numbing and tedious, but because I did it already early in my career, I know when to intervene because the agent is not doing it correctly. I think that is the OP's point.
  - xtajv 2mo ago
    I think about LLMs in software today as attempting to provide a similar role as compilers in terms of translating high-level thoughts into low-level details. The only problem is that I actually trust compilers.
    - smitty1e 2mo ago
      How quickly would you drop a non-deterministic compiler for the source code of a project?
    - witx 2mo ago
      I detest this compiler analogy so much: llms are non deterministic by nature, compilers should not and are not
      - xtajv 1mo ago
        I'm not saying that LLMs are like compilers. I'm saying that LLMs are like really bad compilers hehe.
- inigyou 2mo ago
  Boilerplate details mean we've failed as an industry. Why haven't we already got the computer to automate all the boring bits without AI?
  - risaacs99 2mo ago
    why can't AI be that solution?
    - inigyou 2mo ago
      why use a nuclear bomb to drive a nail?
      - sigbottle 2mo ago
        To further onto this, humans could technically simulate Turing machines themselves but they don't. Efficiency and finding the right abstractions and tradeoffs is literally identical with making new capacities and capabilities. If all of your systems were truly "run by AI", we wouldn't have systems. Systems are systems because the AI uses well developed tools and protocols that humans have put together. It's a stable capacity.
  - IsTom 2mo ago
    I feel that this is because people have been reinventing the wheel a lot in IT. A lot of innovation that finally lands in programming languages has been done decades earlier, but now it's mostly awkwardly bolted on existing languages and frameworks.
  - trescenzi 2mo ago
    I really enjoy working with Gleam which is a rather boilerplate heavy language. However most of the work is managed by a really well built LSP. If you're writing a strongly type language it's easy to programmatically manage all of the boilerplate. You could you an LLM but why bother when it's a so formulaic.
    - 2mo ago
cheevly 2mo ago
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.
- RealityVoid 2mo ago
  Tools? Yes. Reliable foundations? Eh, mostly not. Maybe I'm holding it wrong, but I'm not impressed. Not in the least because in order to get a good system you must have a good image of the system in your head. And if AI builds the system, how will you ever get that system in your head?
  - bonoboTP 2mo ago
    How would you do it if you hired an employee in your company to do it? You'd talk to the employee and read the docs they write. Same here.
    - RealityVoid 2mo ago
      When an employee writes a system, the employee owns the system. When an AI writes a system for you, YOU own the system.
      - bonoboTP 2mo ago
        Owns? What a strange word to use. I doubt they own it in the sense that the profits of it go to their bank account. Use a better word and things will be clearer.
        RealityVoid 2mo ago
        Yes, owns. Ownership as in accountability, stewardship and care. But I think you already got this from my post and if we're fighting about semantics, there's no constructive discussion to be had.
deleted 2mo ago
[deleted]
metalcrow 2mo ago
> 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 off Is this true? I can be good at something and be happy to not have to do it anymore I feel
- zelphirkalt 2mo ago
  Though not the other way around. You don't become good at something by handing it off. In that case you either are already good, or never become good.
- wcfrobert 2mo ago
  My opinion is that juniors need time in the saddle to develop good engineering judgement and taste. Outsourcing critical thinking is seductive and a slippery slope. LLM lures juniors into feeling productive, and molds them into ineffectual middle managers to be readily replaced when there's a bad quarter.
  - witx 2mo ago
    Yes exactly. The mids of my previous team where submitting PRs that at first glance looked good, well documented and with a very clean and professional English. As you started pulling the threads it was, usually, a mess of subtle bugs and over abstraction. But to them it was great, as it was llm generated and they (the mid devs) had no better judgement.
dnnehgf 2mo ago
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.
hahahaa 2mo ago
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.
- theshrike79 2mo ago
  "Code Smell" is the term I use here. With enough experience you can just glance at a diff and see if it "smells". If it does, you drill down and see if you were right. If not, you trust the process and approve. (And I'm talking about basic run of the mill code here, if you're doing something that kills people, don't go by feels)
blitzar 2mo ago
CEOs, serial entrepreneurs, managers etc all seem to find it pretty empowering. I treat my Ais like employees, pizza party and all.
bitwize 2mo ago
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!
- bonoboTP 2mo ago
  AI can do administrative tasks.
RGS1811 2mo ago
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.
- jv22222 2mo ago
  Agree. Creating products with AI is like creating a tightly packed ball of wool. Then, to try to understand what happened you have to somehow pick a strand and pull it out to have a look. Very difficult with tightly packed wool. I've run some experiments in the past month that get me closer to being able to work with this opaque bundle. It's the main thing I think about every day, how to solve this problem.
- lelanthran 2mo ago
  > 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. You aren't going to get that. Why would they even offer you that? You're going to be the meatbag peripheral to an AI.
  - Groxx 2mo ago
    Plus it would reduce token counts. Careful use is almost directly opposed to their financial goals.
arbirk 2mo ago
It is all about abstraction, and basic English is a quite bad abstraction
iamleppert 2mo ago
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.
- chris_armstrong 2mo ago
  I didn't interpret it as an argument about layers of abstraction. You need to be in the detail at the level you're writing (and it's certainly advantageous to know some of the detail of the abstractions below) because you're building abstractions on top of that, because the details subtly change at the base level you're building at, impacting the level that you're building to.
- wavemode 2mo ago
  You're confusing translation and interpretation. A compiler is merely translating your code into a lower-level form. (There is a degree of heuristic-based interpretation that goes into generating good code, but the code's observable behavior is not allowed to change.) But an LLM has to interpret your words and make judgment calls about the logical details, which is a very different thing. An LLM sufficiently intelligent to make acceptable judgment calls in all situations (acceptable enough to ship to production without human review of those details) would likely be indistinguishable from AGI.
oh_my_goodness 2mo ago
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.
- witx 2mo ago
  And the team (AI) is really not that smart. Just very fast at pasting and gobling stack overflow and github repos together
brid 2mo ago
Anyone that sells you on empowering anything is preying on your pride. Don't be a sucker.
jclardy 2mo ago
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.
- tpmoney 2mo ago
  I agree with your first part, that software is built to solve a problem. But I think you sort of sidestep what makes AI exciting to non-software people with your second part. The people who are excited about this aren't excited because they can ask for a todo app but because they can solve the problem the todo app was supposed to be soling for them without needing to find and learn a todo app. AI is the new "excel spreadsheet with ridiculous formulas on top of VB script on top of pivot tables" for the non-programmers. Yes, the AI might not do it efficiently or even always give the right answers, but the spreadsheets didn't either. For non-programmers, the computer has always been a black box, data goes in, data comes out. Usually it's right, sometimes it's wrong and the users mostly had no idea why or how. But now they don't need the middleware app. They don't need to take their data and split it up into very specially structured files, and put just the right pieces of information on just the right lines and in the right spaces. They don't need to remember to do "(foo and (bar or baz))" to get the right answer, as opposed to "(foo and bar or baz)" and get the wrong one. AI for non-programmers is the closest we've ever come to "natural language programming" for people to use. It doesn't matter that it gets things wrong sometimes, or does it inefficiently or makes something unmaintainable unless you use the AI again. What matters to them is they can say "take all this data here and swizzle the frobs" in their native language instead of learning a specific programming syntax and system. And they can point it at some arbitrary data in whatever format they happen to have the data in, and they have a halfway decent chance of getting something that does what they want. It's not going to be pretty, it's not going to be perfect and it's probably going to break in subtle and unexpected ways. But as long as most of the time its mostly good enough, people will still use it enthusiastically. We're effectively looking at "worse is better" for the modern age and for people that aren't and never were going to be programmers.
chungusamongus 2mo ago
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.
hangrybear666 2mo ago
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.
lifeisstillgood 2mo ago
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
- lelanthran 2mo ago
  > 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) This is very interesting. Which book series is this?
  - 16bitvoid 2mo ago
    Sounds like "Off to be the Wizard". The series is called "Magic 2.0"
  - Egrodo 2mo ago
    Found it (with the help of AI, naturally). Looks like "Wizard 2.0" by Scott Meyer. https://www.goodreads.com/book/show/18616975-off-to-be-the-wizard https://www.goodreads.com/book/show/18616975-off-to-be-the-w...
  - novaleaf 2mo ago
    as others mentioned, it sounds like "Off to Be the Wizard". Unfortunately I wouldn't call it a great series. It starts off strong but drags. IIRC I got through half of the second book before stopping.
anditherobot 2mo ago
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.
- mrbnprck 2mo ago
  There already are use-cases for automatic software deployment where monitoring is ingested back to the AI, which then judges to rollback/fix a feature if certain metrics spike/user complaints arive. If you had the data basis (user reports, trends, ...) you could let the AI decide upon that what to build.
sharts 2mo ago
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.
- bigstrat2003 2mo ago
  For one thing, it's not actually that useful to have such a person at your fingertips. You put up with the drain a junior places upon you because with training, he'll be able to come into his own and pay off the time invested. An LLM can't do that. Also, a lot of people incorrectly believe that an LLM is smarter than a new grad, and of course the companies making them have a vested financial interest in lying to you that their products are smarter than they are.
naushniki 2mo ago
Is it true that you are only as good a programmer with AI as you are without?
varispeed 2mo ago
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.
iepathos 2mo ago
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.
- Barrin92 2mo ago
  >We don't need to understand them to be able to verify they work correctly I don't think that's the case and it's becoming more obvious every day. From people who cannot distinguish truth or fiction on online platforms, good code from bad, to insecure software that causes supply chain attacks, to investment vehicles or fake medicine peddled that does not work, the idiotic MBA manager who does not understand the workers they manage and so on. That is why we're living on BS metrics and crappy reviews, because to the people who manage organizations their own workplace is a Blackbox. The critique that "AI" systems are semantically blind token processors is correct, it's just not bothering anyone because it already applied to most modern companies. When people become passive consumers rather than broadly competent users how something works cannot be evaluated so by definition all they have to go off is appearance, which is why we live in the age of influencers and marketing, because that is now the only factor that actually matters.
  - iepathos 2mo ago
    If I commission a part specified as 10.00 ± 0.01 mm, I can verify it with a calibrated micrometer without understanding the CNC machine, its software, or how to manufacture the part. Likewise, a function with a finite input space can be exhaustively tested against its specification without understanding its implementation. In these cases, I need to understand the requirement and the test, not the production details, which can actually be a black box. Your examples show that verification is sometimes inadequate, not that it requires full productive competence. The conclusion doesn't generalize.
luciana1u 2mo ago
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customguy 2mo ago
> 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 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 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 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.
johnfn 2mo ago
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.
- skydhash 2mo ago
  The issue is reliability. I don't need to know the implementation of the database or the lower levels of the network tasks because I trust that they works well. A bug that affects me has a very low chance of occurring and the main risk is me not reading or understanding the docs. With AI generated systems, no one knows what's going on. Not even the AI. When an issue pops up (which has a very good chance to happen because of the complexity of integrations), debugging it can be like reverse engineering obfuscated assembly code.
- KronisLV 2mo ago
  > Most web developers are perfectly capable without understanding the intricacies of the file system or OS, even though the browser sits on top them. This will mess you up if you ever need to store a significant amount of files on the file system directly, or even deal with resource usage for batch processes, or have to dig into non-trivial transaction handling when dealing with DBs without having learnt enough about them, or even the whole domain of SQL and query optimization that ORMs will not protect you from and so many other things. I don't think you need to know everything, but you definitely need to learn. > But surely at some point you need to stop, right? I guess, but typically due to your own lack of curiosity or mental exhaustion, or even limited time to spend on something, rather than the new knowledge and skills not being good to have. At least knowing when AI is heading in the wrong direction for any given domain will save your bacon.
charbz 2mo ago
https://www.charbzg.com/blog/ai-empowerment https://www.charbzg.com/blog/ai-empowerment
- froh 2mo ago
  > It is empowering to hand off execution July 26, 2026 > I read David Nicholas Williams's short blog post titled It's not empowering to hand off the details, in which he argues that AI cannot replace expertise because doing good work requires deep familiarity with the details. > I couldn't agree more! > He articulates very well the puzzling phenomenon I see every day with "AI-pilled" colleagues (including many engineers) who trust the model with far more than they should. They delegate the thinking and designing along with the execution, lose touch with the codebase, miss out on critical learnings, and then complain when the slop they produced doesn't solve the original problem. > But I think the argument is incomplete without a counterexample. There is one phase where handing off work to AI is genuinely empowering, and that is worth defining and formalizing.
luciana1u 2mo ago
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feiz45607 2mo ago
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jreynar 2mo ago
Completely agree. The worst sort of manager is the one who wants to stay "high level" and proposes things that either aren't possible or are vastly harder than their idea to "just do X" suggests. And the root cause is them not knowing the details. What gets me excited about AI is that you can hand off some of the detailed work, specifically the repetitive sort. As a sales person, you ought to know how to create a quote for a customer. But creating the 50th one for the same product for the same number of seats becomes drudgery. As a software engineer, you should know how to fix (or at least you should have back in the day) a buffer overrun, but it gets tedious to fix hundreds of them (and I know since I was at Microsoft when we paused Office development to do just that, for months). I bet there's an example for every role. And the benefit of having an AI handle those details -- not the first time, but once you're a master and the AI has become trusted -- is that you can focus on things that require a human being's attention. More creative, more collaborative tasks. Conveniently those tend to be more rewarding than fixing another teensy bug or writing another formulaic email.

225 points by davnicwil 2mo ago

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.

breezybottom 2mo ago
So what? Jobs aren't supposed to be fun. Lots of people depend on those boring details.
- exe34 2mo ago
  Some of us just wouldn't work if it wasn't fun. I'd let myself starve in the streets. (I have some experience with starvation from an eating disorder phase in my twenties, it's only unbearable if you have to work).
  - breezybottom 2mo ago
    Easy to say when you're not at risk of starving.
    - exe34 2mo ago
      I like how you ignored the second part of my post. I specifically included it because I knew someone would respond like this to the first part. I think it's actually feasible when you have no other options - it's my retirement plan anyway.
- canthonytucci 2mo ago
  I hope we can save “jobs aren’t supposed to be fun” for stuff like undertaker and grief counselor. My feeling is making things should be mentally stimulating, and as many tedious parts that can be automated should be, so we can spend precious human thought on thinking instead of recitation. I don’t know what you mean by the last part. Do you mean programmers depend on busy work to eat or the users depend on the human touch on the boring details?
  - bluefirebrand 2mo ago
    For me there is nothing less fun than using AI to generate code Then I have to do the boring bullshit work of reviewing it and making sure it's correct? Fuck that Writing code is way more fun than reviewing other people's code
- xboxnolifes 2mo ago
  Saying jobs aren't supposed to be fun is akin to saying life should be dreadful. Work tends to be around half of your waking hours, usually your best and least tired half too. If anything we should be striving to make all kinds of work more enjoyable.
bogometer 2mo ago
You said what I was thinking. AI can do the things I always found mind numbing and tedious, but because I did it already early in my career, I know when to intervene because the agent is not doing it correctly. I think that is the OP's point.
- xtajv 2mo ago
  I think about LLMs in software today as attempting to provide a similar role as compilers in terms of translating high-level thoughts into low-level details. The only problem is that I actually trust compilers.
  - smitty1e 2mo ago
    How quickly would you drop a non-deterministic compiler for the source code of a project?
  - witx 2mo ago
    I detest this compiler analogy so much: llms are non deterministic by nature, compilers should not and are not
    - xtajv 1mo ago
      I'm not saying that LLMs are like compilers. I'm saying that LLMs are like really bad compilers hehe.
inigyou 2mo ago
Boilerplate details mean we've failed as an industry. Why haven't we already got the computer to automate all the boring bits without AI?
- risaacs99 2mo ago
  why can't AI be that solution?
  - inigyou 2mo ago
    why use a nuclear bomb to drive a nail?
    - sigbottle 2mo ago
      To further onto this, humans could technically simulate Turing machines themselves but they don't. Efficiency and finding the right abstractions and tradeoffs is literally identical with making new capacities and capabilities. If all of your systems were truly "run by AI", we wouldn't have systems. Systems are systems because the AI uses well developed tools and protocols that humans have put together. It's a stable capacity.
- IsTom 2mo ago
  I feel that this is because people have been reinventing the wheel a lot in IT. A lot of innovation that finally lands in programming languages has been done decades earlier, but now it's mostly awkwardly bolted on existing languages and frameworks.
- trescenzi 2mo ago
  I really enjoy working with Gleam which is a rather boilerplate heavy language. However most of the work is managed by a really well built LSP. If you're writing a strongly type language it's easy to programmatically manage all of the boilerplate. You could you an LLM but why bother when it's a so formulaic.
  - 2mo ago

cheevly 2mo ago

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.

RealityVoid 2mo ago
Tools? Yes. Reliable foundations? Eh, mostly not. Maybe I'm holding it wrong, but I'm not impressed. Not in the least because in order to get a good system you must have a good image of the system in your head. And if AI builds the system, how will you ever get that system in your head?
- bonoboTP 2mo ago
  How would you do it if you hired an employee in your company to do it? You'd talk to the employee and read the docs they write. Same here.
  - RealityVoid 2mo ago
    When an employee writes a system, the employee owns the system. When an AI writes a system for you, YOU own the system.
    - bonoboTP 2mo ago
      Owns? What a strange word to use. I doubt they own it in the sense that the profits of it go to their bank account. Use a better word and things will be clearer.
      - RealityVoid 2mo ago
        Yes, owns. Ownership as in accountability, stewardship and care. But I think you already got this from my post and if we're fighting about semantics, there's no constructive discussion to be had.

deleted 2mo ago

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metalcrow 2mo ago

> 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 off Is this true? I can be good at something and be happy to not have to do it anymore I feel

zelphirkalt 2mo ago
Though not the other way around. You don't become good at something by handing it off. In that case you either are already good, or never become good.
wcfrobert 2mo ago
My opinion is that juniors need time in the saddle to develop good engineering judgement and taste. Outsourcing critical thinking is seductive and a slippery slope. LLM lures juniors into feeling productive, and molds them into ineffectual middle managers to be readily replaced when there's a bad quarter.
- witx 2mo ago
  Yes exactly. The mids of my previous team where submitting PRs that at first glance looked good, well documented and with a very clean and professional English. As you started pulling the threads it was, usually, a mess of subtle bugs and over abstraction. But to them it was great, as it was llm generated and they (the mid devs) had no better judgement.

dnnehgf 2mo ago

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.

hahahaa 2mo ago

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.

theshrike79 2mo ago
"Code Smell" is the term I use here. With enough experience you can just glance at a diff and see if it "smells". If it does, you drill down and see if you were right. If not, you trust the process and approve. (And I'm talking about basic run of the mill code here, if you're doing something that kills people, don't go by feels)

blitzar 2mo ago

CEOs, serial entrepreneurs, managers etc all seem to find it pretty empowering. I treat my Ais like employees, pizza party and all.

bitwize 2mo ago

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!

bonoboTP 2mo ago
AI can do administrative tasks.

RGS1811 2mo ago

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.

jv22222 2mo ago
Agree. Creating products with AI is like creating a tightly packed ball of wool. Then, to try to understand what happened you have to somehow pick a strand and pull it out to have a look. Very difficult with tightly packed wool. I've run some experiments in the past month that get me closer to being able to work with this opaque bundle. It's the main thing I think about every day, how to solve this problem.
lelanthran 2mo ago
> 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. You aren't going to get that. Why would they even offer you that? You're going to be the meatbag peripheral to an AI.
- Groxx 2mo ago
  Plus it would reduce token counts. Careful use is almost directly opposed to their financial goals.

arbirk 2mo ago

It is all about abstraction, and basic English is a quite bad abstraction

iamleppert 2mo ago

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.

chris_armstrong 2mo ago
I didn't interpret it as an argument about layers of abstraction. You need to be in the detail at the level you're writing (and it's certainly advantageous to know some of the detail of the abstractions below) because you're building abstractions on top of that, because the details subtly change at the base level you're building at, impacting the level that you're building to.
wavemode 2mo ago
You're confusing translation and interpretation. A compiler is merely translating your code into a lower-level form. (There is a degree of heuristic-based interpretation that goes into generating good code, but the code's observable behavior is not allowed to change.) But an LLM has to interpret your words and make judgment calls about the logical details, which is a very different thing. An LLM sufficiently intelligent to make acceptable judgment calls in all situations (acceptable enough to ship to production without human review of those details) would likely be indistinguishable from AGI.

oh_my_goodness 2mo ago

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.

witx 2mo ago
And the team (AI) is really not that smart. Just very fast at pasting and gobling stack overflow and github repos together

brid 2mo ago

Anyone that sells you on empowering anything is preying on your pride. Don't be a sucker.

jclardy 2mo ago

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.

tpmoney 2mo ago
I agree with your first part, that software is built to solve a problem. But I think you sort of sidestep what makes AI exciting to non-software people with your second part. The people who are excited about this aren't excited because they can ask for a todo app but because they can solve the problem the todo app was supposed to be soling for them without needing to find and learn a todo app. AI is the new "excel spreadsheet with ridiculous formulas on top of VB script on top of pivot tables" for the non-programmers. Yes, the AI might not do it efficiently or even always give the right answers, but the spreadsheets didn't either. For non-programmers, the computer has always been a black box, data goes in, data comes out. Usually it's right, sometimes it's wrong and the users mostly had no idea why or how. But now they don't need the middleware app. They don't need to take their data and split it up into very specially structured files, and put just the right pieces of information on just the right lines and in the right spaces. They don't need to remember to do "(foo and (bar or baz))" to get the right answer, as opposed to "(foo and bar or baz)" and get the wrong one. AI for non-programmers is the closest we've ever come to "natural language programming" for people to use. It doesn't matter that it gets things wrong sometimes, or does it inefficiently or makes something unmaintainable unless you use the AI again. What matters to them is they can say "take all this data here and swizzle the frobs" in their native language instead of learning a specific programming syntax and system. And they can point it at some arbitrary data in whatever format they happen to have the data in, and they have a halfway decent chance of getting something that does what they want. It's not going to be pretty, it's not going to be perfect and it's probably going to break in subtle and unexpected ways. But as long as most of the time its mostly good enough, people will still use it enthusiastically. We're effectively looking at "worse is better" for the modern age and for people that aren't and never were going to be programmers.

chungusamongus 2mo ago

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.

hangrybear666 2mo ago

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.

lifeisstillgood 2mo ago

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

lelanthran 2mo ago
> 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) This is very interesting. Which book series is this?
- 16bitvoid 2mo ago
  Sounds like "Off to be the Wizard". The series is called "Magic 2.0"
- Egrodo 2mo ago
  Found it (with the help of AI, naturally). Looks like "Wizard 2.0" by Scott Meyer. https://www.goodreads.com/book/show/18616975-off-to-be-the-wizard https://www.goodreads.com/book/show/18616975-off-to-be-the-w...
- novaleaf 2mo ago
  as others mentioned, it sounds like "Off to Be the Wizard". Unfortunately I wouldn't call it a great series. It starts off strong but drags. IIRC I got through half of the second book before stopping.

anditherobot 2mo ago

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.

mrbnprck 2mo ago
There already are use-cases for automatic software deployment where monitoring is ingested back to the AI, which then judges to rollback/fix a feature if certain metrics spike/user complaints arive. If you had the data basis (user reports, trends, ...) you could let the AI decide upon that what to build.

sharts 2mo ago

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.

bigstrat2003 2mo ago
For one thing, it's not actually that useful to have such a person at your fingertips. You put up with the drain a junior places upon you because with training, he'll be able to come into his own and pay off the time invested. An LLM can't do that. Also, a lot of people incorrectly believe that an LLM is smarter than a new grad, and of course the companies making them have a vested financial interest in lying to you that their products are smarter than they are.

naushniki 2mo ago

Is it true that you are only as good a programmer with AI as you are without?

varispeed 2mo ago

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.

iepathos 2mo ago

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.

Barrin92 2mo ago
>We don't need to understand them to be able to verify they work correctly I don't think that's the case and it's becoming more obvious every day. From people who cannot distinguish truth or fiction on online platforms, good code from bad, to insecure software that causes supply chain attacks, to investment vehicles or fake medicine peddled that does not work, the idiotic MBA manager who does not understand the workers they manage and so on. That is why we're living on BS metrics and crappy reviews, because to the people who manage organizations their own workplace is a Blackbox. The critique that "AI" systems are semantically blind token processors is correct, it's just not bothering anyone because it already applied to most modern companies. When people become passive consumers rather than broadly competent users how something works cannot be evaluated so by definition all they have to go off is appearance, which is why we live in the age of influencers and marketing, because that is now the only factor that actually matters.
- iepathos 2mo ago
  If I commission a part specified as 10.00 ± 0.01 mm, I can verify it with a calibrated micrometer without understanding the CNC machine, its software, or how to manufacture the part. Likewise, a function with a finite input space can be exhaustively tested against its specification without understanding its implementation. In these cases, I need to understand the requirement and the test, not the production details, which can actually be a black box. Your examples show that verification is sometimes inadequate, not that it requires full productive competence. The conclusion doesn't generalize.

luciana1u 2mo ago

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customguy 2mo ago

> 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 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 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 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.

johnfn 2mo ago

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.

skydhash 2mo ago
The issue is reliability. I don't need to know the implementation of the database or the lower levels of the network tasks because I trust that they works well. A bug that affects me has a very low chance of occurring and the main risk is me not reading or understanding the docs. With AI generated systems, no one knows what's going on. Not even the AI. When an issue pops up (which has a very good chance to happen because of the complexity of integrations), debugging it can be like reverse engineering obfuscated assembly code.
KronisLV 2mo ago
> Most web developers are perfectly capable without understanding the intricacies of the file system or OS, even though the browser sits on top them. This will mess you up if you ever need to store a significant amount of files on the file system directly, or even deal with resource usage for batch processes, or have to dig into non-trivial transaction handling when dealing with DBs without having learnt enough about them, or even the whole domain of SQL and query optimization that ORMs will not protect you from and so many other things. I don't think you need to know everything, but you definitely need to learn. > But surely at some point you need to stop, right? I guess, but typically due to your own lack of curiosity or mental exhaustion, or even limited time to spend on something, rather than the new knowledge and skills not being good to have. At least knowing when AI is heading in the wrong direction for any given domain will save your bacon.

charbz 2mo ago

https://www.charbzg.com/blog/ai-empowerment https://www.charbzg.com/blog/ai-empowerment

froh 2mo ago
> It is empowering to hand off execution July 26, 2026 > I read David Nicholas Williams's short blog post titled It's not empowering to hand off the details, in which he argues that AI cannot replace expertise because doing good work requires deep familiarity with the details. > I couldn't agree more! > He articulates very well the puzzling phenomenon I see every day with "AI-pilled" colleagues (including many engineers) who trust the model with far more than they should. They delegate the thinking and designing along with the execution, lose touch with the codebase, miss out on critical learnings, and then complain when the slop they produced doesn't solve the original problem. > But I think the argument is incomplete without a counterexample. There is one phase where handing off work to AI is genuinely empowering, and that is worth defining and formalizing.

luciana1u 2mo ago

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feiz45607 2mo ago

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jreynar 2mo ago

Completely agree. The worst sort of manager is the one who wants to stay "high level" and proposes things that either aren't possible or are vastly harder than their idea to "just do X" suggests. And the root cause is them not knowing the details. What gets me excited about AI is that you can hand off some of the detailed work, specifically the repetitive sort. As a sales person, you ought to know how to create a quote for a customer. But creating the 50th one for the same product for the same number of seats becomes drudgery. As a software engineer, you should know how to fix (or at least you should have back in the day) a buffer overrun, but it gets tedious to fix hundreds of them (and I know since I was at Microsoft when we paused Office development to do just that, for months). I bet there's an example for every role. And the benefit of having an AI handle those details -- not the first time, but once you're a master and the AI has become trusted -- is that you can focus on things that require a human being's attention. More creative, more collaborative tasks. Conveniently those tend to be more rewarding than fixing another teensy bug or writing another formulaic email.