[HN Gopher] Two narratives about AI
___________________________________________________________________
Two narratives about AI
Author : RickJWagner
Score : 232 points
Date : 2025-07-24 16:08 UTC (6 hours ago)
(HTM) web link (calnewport.com)
(TXT) w3m dump (calnewport.com)
| itqwertz wrote:
| The real benefactors of AI in software development are senior
| devs who've had enough of boilerplate, framework switching, and
| other tedious low-value tasks. You cut down on the former
| laborious tradition of picking through StackOverflow for glimmers
| of hope.
| almog wrote:
| Yet when you look beyond boilerplate code generation, it's not
| all that LLMs increase experienced developers productivity
| (even when they believe that it does):
| https://arxiv.org/abs/2507.09089
|
| Edit: Hello downvoters, would love to know if you found any
| flawed argument, is this just because this study/comment
| contradicting the common narrative on HN or something else
| entirely?
| CharlesW wrote:
| Is there literally anything other than this single,
| 16-participant study with that validates the idea that
| leveraging AI as an assistant reduces completion time in
| general?
|
| Unless those participants were just complete idiots, I simply
| cannot square this with my last few weeks absolutely
| barnstorming on a project using Claude Code.
| emp17344 wrote:
| The sample size isn't the individual participants, it's the
| hundreds of tasks performed as part of the study. There's
| no indication the study was conducted incorrectly.
| CharlesW wrote:
| Except that the participants were thrown into tasks cold,
| seemingly without even the most basic prep one
| would/should do before throwing AI at a legacy codebase
| (sometimes called "LLM grounding" or "LLM context
| bootstrapping"). If the participants started without
| something like this, the study was either conducted
| incorrectly or was designed to support a certain
| conclusion. LLMs.md +--
| data_model.md +-- architecture.md +--
| infrastructure.md +-- business_logic.md +--
| known_issues.md +-- conventions.md
| n4r9 wrote:
| Was that project fairly early-days? The current impression
| seems to be that AI is useful for accelerating the
| development of smaller and simpler projects, but slows
| things down in large complex codebases.
| whstl wrote:
| This study was about "246 tasks in mature projects". I
| would expect AI to fare much better in a study about new
| projects or brainstorming.
| no_wizard wrote:
| I wish we did a more formal study, but at $previous_job we
| rolled out AI tools (in that case it was github copilot)
| and we found that for 6-8 months productivity largely
| stayed the same or reduced slightly, but _after_ that it
| sharply increased. This was rolled out to hundreds of
| developers with training, guidance, support etc. It was
| done in what I would consider the right way.
| steveklabnik wrote:
| From the paper:
|
| > We do not provide evidence that:
|
| > AI systems do not currently speed up many or most software
| developers
|
| > We do not claim that our developers or repositories
| represent a majority or plurality of software development
| work
| almog wrote:
| Not sure why you quoted that part, it just says that there
| is no assumption for the results to be extrapolated to any
| codebase or any developer, setting the boundaries of the
| study objectives.
| steveklabnik wrote:
| You have made the claim that it does extrapolate. Which
| they themselves do not make.
| itsafarqueue wrote:
| That study is going to go down as the red herring it is.
| Shows little more than people with minimal experience using
| LLMs for dev do it wrong.
| whynotminot wrote:
| One of the problems with this study is that the field is
| moving so very fast.
|
| 6 months in models is an eternity. Anthropic has better
| models out since this study was done. Gemini keeps getting
| better. Grok / xAI isn't a joke anymore. To say nothing of
| the massive open source advancements released in just the
| last couple weeks alone.
|
| This is all moving so fast that one already out of date
| report isn't definitive. Certainly an interesting snapshot in
| time, but has to be understood in context.
|
| Hackernews needs to get better on this. The head in the sand
| vibe here won't be tenable for much longer.
| stronglikedan wrote:
| > Hello downvoters... is this just because...
|
| Since you asked, I downvoted you for asking about why you're
| being downvoted. Don't waste brain cells on fake internet
| points - it's bad for your health.
| oidar wrote:
| The volume of emotion running through the discourse on LLMs feel
| qualitatively different compared to something like bitcoin.
| poly2it wrote:
| I'm so tired of it. Lobste.rs has become unusable due to the
| endless echoes of resentment.
| logicchains wrote:
| Have some empathy. Even if it's not certain, there's a non-
| zero possibility that a large number of developer jobs
| (especially those focused purely on coding) will go the way
| of factory workers and switchboard operators, and if that
| happened it'd be a very tough transition for many people.
| johnfn wrote:
| I seem to recall an endless string of comments mockingly
| reporting that "crypto bros" were "speedrunning the discovery
| of every financial regulation" every time a new crypto news
| article popped up anywhere. You could have set your watch to
| it.
| mperham wrote:
| One could mostly ignore Bitcoin. AI usage and its network
| effects are much more widespread and often place additional
| work on me, even if I choose not to use AI directly. Incorrect
| issues or pull requests, unmaintainable heaps of code, etc.
| ninetyninenine wrote:
| Crypto doesn't have implications of replacing your programming
| skills.
| fragmede wrote:
| At the end of the day Bitcoin is a networked technology. It's
| worthless to me if you/the store/landlord/taxman won't take it,
| and most of them don't, so its value is only between adherents,
| which means, sure, I can buy some, but then what? Use it to buy
| something sketchy online?
|
| Meanwhile, anyone can go to chat.com and ask for code to do
| whatever they ask. Some questions it will answer well, others
| it will not. Because we're discussing this in the abstract, LLM
| good!/LLM bad! Grar!, and barely touching on details, like the
| programming language, the libraries, nevermind sharing the
| prompts, both camps are convinced they're right, with much more
| furvor than Bitcoin. Additionally the technology is evolving so
| fast that someone's bad experience from a couple months ago is
| already out of date. Meanwhile, how many times can you have the
| same argument about Bitcoin? There are a couple details here
| and there, but nothing structurally changed with Bitcoin since
| its inception. Which is a shame, if they'd managed to fork so
| transactions weren't horribly slow, maybe we'd be having a
| different discussion. But I digress.
|
| The volume of emotion is different, not because of the money
| swimming around, of which there is a lot, but because we're
| arguing over things we see with our own eyes but aren't giving
| enough detail to have productive discussions about. Insulting
| people adds to the emotionally charged nature. Things like "If
| you find LLMs used, it's because you're a bad programmer/an
| idiot/only work on loser problems" or "AIs going to put you out
| of a job" don't encourage reasonable nuanced discussion.
| Insulting someone for liking Bitcoin doesn't cut as deep. No
| one's been working on Bitcoin for four decades and made it
| their whole (public) identity.
| Karrot_Kream wrote:
| > No one's been working on Bitcoin for four decades and made
| it their whole (public) identity.
|
| It sounds like a large part of the problem is getting your
| identity wrapped up into this. Both the CEOs and the devs.
| fragmede wrote:
| To be clear, I was referring to programming ability when I
| was referring to identity, not AI. It's sometimes hard for
| me to forget that you are not your code.
| Karrot_Kream wrote:
| Yes I mean that too. I have no idea how you can "measure"
| programming ability. The whole concept confuses me. I've
| been coding since I was a kid and have contributed to
| FOSS and closed codebases. There's certainly programmers
| out there that I consider _bad_ , but beyond that there's
| no way to measure how "good" someone is at coding. The
| fact that people can identify around their perception of
| programming skill is deeply confusing to me and makes
| these sorts of reactions even harder to understand.
| fragmede wrote:
| Programmers are just as emotional as the next human, no
| matter how much they want to believe otherwise, so almost
| all of them (myself included) think they're better than
| average, which can't actually be true.
|
| Skill is linked to prestige and loosely linked to pay,
| which gets linked back to prestige. Thus even without an
| actual measure of programming ability, if someone says
| "you couldn't program your way out of a paper bag", it's
| hard for most people not to feel insulted, linking back
| to prestige. Not everyone buys into that, or is impulsive
| enough to respond emotionally, of course, but it should
| at least make sense on a conceptual level.
| jeanlucas wrote:
| I don't like titles like this :( I don't wanna read it
| ducttapecrown wrote:
| Here, I asked ChatGPT to summarize it for you:
|
| just kidding.
| 827a wrote:
| Here's something I assert to know about how AI and software
| engineering intersect in 2025: It makes certain classes of tasks
| 150% faster, while making other classes of tasks 300% slower.
| What I rarely know upfront is whether a given task will fall into
| the former class or the latter.
| titaniumrain wrote:
| The author is the only one knows something about AI! wink wink
| wink
| gausswho wrote:
| If you'd read the article, you'd know that's not what he's
| purporting.
| Loic wrote:
| The full advice:
|
| My advice, for the moment:
|
| - Tune out both the most heated and the most dismissive
| rhetoric.
|
| - Focus on tangible changes in areas that you care about that
| really do seem connected to AI--read widely and ask people
| you trust about what they're seeing.
|
| - Beyond that, however, follow AI news with a large grain of
| salt. All of this is too new for anyone to really understand
| what they're saying.
|
| AI is important. But we don't yet fully know why.
|
| With that, it shows that he is not really using the AI tools,
| he would be using them he would have given this advice :
|
| - try the tools and look where they can improve your life.
| titaniumrain wrote:
| These tips seem like common knowledge -- essentially, it's
| similar to a reminder to be cautious about what you eat
| when you haven't prepared the meal yourself.
| stonemetal12 wrote:
| >AI is important. But we don't yet fully know why.
|
| And that is how you know it is hype and not actually
| important. Imagine any other actually important thing then
| try to add we don't know why. Doctors important but we
| don't know why. Electric cars important but we don't know
| why. Computers important but we don't know why. It just
| doesn't work.
| paul7986 wrote:
| What about graphic, web and app design? I just do not see a long
| term career going forward (been meaning to research how many UX
| jobs are being listed in 2025 to previous years). UX Research I
| do as you are interacting with users and AI is not a person
| (yet).
| zer00eyz wrote:
| There hasn't been enough real "UX" work since before 2008. Most
| companies arent running focus groups. They haven't put their
| designs in front of real users (real usability testing) and
| gotten feed back on them.
|
| Yes online tools are great and all but you're only getting
| feedback from the people already in. "I can get through your
| poorly designed app for work" is not something an online tool
| will tell you.
|
| As for design, there was this tool posted a few days ago:
| https://finddesignagency.com
|
| Great effort by the person who made it. The product they are
| showing off made me think of the line from the song "and they
| are all made out of ticky tacky and they all look just the
| same"
| hooverd wrote:
| AI, to me, specifically in the field of UX, feels like it's
| pushed as a panacea for having to do actual fucking UX work.
| Just throw everything behind a natural language interface! Slop
| it up!
| iambateman wrote:
| While I read this article, Claude code was fixing a bug for me.
|
| I agree with Cal that we basically don't know what happens next.
| But I do know that the world needs a lot more good software and
| expanding the scope of what good software professionals can do
| for companies is positive.
| thinkingtoilet wrote:
| I wonder if you would say this if, say, in a year you're laid
| off because AI got good enough to write your code. Would you be
| happy that there is better software in the world at the expense
| of your job?
| iambateman wrote:
| I'm optimistic - perhaps naively - about my ability to retool
| within work.
|
| 10 years ago, I was building WordPress websites for
| motivational speakers. Today, I build web apps for the
| government. Certainly in 10 years we will be in a different
| place than we are today.
|
| Your argument, taken in a broader sense, would have us
| tending to corn fields by hand to avoid a machine taking our
| job.
| thinkingtoilet wrote:
| That was a terrific non-answer. The difference is the
| industrial revolution created jobs, at some point
| technology will remove jobs. I'm sure you'll be thrilled to
| be out of a job in the name of good software. It's amazing
| how the tune changes so quickly when it's your job on the
| line.
| iambateman wrote:
| Sure, AI may break the American economic system - which
| would be negative both for me, you, and the entire world.
| I would not relish that and I think we should ask our
| brightest young thinkers to imagine a world in which the
| productivity gains from AI don't simply accrue to capital
| holders.
|
| Getting back to Cal's point, I think there's a lot of
| legitimate questions and uncertainties about what
| knowledge work will look like over the next decade. You
| say that technology will remove jobs...and I think you're
| right directionally, but I can't tell you the timeline
| for that, nor it's effects.
|
| While I love being a software engineer, what that
| actually looks like on a daily basis has materially
| changed _a lot_ every few years. Sitting for a day
| debugging why my SCSS won't render is not the core value
| I bring to this world as a human.
| gishglish wrote:
| > Your argument, taken in a broader sense, would have us
| tending to corn fields by hand to avoid a machine taking
| our job.
|
| To play off another analogy commonly used in this topic:
| you are the horse, not the rider. Sure some horses will
| find new work, at the grace of their owners. Some lucky
| individuals may even get a carefree life of mostly leisure.
|
| But for many, it's off to the glue factory, and not for a
| job.
| NickNaraghi wrote:
| Big nothingburger which is particularly surprising given the
| quality of Newport's other work. tl;dr don't believe the extreme
| takes while we are in a time of high uncertainty.
| softwaredoug wrote:
| There are different groups with vested interests that color a lot
| of AI discourse
|
| You have Tech CEOs that want work done cheaper and AI companies
| willing to sell it to them. They will give you crazy alarming
| narratives around AI replacing all developers, etc.
|
| Then you have tech employees who want to believe they're
| irreplaceable. It's easy to want to keep working how we've always
| worked with hope of getting back to pre 2022 levels of software
| hiring and income. AI stands in the way of that.
|
| I don't think people are doing this intentionally all the time.
| But there is so much money and social stature from all these
| groups on the line, there are very few able to give a neutral,
| disinterested perspective on a topic like AI coding.
|
| And to add to that, reasoned, boring, thoughtful middle of the
| road takes are just naturally going to get fewer eyeballs than
| extreme points of view.
| PaulDavisThe1st wrote:
| > you have [ ... ]. then you have [ ... ]
|
| Those are groups defined by something other than actual LLM
| usage, which makes them both not particularly interesting. What
| is interesting:
|
| You have people who've tried using LLMs to generate code and
| found it utterly useless.
|
| Then you have people who've tried using LLMs to generate code
| and believe that it has worked very well for them.
| 0x500x79 wrote:
| I think this is an easy thing to wrap my mind around (since I
| have been in both camps):
|
| AI can generate lots of code very quickly.
|
| AI does not generate code that follows taste and or best
| practices.
|
| So in cases where the task is small, easily plannable, within
| the training corpus, or for a project that doesn't have high
| stakes it can produce something workable quickly.
|
| In larger projects or something that needs maintainability
| for the future code generation can fall apart or produce
| subpar results.
| logicchains wrote:
| Recent LLMs are fairly good at following instructions, so a
| lot of the difference comes down to the level of detail and
| quality of the instructions given. Written communication is
| a skill for which there's a huge amount of variance among
| developers, so it's not surprising that different
| developers get very different results. The relative quality
| of the LLM's output is determined primarily by the written
| communication skills of the individuals instructing it.
| mattwad wrote:
| Yea this! How many devs say "it doesn't do what i expect"
| did not try to write up a plan of action before it just
| YOLO'd some new features? We have to learn to use this
| new tool, but how to do that is still changing all the
| time.
| no_wizard wrote:
| Corpus also matters. I know Rust developers who aren't
| getting very good results even with high quality prompts.
|
| On the other hand, I helped integrate Cursor as a staff
| engineer at my current job for all our developers (many
| hundreds), who primarily work in JavaScript / TypeScript,
| and even middling prompts will get results that only
| require refactoring, assuming the LLM doesn't need a ton
| of context for the code generation (e.g. greenfield or
| independent features).
|
| Our general approach and guidance has been that
| developers need to write the tests _first_ and have
| Cursor use that as a basis for what code to generate.
| This helps prevent atrophy and over time we 've find
| thats where developers add the most value with these
| tools. I know plenty of developers want to do it the
| other way (have AI generate the tests) but we've had more
| issues with that approach.
|
| We discourage AI generating everything and having a human
| edit the output, as it tends to be slower than our chosen
| approach and more likely to have issues.
|
| That said, LLMs still struggle if they need to hold alot
| of context. For instance, if you have a bunch of files
| that it needs to understand to _also_ generate code that
| is worthwhile, particularly if you want it to re-use
| code.
| logicchains wrote:
| >Corpus also matters. I know Rust developers who aren't
| getting very good results even with high quality prompts.
|
| Which model were they using, out of interest? I've gotten
| decent results for Rust from Gemini 2.5 Pro. Its first
| attempt will often be disgusting (cloning and other
| inefficiencies everywhere), but it can be prompted to
| optimise that afterwards. It also helps a lot to think
| ahead about lifetimes and explicitly tell it how to
| structure them, if there might be anything tricky
| lifetime-wise.
| no_wizard wrote:
| No idea. I do know they all have access to Cursor and
| tried different models, even the more expensive options.
|
| What you're describing though, having to go through _that
| elaborate detail_ really drives to my point though, and I
| think shows a weakness in these tools that is a hidden
| cost to scaling their productivity benefits.
|
| What I can tell you though both from observation and
| experience, is that because the corpus for TypeScript /
| JavaScript is infinitely larger as it stands today, even
| Gemini 2.5 Pro will 'get to correct' faster even with
| middling prompt(s) vs for a language like Rust.
| abalashov wrote:
| I do a lot of work in a rather obscure technology
| (Kamailio) with an embedded domain-specific scripting
| language (C-style) that was invented in the early 2000s
| specifically for that purpose, and can corroborate this.
|
| Although the training data set is not wholly bereft of
| Kamailio configurations, it's not well-represented, and
| it would be at least a few orders of magnitude smaller
| than any mainstream programming language. I've
| essentially never had it spit out anything faintly useful
| or complete Kamailio-wise, and LLM guidance on Kamailio
| issues is at least 50% hallucinations / smoking crack.
|
| This is irrespective of prompt quality; I've been working
| with Kamailio since 2006 and have always enjoyed writing,
| so you can count on me to formulate a prompt that is both
| comprehensive and intricately specific. Regardless, it's
| often a GPT-2 level experience, or akin to running some
| heavily quantised 3bn parameter local Llama that doesn't
| actually know much of anything specific.
|
| From this one, can conclude that a tremendous amount of
| reinforcement for the weights is needed before the LLM
| can produce useful results in anything that isn't quasi-
| universal.
|
| I do think, from a labour-political perspective, that
| this will lead to some guarding and fencing to try to
| prevent one's work-product from functioning as free
| training for LLMs that the financial classes intend to
| use to displace you. I've speculated before that this
| will probably harm the culture of open-source, as there
| will now be a tension between maximal openness and
| digital serfdom to the LLM companies. I can easily see
| myself saying:
|
| I know our next commercial product (based on open-source
| inputs) releases, which are on-premise for various
| regulatory and security reasons, will be binary-only; I
| have never customers looking through our plain-text
| scripts before, but I don't want them fed into LLMs for
| experiments with AI slop.
| NoOn3 wrote:
| It seems to me If you know all these instructions
| clearly, then you know everything, and it's easy for you
| to write the code yourself, and you don't need an LLM.
| logicchains wrote:
| The amount of typing it takes to describe a solution in
| English text is often less than the amount of typing
| needed to actually implement it in code, especially after
| accounting for boilerplate and unit tests. Not to mention
| the time spent waiting for the compiler and test harness
| to run. As a concrete example, the HTTP2.0 spec is way
| fewer chars long than any HTTP2.0 server implementation,
| and the C spec is way fewer chars long than any compliant
| C compiler. The C++ spec is way, way fewer chars long
| than any compliant C++ compiler.
| no_wizard wrote:
| >The amount of typing it takes to describe a solution in
| English text is often less than the amount of typing
| needed to actually implement it in code
|
| I don't find this to be true. I find describing a
| solution in English _well_ to be slower than describing
| the problem _in code_ (IE, by writing tests first) and
| having that be the structured data that the LLM uses to
| generate code.
|
| Its far faster, from the results I'm seeing plus my own
| personal experience, to write clear tests which benefit
| from being a form of structured data that the LLM can
| analyze. Its the guidance we have given to our engineers
| at my day job and it has made working with these tools
| dramatically easier.
|
| In some cases, I have found LLM performance to be subpar
| enough that it is indeed, faster to write it myself. If
| it has to hold many different pieces of information
| together, it starts to falter.
| svantana wrote:
| I don't think it's so clear-cut. The C spec I found is
| 4MB and the tcc compiler source code is 1.8MB. It might
| need some more code to be fully compliant, but it may
| still be smaller than 4MB. I think the main reason why
| code bases are much larger is because they contain stuff
| not covered by the spec (optimization, vendor-specific
| stuff, etc etc).
|
| Personally I'd rather write a compiler than a
| specification, but to each their own.
| steveBK123 wrote:
| Use shorter variable names
| dasil003 wrote:
| Yes, and also writing for an LLM to consume is its own
| skill with nuances that are in flux as models and tooling
| improves.
| fhd2 wrote:
| That about sums it up from my experience as well. But as
| parent said, such takes unfortunately don't get a lot of
| eyeballs :(
| fragmede wrote:
| That was four short paragraphs with basically no details
| - there's basically nothing for eyeballs to see. If I
| wrote a history of the world that consisted of "Some
| people lived and died, some of them were bad, I guess",
| how many copies do you think I'd sell? Any? What's
| interesting is the details, and a post giving actual
| detail of building some app, and the benefits and
| shortcomings of a specific tool would be of great
| interest to many. If I ask an LLM to save the date to the
| database, and then ask it to save the time, do I get two
| variables in two columns? Does that make sense for my
| app? Do I have to ask it to refactor? Is it able to do
| that successfully? Does it drop tables during program
| initialization? How does the latest model do with
| designing the entire program? How often does it
| hallucinate for this set of libraries and prompts?
| There's quite a bit of variance! If it hallucinated
| libraries and APIs left and right it would be far less
| useful. Some people don't even get hallucinations because
| their prompts are so we'll trod. There are all sorts of
| interesting details to be learned and shared about these
| new tools that would get a ton of eyeballs.
| fmbb wrote:
| LLMs also don't always generate code that works.
|
| And you don't always know or understand what the product
| owner wants you to build.
|
| Writing code faster is very rarely what you need.
| brazzy wrote:
| I've just seen that change happen in the a pet project
| within less than 10 hours of work.
|
| I tried vibe-coding something for my own use, your classic
| "scratch your own itch" project.
|
| The first MVP was a one-shot success, really impressive.
|
| But as the code grew with every added feature, progress
| soon slowed down. The AI claimed to have fixed a bug when
| it didn't. It switched chest several timea back and forth
| between using a library function and rolling its own
| implementation, each time claiming to have "simplified" the
| code and made it "more reliable". With every change, it
| claimed to have "improved" the code, even when it just
| added a bunch of shamelessly duplicated shit.
|
| One effect I am sure AI will have is to massively excarbate
| the phenomenon of people who quickly produce a large amount
| of shitty, unmaintainable code that fulfills half the
| requirements, and then leave the mess behind for another
| greenfield project.
| AaronAPU wrote:
| We're so unaccustomed to working with non-deterministic
| computer tech that rather than acknowledge they are hit-
| or-miss, everyone just picks one side and goes all-in on
| it.
|
| Which sounds an awful lot like politics.
| jandrese wrote:
| I think there is a strong case that experienced developers
| can not be replaced by AI anytime soon. Where the danger lies
| is for junior developers fresh out of college. How are they
| supposed to become experienced developers if an AI can do the
| grunt work they normally get assigned?
|
| It really doesn't help that AI companies are hype machines
| full of salesmen trying to hype up their product so you buy
| it. There have been a lot of amazing AI "success stories"
| that don't hold up under scrutiny.
| elktown wrote:
| > Where the danger lies is for junior developers [...] if
| an AI can do the grunt work they normally get assigned?
|
| Just because "well, maybe true for junior devs!" is a
| compromise over "AI will make all programmers obsolete!" it
| doesn't make it reasonable. It's still an extraordinary
| claim.
| qsort wrote:
| And then you have research that says they're _both_ full of
| shit. The article is perhaps a bit shallow, but it 's
| spiritually correct: there's a lot of uncertainty and people
| who claim they figured it all out are mostly spewing
| nonsense.
| rapind wrote:
| I mean it's working for me. It's definitely not living up
| to the hype IMO (market is way overvaluing), but I wouldn't
| want to work without it any more, which is actually saying
| a lot.
|
| This take is as a senior (greybeard) developer using paid
| claude-code in the terminal only (I use plain vim for my
| own code). I'm running my own business while wearing all of
| the hats, so I'm not as worried about becoming obsolete,
| but I also have zero motivation to get other businesses
| using it (I'm not invested into any AI companies)!
|
| To be honest, I could probably even be using it better, but
| I haven't spent much time yak shaving over my setup beyond
| zen mcp.
|
| That being said, I think anyone looking to invest into
| established AI companies right now is in for a rude
| awakening. I think it'll be a commodity / utility like
| cloud computing with tons of competition and not a ton of
| differentiating features. That's just my opinion though,
| and I could be horrendously wrong!
| qsort wrote:
| I'm also seeing benefits, and I'm on pretty much the same
| stack as you. The METR paper I'm citing was misquoted a
| lot (N was small, and it wasn't a favorable setup for AI
| tools), but the most important finding was that it's very
| easy to fool ourselves about productivity benefits.
|
| Am I going to cancel my Anthropic subscription? Certainly
| not, but I'm not going to pretend like my setup is The
| One True Way. The plural of anecdote isn't data. Nobody
| has this figured out, nobody.
| victorbjorklund wrote:
| Or are those people biased by what they want to be true
| because of their current situation (the dev who dont wanna
| change how they work and therefore wants AI to not work or
| the non-technical person who dont wanna learn to code or be
| dependent on a developer and therefore want it to work)
| setr wrote:
| I think the problem with this one is that LLMs are somehow
| both unreasonably effective as well as unreasonably
| ineffective. Letting the code editor llms do their
| suggestions, I've gotten a ton of useless boilerplate garbage
| suggestions, but periodically, a couple times of day, it
| suggests blocks of code that are far more complete,
| comprehensive and correct than it has any right to be.
|
| Whether you'll get the high IQ or low IQ LLM on the next
| suggestion is a crapshoot; how much consideration you give to
| either outcome (focus on the random instances of brilliance,
| or the constant stream of bullshit) drives the final
| perception.
| awfulneutral wrote:
| That has been my experience too. I recently turned it all
| off because I decided the amount of times it takes me 5x
| longer to accomplish something, in addition to the subtle
| increase of bugs, is not currently worth it. I guess I'll
| try it again in a few months.
| abalashov wrote:
| > Whether you'll get the high IQ or low IQ LLM on the next
| suggestion is a crapshoot
|
| I have heard theories from people--whose ideas I don't
| ordinarily consider to be in the realm of purely uninformed
| speculation--that this can vary depending on system-wide
| GPU load, and is throttled accordingly based on real-time
| demand by the major LLM providers.
|
| Whether it's true, I have no idea.
| emp17344 wrote:
| Sounds like conspiratorial thinking to come to terms with
| the fact that LLMs are fundamentally non-deterministic
| text predictors. You can get dramatically different
| responses to the same question, and that's just how the
| system works.
| abalashov wrote:
| That was my reaction as well, but I wondered.
| no_wizard wrote:
| >Then you have tech employees who want to believe they're
| irreplaceable. It's easy to want to keep working how we've
| always worked with hope of getting back to pre 2022 levels of
| software hiring and income. AI stands in the way of that.
|
| Eventually, things will stabilize to a point where we will know
| what the boundaries of all the new LLM based tooling is good
| for, and where humans add lots of value to that.
|
| That will then drive a maximalist hiring spree, as the more
| people you have working at an increase in velocity, the faster
| you ship, and for once, perhaps the quality of code won't
| substantially decrease, assuming LLMs improve another few leaps
| in output quality and engineering workflows adjust in a
| normalized way.
|
| Thats the hopeful side of the equation anyway.
|
| I feel incredibly bad about customer oriented jobs, like white
| glove customer service. I already saw a trend (especially since
| 2020 but certainly before as well) where these AI chat bots and
| AI support lines will decimate that job category. These are
| pretty common white collar jobs, lots of people even in our
| industry got their starts on support lines.
| Exoristos wrote:
| I don't think any normal customer is going to want to talk to
| AI, once the novelty wears off. It's going to be "Let me talk
| to your supervisor" almost every time.
| jgilias wrote:
| Oh, but there's something called "containment" that you
| measure and optimize on your chatbots.
| abalashov wrote:
| Maybe. It all depends on whether the AI can actually solve
| your problem.
| danielbln wrote:
| Yeah, if the AI isn't shite and has access to tools to
| solve my problem, I'll take it over some overworked and
| undermotivated human call center any day.
| itsafarqueue wrote:
| That's just like, your opinion man.
| sensanaty wrote:
| Co I work for creates customer support software, so
| naturally we have some AI solution available to people.
|
| A lot of our customers (aka businesses deploying our
| customer support software for _their_ customers) are
| telling us people fucking _hate_ dealing with AI in
| literally any capacity, even if some of the stuff we offer
| actually works quite good (FAQ bots, bots that redirect to
| the proper channels /teams and stuff like that). The
| C-suite at my company have had to go back on some of their
| OKRs of late, because after an initial huge bump of AI
| usage, clients are starting to kill off the AI tooling and
| our usage numbers are dwindling because _their_ customers
| hate it.
|
| I get to see some of the chats people have with the AI
| systems, and people will straight up say slurs in chats
| because they know it's the quickest way of escalating to an
| actual human lol. People _really_ don 't like this crap,
| but of course CEOs and their ilk are usually psychopaths so
| they don't really give a shit if it means they can save 5
| cents per user.
| layer8 wrote:
| > the more people you have working at an increase in
| velocity, the faster you ship
|
| That sounds like a contradiction to Brooks's law, which I
| don't see being invalidated by AI tooling.
| dijit wrote:
| idk, I'm not a software engineer. I'm a sysadmin.
|
| Or, am I a "devops engineer"?
|
| or.. a "SRE"...
|
| or... am I a platform engineer?
|
| You know what, I don't know.
|
| What I _do_ know, is that people keep trying to make my job
| obsolete, only to hire me under a different title for more
| money later. The practices and the tools are the same too, yet
| to justify it to themselves they 'll make shit up about how the
| work is "actually, a material difference from what came before"
| (except, it's really not).
|
| I'm still employable after 20 years of this.
|
| I'm not a software engineer, and I'm not a tech CEO - I don't
| care, but people have been trying to replace me my whole career
| (even myself: "Automate yourself out of a job" is a common
| sysadmin mantra after all). Yet, somehow, I'm still here.
| kshacker wrote:
| Same here, but this time is different. Truly.
|
| Some of the easy jobs will be taken away and your job is not
| under threat. Right? But some of the people who were doing
| low skilled jobs will grow to compete with you. Less supply
| more demand. Either the pay will come down or there are very
| few jobs. Fingers crossed.
| dylan604 wrote:
| > But some of the people who were doing low skilled jobs
| will grow to compete with you.
|
| Yes, and this is not shocking. This is how it is meant to
| work. You get a low level job because you're new and have a
| lot to learn. You learn more things as you work the low
| level job, and then you can get promoted or move to a new
| role that is not so low level. You keep growing until you
| eventually compete with the people that were senior level
| when you were working that low level job.
| dijit wrote:
| It always feels like "this time its different".
|
| NoOps, NoSQL, Heroku, PaaS, IaaS.
|
| Maybe there are less people in operations than before,
| there are certainly some companies that do their best not
| to employ any operations focused people and use FaaS for
| everything and only hire feature developers... who, end up
| doing the operations work that crops up.
|
| _shrug_
| thewebguyd wrote:
| > Maybe there are less people in operations than before
|
| Even that ended up not being true, and I'd argue we have
| even more people doing ops now than we did before all the
| buzzwords.
|
| Going to change my job title to cockroach because no
| matter how many times companies and trends have tried to
| kill ops, I'm still around, and sometimes in larger
| numbers.
| dylan604 wrote:
| > "Automate yourself out of a job" is a common sysadmin
| mantra after all
|
| Not just sysadmin. I've been automating the hell out of
| tedious mundane tasks that are done by error prone humans,
| and only become more error prone as they get tired/bored of
| these mundane tasks. The automation essentially just becomes
| a new tool/app for the humans to use.
|
| At this point of my experience doing this, employees scared
| of automation are probably employees that aren't very good at
| their job. Employees that embrace this type of automation are
| the ones that tend to be much better at their job.
| benlivengood wrote:
| If you're like me, though, your day-to-day has probably
| shifted a lot.
|
| My day used to be making sure desktops worked and we had a
| repeatable process to make new good desktops out of all the
| complex client software they needed.
|
| Then I made sure servers got upgraded and patched and taken
| care of on a day-to-day level, although it was still someone
| else's job to keep desktops running. At home I compiled my
| own kernels and used tarballs to install and update packages.
| Desktop hardware support was iffy in Linux.
|
| Then I jumped to borg and tupperware and kubernetes where
| hardware never mattered and it almost didn't matter what
| clients had because the browser they used auto-updated. At
| home I switched to distros where package management was
| automatic and rarely, if ever, broke.
|
| I don't even know the hostnames or the network addresses of
| the hardware that runs my services, and AWS or GCP SREs
| probably rarely need to know either. Now I care about an
| abstract thing called a service that is instrumented with
| logs, metrics, and traces that would put the best local
| development tools of 20 years ago to shame. CI/CD and
| infrastructure as code pipelines actually did automate away
| many of the checklist-style sysadmin work of the past. At
| home I could run Talos and Ceph and Crossplane if I wanted to
| but so far I've dragged the old days of individual hosts
| along mostly for nostalgia.
|
| I expect to eventually end up caring about systems at an even
| more abstract level once something like Crossplane becomes as
| universal as Terraform and GitHub actions. They'll probably
| run on something like web assembly on bare metal because no
| one actually cares what's underneath their containers if they
| keep working.
|
| The stack of technology gets taller and more abstract and as
| it does so the job of caring about the lower layers gets
| automated and the lower layers get, if not simplified,
| standardized to the point that automation is more reliable
| than human intervention.
|
| Humans will only get squeezed out of the loop when superhuman
| artificial intelligence arrives and our abstract design and
| management of systems becomes less reliable than the
| automation. Then hopefully we get a nice friendly button to
| push for more automatically-human-aligned utility.
|
| EDIT: That's not to say that the lower levels can be
| automatically _designed_ ; not yet at least. Eventually once
| AI is good enough at formal design then quite likely. We
| still need low-level software engineering to keep building
| the stack but it is vastly more commoditized (the one open
| source developer in the xkcd cartoon keeping 99% of the
| world's infrastructure running on a 20-year old tool/utility)
| Exoristos wrote:
| Each generation of young workers seems to need to learn for
| themselves that the class warfare is endless, and mundane.
| mattgreenrocks wrote:
| Very helpful insight, thank you!
| petethepig wrote:
| Many jobs aim to solve problems so well that there's nothing
| left to fix -- doctors curing illnesses, firefighters
| preventing fires, police reducing crime, pest control
| eliminating infestations, or electricians making lasting
| repairs. And that's totally fine -- people still have jobs,
| and when it works, it's actually great for everyone.
| lovich wrote:
| > when it works
|
| That's a load bearing phrase
| oooyay wrote:
| I really loath that part of this industry; I spent over a
| decade in it and the only tangible thing I've taken away from
| it is that the problems these philosophies and practices set
| out to solve are derivative of two things:
|
| - Infrastructure is very often fundamentally disconnected
| from the product roadmap and thus is under constant cycles of
| cost control
|
| - The culture of systems administration does not respond well
| to change or evolution. This is a function that is built
| around shepherding systems - whether at scale or as pets.
|
| Long way of saying the gamut isn't that corporations will
| ever be free of systems administration any more than they'll
| be freed from software engineering. It is far easier to
| optimize software than it is to optimize infrastructure
| though, which is why it feels like someone is coming after
| you. To make matters more complex, a lot of software today
| overlaps with the definition of infrastructure.
| righthand wrote:
| Thank you for this, not only on the Ai-related discussion but
| painting the sense that sys admin work is still as complex
| and finnicky as it ever was. All we did with that role is let
| Amazon evangelize some weird taxing "standard" for hosting.
| empath75 wrote:
| There are also a large number of people who have a deep-seated
| philosophical objection to the entire project of ai. It's not
| just about their job, it's about their sense of who and what
| they are as a human being, their soul or whatever. They will
| insist that AI's do not think or know anything, no matter what
| evidence there is to contrary.
| emp17344 wrote:
| Everyone has an agenda. Similarly, groups like r/singularity
| and the rationalists have spent years predicting the oncoming
| advent of a machine god, and are desperately reading too much
| into every LLM advancement.
| dragonwriter wrote:
| > It's easy to want to keep working how we've always worked
|
| There is no "how we've always worked"; there was no steady
| state. Constant evolution and progressive automation of the
| simpler parts has been the norm for software development
| forever.
|
| > with hope of getting back to pre 2022 levels of software
| hiring and income. AI stands in the way of that.
|
| It doesn't, though. Productivity multipliers don't reduce
| demand for the affected field or income in it. (Tight money
| policies and economic slowdowns, especially when they co-occur,
| do, though, especially in a field where much of the demand and
| high income levels are driven by speculative investment, either
| in startups or new ventures by established firms.)
| ninetyninenine wrote:
| Thank you. This is the most accurate take of what's going on.
| Though the overwhelming population of people aren't CEOs. It's
| people.
|
| That's why the sentiment among most people and also HN is
| highly negative against AI. If you're reading this you likely
| have that bias.
| greenie_beans wrote:
| it has devalued the labor. i scoped a contract but they want me
| to do it in less time now that we have AI. this lets them pay
| me less for the same work. and AI CEOs sell it as "society will
| do less work" but instead now i'm expected to do more work
| because the work takes less time. same as it ever was with
| technology advances.
| wincy wrote:
| Look, maybe I'm saying the quiet part out loud, but if software
| engineering isn't where the money is at anymore, and those jobs
| go away, I'd be competent at something else. I'm a smart
| person. I work hard. I'm confident I'd be able to displace
| someone who isn't as smart as me and just "take" their job.
|
| There's going to be a need for smart people with a good work
| ethic unless _literally_ everyone loses their jobs, and at that
| point we're living past the singularly event horizon as far as
| I'm concerned and all bets are off.
| o_nate wrote:
| Maybe it's too soon to say that autonomous LLM agents are the
| wave of the future and always will be, but that's basically
| where I'm at.
|
| AI code completion is awesome, but it's essentially a better
| Stack Overflow, and I don't remember people worrying that Stack
| Overflow was going to put developers out of work, so I'm not
| losing sleep that an improved version will.
| abalashov wrote:
| The problem with the "agents" thing is that it's mostly hype,
| and doesn't reflect any real AI or model advances that makes
| them possible.
|
| Yes, there's a more streamlined interface to allow them to do
| things, but that's all it is. You could accomplish the same
| by copy-and-pasting a bunch of context into the LLM before
| and asking it what to do. MCP and other agent-enabling data
| channels now allow it to actually reach out and do that
| stuff, but this is not in itself a leap forward in
| capabilities, just in delivery mechanisms.
|
| I'm not saying it's irrelevant or doesn't matter. However, it
| does seem to me that as we've run out of low-hanging fruit in
| model advances, the hype machine has pivoted to "agents" and
| "agentic workflows" as the new VC-whetting sauce to keep the
| bubble growing.
| o_nate wrote:
| I don't want to blame Alan Turing for this mess, but his
| Turing Test maybe gave people that idea that something that
| can mimic a human in conversation is also going to be able
| to think like a human in every way. Turns out not to be the
| case.
| abalashov wrote:
| Well, I agree with you. But I'd be remiss not to say that
| this is a lively controversy in the world of cognitive
| science and philosophy of mind.
|
| To one camp in this discursive space, who of course see
| themselves to be ever the pragmatists, the essence of the
| polemic about whether LLMs can "think" is not about
| whether they think in exactly the same ways we do or
| capture the essence of human thinking, but whether it
| matters at all.
| o_nate wrote:
| Well, it's an interesting question. I'm not sure we
| really know what "thinking" is. But where the rubber
| meets the road in the case of LLM agents is whether they
| can achieve the same measurable outcomes as a human
| agent, regardless of how they get there. And it seems not
| at all clear how to build those capabilities on top of an
| admittedly impressive verbal ability.
| abalashov wrote:
| It may be because I've a writer/English major
| personality, and so am very sensitive to the mood and
| tone of language, but I've never had trouble
| distinguishing LLM output from humans.
|
| I'm not suggesting anything so arrogant as that I cannot
| be fooled by someone intentionally deploying an LLM with
| that aim; if they're trained on human input, they can
| mimic human output, I'm sure. I just mean that the
| formulations that come out of the mainstream public LLM
| providers' models, guided however they are by their
| pretraining and system prompts, are pretty unmistakably
| robotic, at least in every incarnation I've seen. I
| suppose I don't know what I don't know, i.e. I can't rule
| out that I've unknowingly interacted with LLMs without
| realising it.
|
| In the technical communities in which I move, there are
| quite a few forums and mailing lists where low-skilled
| newbies and non-native English speakers frequently try to
| disgorge LLM slop. Some do it very blatantly, others must
| believe they're being quite sly and subtle, but even in
| the latter case, it's absolutely unmistakable to me.
| steveBK123 wrote:
| Also judging by my LinkedIn, but all the senior tech execs on
| the job market are now Generative AI Experts, which is funny
| because I thought they were all Cryptocurrency Experts when I
| last saw them posting this much in 2020.
| jofla_net wrote:
| The best is when you work with one, in a small enough
| company. During which they extoll some currently-hot grift,
| and then after the company goes under (maybe not due to thier
| poor leadership), you read about their huge successes there!
| Much win.
| steveBK123 wrote:
| This rhymes with the guys I am currently observing.
|
| Former cloud data lake enterprise architecture & agile
| development experts as well.
|
| True Renaissance Men.
| happytoexplain wrote:
| (Note: This is an American take, and uses software jobs as the
| primary example, but a lot of this applies to other jobs)
|
| Yes, well said - with one caveat: "Money and social status" is
| subtly but crucially different from "livelihood". You correctly
| identify the group of people whose _lives_ are affected, but
| lump those people along with CEOs and AI companies under the
| umbrella of "money and social status" in your summarization,
| which maybe undersells the role of the masses in this equation.
|
| The software job - traditionally one of the few good career
| options remaining for a large chunk of Americans - is falling.
| There are many different reasons, and AI, while not the
| apocalypse, is a small but crucial part of it. We need to get
| over the illusion that a large piece of that fall consists of
| wildly luxurious incomes reducing to simply cushy incomes -
| "boo hoo", we say, sarcastically. But the majority of software
| folks are going from "comfortable" to "unhappy but livable",
| while some are going from "livable" to "not livable", while
| others are no longer employed at all. There were already too
| many people across the job spectrum in these buckets, and
| throwing another gigantic chunk of citizens in there is going
| to eventually cause big, bad things to happen.
|
| We need to start giving a shit about our citizens, and part of
| that is avoiding the implication that just because something
| disruptive is _inevitable_ , doesn't mean the affect isn't
| devastating and we should just _do absolutely nothing_ about
| the situation. Another part of that is avoiding the implication
| that the average person can just _successfully change careers_
| without enormous suffering. We can ease, assist, _REGULATE_
| (which the party in power would like to make illegal), etc. It
| 's important to understand that none of that means "stopping"
| AI or something ridiculous like that.
|
| We need to start giving a shit about our citizens.
|
| A third time: We need to start giving a shit about our
| citizens.
|
| And sorry, most of this was not directed personally at you.
| Just the first note about your wording.
| skeeter2020 wrote:
| Why don't Tech CEOs and CTOs see how AI is going to "disrupt"
| their jobs? If anyone can write code, why will I hire your
| company to create the software I use?
|
| I also see the non-development jobs as much more in peril from
| AI; I can go generate marketing copy, HR policies, and project
| plans of comparable (or better!) quality today.
| mattgreenrocks wrote:
| Because it's meant to be a psyop more than a reflection of
| reality.
| zozbot234 wrote:
| AI is glorified autocomplete. Look at what happens when AI
| tries its hand at writing legal briefs, and you'll understand
| why it cannot possibly replace software developers.
| lincoln20xx wrote:
| That may be true. But it's pretty great at generating lines
| of questioning for cross-examination.
| epicureanideal wrote:
| I wonder to what extent a non LLM system with access to the
| same original corpus of text would do, with some simple
| similarity search feature across the corpus?
| fleebee wrote:
| > There has been no shortage of evidence to support these claims.
|
| One would usually show some kind of evidence after making such a
| statement. Claims from CEOs of AI companies don't count.
| Loic wrote:
| Take everything Cal Newport is talking about with a large grain
| of salt.
|
| I don't know a single person with a bit of seniority, using
| Claude Code, who wants to go back to any IDE from 5 years ago.
| jeffbee wrote:
| Yep. I mentally inserted the subtitle "... especially not Cal
| Newport"
| impish9208 wrote:
| You do know he's a CS professor, right? But he's not on the
| cutting edge of agentic blah-blah AI, so maybe it doesn't
| hold as much water these days.
| jeffbee wrote:
| Being a CS professor informs a person in no way about
| developer productivity.
| ipaddr wrote:
| That's a narrow category.
|
| If you stated a senior who tried Claude Code and is still using
| an IDE that number is much higher.
|
| Still using Claude and wants to go back to an IDE.. why
| wouldn't they go back... why keep using Claude Code and pining
| for a IDE. That's a small small group.
| aggie wrote:
| The value of AI is easy to see personally, concretely. But there
| is always a gap between concrete value in your hands and how that
| plays out in larger systems. The ability to work remotely could
| intuitively project to outsourcing of almost all knowledge work
| to cheaper labor markets, and yet that has only happened at the
| margins. The world is complex and complicated, reserve a measure
| of doubt.
| dmartinez wrote:
| This is a great point.
|
| In-person work has higher bandwidth and lower latency than
| remote work, so for certain roles it makes sense you wouldn't
| want to farm it out to remote workers. The quality of the work
| can degrade in subtle ways that some people find hard to work
| with.
|
| Similarly, handing a task to a human versus an LLM probably
| comes with a context penalty that's hard to reason about
| upfront. You basically make your best guess at what kind of
| system prompt an LLM needs to do a task, as well as the ongoing
| context stream. But these are still relatively static unless
| you have some complex evaluation pipeline that can improve the
| context in production very quickly.
|
| So I think human workers will probably be able to find new
| context much faster when tasks change, at least for the time
| being. Customer service seems to be the frontline example. Many
| customer service tasks can be handled by an LLM, but there are
| probably lots of edge cases at the margins where a human simply
| outperforms because they can gather context faster. This is my
| best guess as to why Klarna reversed their decision to go all-
| in on LLMs earlier this year.
| throwaway20174 wrote:
| AI more of a force muliplier than a replacement. If you rated
| programmers from 0 to 100. AI can take you from 0 to 80, but
| can't take you from 98 to 99.
|
| I'd love to record these AI CEOs statements about what's going to
| happen in the next 24 months and look back at that time -- see
| how "transformed" the world is then.
| amradio1989 wrote:
| I'm stating the obvious, but these things tend to go either
| way. We either grossly overestimate the impact, or grossly
| underestimate it.
|
| In the case of the internet, it ended up going both ways. We
| overestimated it in the near term and underestimated its impact
| in the long term.
|
| They could very well be right. I don't think they are. But I've
| also never seen anything that can scale quite like AI.
| SoftTalker wrote:
| My guess is more if the same (i.e. mostly crap), but faster.
|
| We still create software largely the same as we did in the
| 1980s. Developers sitting at keyboards writing code, line by
| line. This despite decades of research and countless attempts
| at "expert systems", "software through pictures" and endless
| attempts at generating code from various types of models or
| flowcharts or with different development methodologies or
| management.
|
| LLMs are like scaffolding on steroids, but aren't fundamentally
| transforming the process. Developers still need the mental
| model of what they are building and need to be able to verify
| that they have actually built it.
| mattgreenrocks wrote:
| Fully self-driving cars have been just 2 years away for what,
| 10 years now?
| d4mi3n wrote:
| I'm of the opinion that LLM assisted coding tools have a few
| general effects in the domain of software development:
|
| 1. Increases in productivity for experienced software engineers.
|
| 2. Raised industry expectations around productivity of individual
| software engineers.
|
| 3. Lowered ratio of human engineers to other parters in the
| development process (customers, stakeholders, etc.)
|
| I've found the net result is an environment where we can churn
| out code easily, but producing the right code becomes harder.
| Fewer eyes on the production of a product means most of the
| validation later in the development process.
|
| How much an issue this is remains to be seen. Engineers will
| presumably have more time to review and debug things. Debugging
| will be easier. That said, I have no idea if any of that makes up
| for retroactively realizing design assumptions were bad or that
| some subtle constraints about your software were violated.
| meindnoch wrote:
| I'm running about a dozen sockpuppet Twitter accounts that post
| LLM-generated gaslighting posts about software engineering no
| longer being a viable career choice. I'd recommend other senior
| engineers do the same - it only takes about 15 minutes each day.
| ducttapecrown wrote:
| How did you pick the number "about a dozen"? Probably just LLM
| budget constraint I guess.
| 20k wrote:
| The key is to look at the long term structural changes the
| industry is going through, and whether or not AI helps, or
| hinders that goal
|
| In general, the industry has been making huge efforts to push
| errors from _runtime_ , to compile time. If you imagine points
| where we can catch errors being laid out from left to right, we
| have the following:
|
| Caught by: Compiler -> code review -> tests -> runtime checks ->
| 'caught' in prod
|
| The industry is trying to push errors _leftwards_. Rust, heavier
| review, safety in general - its all about cutting down costs by
| eliminating expensive errors earlier in the production chain.
| Every industry does this, its much less costly to catch a
| defective oxygen mask in the factory, than when it sets a plane
| on fire. Its also better to catch a defective component in the
| design phase, than when you 're doing tests on it
|
| AI is all about trying to push these errors _rightwards_. The
| only way that it can save in engineer time is if it goes through
| inadequate testing, validation, and review. 90% of the complexity
| of programming is building a mental model of what you 're doing,
| and ensuring that it meets the spec of what you want to do. A lot
| of that work is currently pure mental work with no physical
| component - we try and offload it increasingly to compilers in
| safe languages, and add tests and review to minimise the
| slippage. But even in a safe language, it still requires a very
| high amount of mental work to be done to make sure that
| everything is correct. Tests and review are a stop gap to try and
| cover the fallibility of the human brain
|
| So if you chop down on that critical mental work by using
| something probabilistically correct, you're introducing errors
| that _will_ be more costly down the line. It 'll be fine in the
| short term, but in the long term it'll cost you more money.
| That's the primary reason why I don't think AI will catch on -
| its short termist thinking from people who don't understand what
| makes software complex to build, or how to actually produce
| software that's cheap in the long term. Its also exactly the same
| reason that Boeing is getting its ass absolutely handed to it in
| the aviation world. Use AI if you want to go bankrupt in 5 years
| but be rich now
| WaxProlix wrote:
| That's true up to a certain threshold on 'probabilistically
| correct', right? At a certain number of 9s, it's fine. And
| increasingly I use AI to help ask me questions, refine my
| understanding of problem spaces, do deep research on existing
| patterns or trends in a space and then use the results as
| context to have a planning session, which provides context for
| architecture, etc.
|
| So, I don't know that the tools are inherently rightward-
| pushing
| 20k wrote:
| The problem is, given the inherent limitations of natural
| language as a format to feed to an AI, it can never have
| enough information to be able to solve your problem
| adequately. Often the constraints of what you're trying to
| solve only crop up during the process of trying to solve the
| problem itself, as it was unclear that they even existed
| beforehand
|
| An AI tool that could have a precise enough specification fed
| into it to produce the result that you wanted with no errors,
| would be a programming language
|
| I don't disagree at all that AI can be helpful, but there's a
| huge difference between using it as a research tool (which is
| very valid), and the folks who are trying to use it to
| replace programmers en masse. The latter is what's driving
| the bubble, not the former
| B56b wrote:
| AI code reliability is nowhere near any number of 9s
| bugglebeetle wrote:
| I'm not sure this follows as SOTA LLMs are pretty good at
| writing Rust, so wouldn't this also make it easier for
| codebases to move leftward in your analogy? For example, I was
| resistant to use Rust for a lot of things because a). The
| community is somewhat annoying and pedantic, even by software
| engineering standards b). The overhead in getting colleagues up
| to speed on Rust code was too much of a time suck. LLMs solve
| both those problems and we're now migrating lots of stuff to
| Rust, my colleagues can ask lots of questions (of Google Gemini
| Pro 2.5), without burdening anyone or being met with disdain,
| and seem generally more curious and positive about these
| moves/Rust overall.
| jjk166 wrote:
| > It'll be fine in the short term, but in the long term it'll
| cost you more money. That's the primary reason why I don't
| think AI will catch on - its short termist thinking from people
| who don't understand what makes software complex to build, or
| how to actually produce software that's cheap in the long term.
| Its also exactly the same reason that Boeing is getting its ass
| absolutely handed to it in the aviation world. Use AI if you
| want to go bankrupt in 5 years but be rich now
|
| I think your analysis is sound from a technical perspective,
| but your closing statement is why AI is going to be mass
| adopted. The people who want to be rich now and don't care
| about what will happen in 5 years have been calling the shots
| for a very long time now, and as much as we technical folks
| insist this can't possibly keep going on forever, it's probably
| not going to stop sometime soon.
| prairieroadent wrote:
| I'm coming to the realization that unsustainable behavior can
| continue for a long time... in our context, for generations
| pas wrote:
| The market can remain irrational longer than you can remain
| solvent.
| nathan_douglas wrote:
| Things can stay stupid longer than you can stay sane.
| lloeki wrote:
| > its short termist thinking from people who don't understand
| what makes software complex to build
|
| Ironically you don't need AI to see this pattern. Maybe AI
| makes it a little bit more obvious who's thinking long term and
| who's not (both at the top and in the trenches)
|
| > Use AI if you want to go bankrupt in 5 years but be rich now
|
| Or, as some would put it "Use AI if you want to be rich now,
| exit, and have someone else go bankrupt in 5 years"
| contextfree wrote:
| In the broader context, you could look further left:
|
| Conception -> design -> compiler -> code review ...
|
| If AI tools allow for better rapid prototyping, they could help
| catch "errors" in the conception and design phases. I don't
| know how useful this actually is, though.
| 20k wrote:
| One of the problems with using AI for prototyping (or just in
| general), is that the act of creating the prototype is what's
| valuable, not the prototype itself. You learn lessons in
| trying to build it that you use to build the real product.
| Using the AI to skip the learning step and produce the
| prototype directly would be missing the point of prototyping
| at all
| amilios wrote:
| Sometimes you need to just pump out an MVP and start
| iterating. AI can exponentially speed this up in my
| experience.
| contextfree wrote:
| That's definitely an issue and I've gotten burnt by similar
| problems when using AI to help navigate and find things in
| codebases, where I've used it to read and understand code
| for me, with seemingly miraculous results at first, but
| ended up wishing I'd read more code "manually" myself, as
| my lack of understanding led to wasting more time on net
| than I saved. I still feel like it should be possible to
| find some kind of a balance, but it's tricky.
| marcosdumay wrote:
| > That's the primary reason why I don't think AI will catch on
|
| It's almost enraging that with the hype around LLMs, the
| development of real automatic programming AI seems to have
| halted.
| Nicook wrote:
| >The industry is trying to push errors leftwards.
|
| Is this true? Most software devs would like to. But I think
| business is more interested in spee which pushes errors to the
| right. Which seems to be more profitable in most software. Even
| stuff thats been around for a decade(s).
| pas wrote:
| nah, in general there's a serious industry-wide push for
| this. software testing is changing (involve QAs early so they
| can help with the spec so when they get the software they
| know what to test against), agile is about delivering small
| valuable parts of the product as soon as possible, VC
| investing (lean startups!) is about testing business ideas as
| soon as possible, etc.
|
| it's all part of the shift left ideology. (same with
| security, you cannot really add it later, same with GDPR and
| other data protection stuff, you cannot track consent for
| various data processing purposes after you already have a lot
| of users onboarded - unless you want to do the sneaky very
| not nice "ToS updated, pay or die, kthxbai" thing [which is
| what Meta did], etc.)
|
| ... of course this usually means that many times people want
| to go from the "barely idea as a Figma proto" to "mature
| product maintained by distributed high-velocity teams"
| without realizing that there are trade-offs.
|
| shift left is makes good business and engineering sense and
| all, as it allows you to focus on the things that work, but
| it requires more iterations to go from that to something
| mature.
| 827a wrote:
| I disagree entirely, and I can convince you I'm right with one
| sentence: More lines of JS/TS are written by AI than lines of
| Rust are written at all. We don't have the data to assert this
| as true, but I think the vast majority of people would agree
| with that statement.
|
| This statement being true disproves the statement "the industry
| has been making huge efforts to push errors from runtime, to
| compile time." The industry is not a monolith. Different actors
| have different, individualized goals.
| pas wrote:
| it's absolutely not a problem that people are writing more
| JS/TS than Rust.
|
| _if_ that Rust is for decades and the JS /TS gets thrown out
| in 1 year.
|
| there's a lot of shitty C being written still around the
| world yet the Rust that goes into the kernel has real value
| long term.
|
| there's an adoption cycle. Rust is probably already well over
| the hype peak, and now it's slowly climbing upward to its
| "plateau of productivity".
|
| (and I would argue that yes there are pretty good things
| happening nowadays in the industry. for many domains
| efficient and safe libraries, frameworks, and platforms are
| getting to be the norm. for example see how Blender became a
| success story. how deterministic testing is getting adopted
| for distributed databases.)
| raincole wrote:
| And I have a very hard time understanding why AI is "pushing
| the errors to the right".
|
| > Compiler -> code review -> tests -> runtime checks ->
| 'caught' in prod
|
| With AI we still compile the code.
|
| We still do code review.
|
| We still run tests (before code review, obviously; don't know
| why it's listed like this).
|
| We still do QA at runtime.
|
| I feel like anti-AI people are those one who actually treat
| AI as magic, not the AI users. AI doesn't magically prevent
| you from doing the things that helped you in pre-AI era.
| Balinares wrote:
| No, but if a shop added overnight 5 fledgling juniors for
| each current employee on the project, not only would the
| delivery not be sped up on account of Brooks's law, but the
| stack would soon tank under the weight of its own issues.
| So outside of such situations as hilarious consultancy
| disasters, no one did that.
|
| Now with AI they do.
| dubbel wrote:
| You are looking at LLMs for code generation exclusively, but
| that is not the only application within software engineering.
|
| In my company some people are using LLMs to generate some of
| their code, but more are using them to get a first code review,
| before requesting a review by their colleagues.
|
| This helps getting the easy/nitpicky stuff out of the way and
| thereby often saves us one feedback+fix cycle.
|
| Examples would be "you changed this unit test, but didn't
| update the unit test name", "you changed this function but not
| the doc string", or "if you reorder these if statements you can
| avoid deep nesting". Nothing groundbreaking, but nice things.
|
| We still review like we did before, but can often focus a
| little more on the "what" instead of the "how".
|
| In this application, the LLM is kind of like a linter with
| fuzzy rules. We didn't stop reviewing code just because many
| languages come with standard formatters nowadays, either.
|
| While the whole code generation aspect of AI is all the rage
| right now (and to quote the article):
|
| > Focus on tangible changes in areas that you care about that
| really do seem connected to AI
| 20k wrote:
| So while I don't disagree with you at all, in terms of AI
| being a bubble, none of that is why the tech is being so
| hyped up. The current speculative hype push is being driven
| by two factors:
|
| 1. The promise that AI will replace most if not all
| developers
|
| 2. Alternatively, that AI will turn every developer into a
| 10-100x developer
|
| My personal opinion is that it'll end up being one of many
| tools that's situationally useful, eg you're 100% right in
| that having it as an additional code review step is a great
| idea. But the amount of money being pumped into the industry
| isn't enough to sustain mild use cases like that and that
| isn't why the tech is being pushed. The trillions of dollars
| being dumped into improving clang tidy isn't sustainable if
| that's the end use case
| giantrobot wrote:
| > 1. The promise that AI will replace most if not all
| developers 2. Alternatively, that AI will turn every
| developer into a 10-100x developer
|
| The AI hype train is promising to deliver the 20 year old
| developer with 30 years of experience that a company can
| pay $10 an hour.
| darksaints wrote:
| This has been a huge frustration for me, but the wild thing is
| that we've built up so many tools over time that help humans
| only for AI coding tools to wild west it and not use them. The
| best AI coding tools will read docs websites, terminal error
| messages, write/run tests, etc. But we have so many better
| tools that none of them seem to use:
|
| * profilers
|
| * debuggers
|
| * linters
|
| * static analyzers
|
| * language server protocol
|
| * wire protocol analyzers
|
| * decompilers
|
| * call graph analyzers
|
| * database structure crawlers
|
| In the absence of models that can do perfect oneshot software
| engineering, we're gonna have to fall back on well-integrated
| tool usage, and nobody seems to do that well yet.
| 20k wrote:
| I think a lot of these use cases for AI are incidental
| byproducts of the actual goal, which is to replace software
| developers. They're trying to salvage some kind of utility.
| Because I agree that the AI tools in use are marginal
| improvements, or downgrades in a lot of cases
|
| I've heard people say they use AI agents to set up a new
| project with git. Just use tortoisegit or something, its free
| and takes one click - its just using AI for the sake of it
| aerhardt wrote:
| Exabytes of code are being written in Python and JS though... I
| don't think that fits with your narrative that everything is
| being pushed to compile-time. C#, Java and Go remain popular
| sure but have they grown that much relative to other languages?
| Rust is being adopted primarily in projects that used to be in
| C or C++ if I'm not mistaken.
| 20k wrote:
| Those languages have been going through exactly the same
| evolution though, like the JS -> typescript migration is one
| of the most direct practical examples of this imo
| abalashov wrote:
| This is the best and most enlightening take I've heard in a
| good while.
|
| I have articulated this to friends and colleagues who are on
| the LLM hype train somewhat differently, in terms of the
| unwieldiness of accumulated errors and entropy,
| disproportionate human bottlenecks when you do have to engage
| with the code but didn't write any of it and don't understand
| it, etc.
|
| However, your formulation really ties a lot of this together
| better. Thanks!
| bwfan123 wrote:
| thanks for articulating so nicely what needs to be said in this
| debate.
|
| Pushing errors leftward vs rightwards is such a nice metaphor,
| not to mention the metaphor on mental models. Also, your
| comment on why natural language is unable to describe the
| problem adequately (later in this thread), since sometimes
| constraints are discovered during the solution process, and
| otherwise, and if problems could be described adequately, thats
| what we call a programming language is very nice - ie, for
| natural language to adequately describe a problem, that becomes
| a formal language.
|
| Only experienced engineers who have been through failed
| projects will understand what you are saying, and the rest of
| those in the grip of the ai-mania will come to terms with it
| soon.
| dimal wrote:
| Vibe coding pushes errors rightward, but using AI to speed up
| typing or summarizing documentation doesn't. Vibe coding will
| fail, but that doesn't mean using AI to code will fail. You're
| looking at one (admittedly stupid) use case and generalizing
| too hastily.
|
| If I have an LLM fix a bug where it gets the feedback from the
| type checker, linter and tests in realtime, no errors were
| pushed rightward.
|
| It's not a free lunch though. I still have to refactor
| afterwards or else I'll be adding tech debt. To do that, I need
| to have an accurate mental model of the problem. I think this
| is where most people will go wrong. Most people have a mindset
| of "if it compiles and works, it ships." This will lead to a
| tangled mess.
|
| Basically, if people treat AI as a silver bullet for dealing
| with complexity, they're going to have a bad time. There still
| is no silver bullet.
| JimDabell wrote:
| Recurse Center made a good observation:
|
| > I expected to find vastly differing views of what future
| developments might look like, but I was surprised at just how
| much our alums differed in their assessment of where things are
| _today_.
|
| > We found at least three factors that help explain this
| discrepancy. First was the duration, depth, and recency of
| experience with LLMs; the less people had worked with them and
| the longer ago they had done so, the more likely they were to see
| little value in them (to be clear, "long ago" here may mean a
| matter of just a few months). But this certainly didn't explain
| _all_ of the discrepancy: The second factor was the _type of
| programming work people cared about_. By this we mean things like
| the ergonomics of your language, whether the task you're doing is
| represented in model training data, and the amount of boilerplate
| involved. Programmers working on web apps, data visualization,
| and scripts in Python, TypeScript, and Go were much more likely
| to see significant value in LLMs, while others doing systems
| programming in C, working on carbon capture, or doing novel ML
| research were less likely to find them helpful. The third factor
| was whether people were doing smaller, more greenfield work
| (either alone or on small teams), or on large existing codebases
| (especially at large organizations). People were much more likely
| to see utility in today's models for the former than the latter.
|
| -- https://www.recurse.com/blog/191-developing-our-position-
| on-...
| softwaredoug wrote:
| "Carbon capture" seems oddly specific?
| pchristensen wrote:
| My guess is that's a specific example of e.g. novel
| scientific modeling.
| 0x500x79 wrote:
| There is a great article floating around on the economics of AI
| and how parasitic the current market is between the Fab Five.
|
| We are 27-ish months since the claim that all software engineers
| would be replaced within six months by some of these CEOs. It is
| their job to analyze the market and determine what the next big
| thing is, but they can be wrong - no one has a crystal ball here.
|
| The difficulty for me is how disconnected a lot of the takes are
| (or even flat out manipulative) that are being pushed out. I am
| an early adopter of AI tools. I utilize them on a day-to-day
| basis, but there is no way that I see AI taking SW jobs right
| now.
|
| You have others claiming that these tools will just get
| exponentially better now, time will tell, but as of right now
| there is still too much value in human coders any anyone that is
| actively pushing for replacing SWE with "Agents" is either
| betting big on the future (that is unproven) or attempting to
| entice/manipulate the larger market.
| wslh wrote:
| I think part of the solution is to start discussing the
| specific limitations of LLMs, rather than speaking broadly
| about AI/AGI. For example, many people assume these models can
| understand arbitrarily long inputs, but LLMs have strict token
| limits. Even when large inputs fit within the model's context
| window, it may not reason effectively over the entire content.
| This happens because the model's attention is spread across all
| tokens, and its ability to maintain coherence or focus can
| degrade with length. These constraints along with hardware
| limitations like those in NPUs are not always obvious to
| everyday users.
| 0x500x79 wrote:
| I agree, but unfortunately it falls flat IME. The hype is too
| strong and being pushed by the Fab Five that is causing an
| unbearable wall to these conversations.
|
| I have these conversations on a day-to-day basis and you are
| labeled as a hater or stupid because XYZ CEO says that AI
| should be in everything/making things 100x easier.
|
| There is a constant stream of "What if we use an LLM/AI for
| this?" even when it's a terrible tool for the job.
| marcosdumay wrote:
| > You have others claiming that these tools will just get
| exponentially better now
|
| Most of those same people are also claiming that the last
| iteration of LLMs are too smart and that the previous ones
| worked better for agent (agentic?) programming...
| fusionadvocate wrote:
| AI research is like the topic of sex during adolescence: of
| everyone say they are doing it, few are; and the few that are in
| fact doing it are probably doing it wrong.
| okokwhatever wrote:
| I'm doing the work of 3 dudes alone (dev, qa, devops). My
| delivery is 100% faster and my development practice allows me to
| reduce the bugs dramatically.
|
| Maybe my stack is easier or the product is not too complex but if
| I take my own experience as a truth, my truth, (we) Engineers are
| going to suffer for a long time.
|
| Everybody will have different experiences but my guess not all
| developers are working in frontier projects so their jobs will be
| the first to suffer the change. At least for me this is going to
| happen.
| catigula wrote:
| Solo developers were already multiple times more productive
| than their coworkers and it never made much difference, even in
| compensation.
| johnwheeler wrote:
| I really blame the Sam Altman hype machine for all of this
| dystopian nonsense. He really is like a Ryan holiday you can't
| trust anything he says. He's the one who started all this
| "employees are going away" stuff with this $20,000 AI employee.
| that's not when he started it, he started it long before that
| with all his basic income bullshit.
| wussboy wrote:
| I don't think you can become a talented enough software developer
| to benefit from using AI by using AI. Google Maps causes us to
| lose the ability to navigate without it. I would not be surprised
| in the slightest if the same is true with AI.
|
| So. A little boost now. But at the risk of not knowing how to get
| where you're going unless someone is holding your hand.
|
| And if that's the case, how can we possibly get to where we've
| never been before?
| upquacker wrote:
| This is a hippie saying you don't know anything about communism.
|
| We know there's a lot of lying, fakery, dishonest, and hype in
| AI.
|
| AI is communists playing the Wizard in The Wizard of Oz.
|
| It's about power, intimidation, and psychology.
| daxfohl wrote:
| Wouldn't the be reacting differently if the cost and speed of
| development in the economy's highest ROI industries was really
| expected to improve by an OOM in the near future?
| jedberg wrote:
| The people who are saying AI will replace everyone are people who
| don't actively deploy code anymore. People like CEOs and VPs.
|
| People who are actively deploying code are well aware of the
| limitations of AI.
|
| A good prompt with some custom context will get you maybe 80% of
| the way there. Then iterating with the AI will get you about 90%
| of the way, assuming you're a senior engineer with enough
| experience to know what to ask. But you will still need to do
| some work at the end to get it over the line.
|
| And then you end up with code that works but is definitely not
| optimal.
| phtrivier wrote:
| Fred Brooks told us to "plan to throw one version away, because
| you will."
|
| What he missed is that the one version that is not thrown away
| will have to be maintained pretty much for ever.
|
| (Can we blame him for not seeing SaaS coming ?)
|
| What if the real value of AI was at the two sides of this:
|
| * to very quickly built the throwaway version that is just used
| during demos, to gather feedback from potential customers, and
| see where things break ?
|
| That can probably be a speed-up of 10x, or 100x, and an
| incredible ROI if you avoid building a "full" version that's
| useless
|
| * then you create the "proper" system the "old" way, using AI
| as an autocomplete on steroid (and maybe get 1.5x, 2x, speedup,
| etc...)
|
| * then you use LLMs to do the things you would not do anyway
| for lack of time (testing, docs, etc...) Here the speedup is
| infinite if you did not do it, and it had some value.
|
| But the power that be will want you to start working on the
| next feature, by this time...
|
| * I don't know about how LLMs would help to fix bugs
|
| So basically, two codebase "lanes", evolving in parallel, one
| where the AI / human ratio is 90/10, one where it's maybe 30/70
| ?
|
| AI for fast accretion, human for weathering ?
| th0ma5 wrote:
| Maybe but anytime someone keeps doing mental gymnastics and
| theorizing that there are new forces at play, something comes
| out and says no, it was something very straightforward.
| Hammock Driven Development describes a zen internalized way
| an expert does exactly as you describe but it is nicer you
| don't have to pay per token. To be clear, I think this all
| falls again under the rubber duck umbrella which is fine, but
| seemingly impossible to design a controlled study for?
| malshe wrote:
| We have a similar situation in the academia specifically for
| teaching. Many faculty members are stressed because they fear the
| admin will start replacing them with AI. Anyone who has done any
| teaching in the classroom knows that we are nowhere close to that
| point. But the admin loves to start cost cutting at the expense
| of education quality.
| the_arun wrote:
| There is a lot of confusion & hype about AI. AI is not just use
| of LLMs. LLMs could help us with GenAI use cases. Not everything
| is GenAI. Main reason for confusion IMHO is - GenAI exposed lot
| of non-tech people to AI and they don't have a full picture.
| vrotaru wrote:
| So what is your pick?
|
| * AI is the next electric screwdriver * AI is THE steam engine.
|
| My pick is that the AI is not THE steam engine.
| jtrn wrote:
| I got triggered enough to write an angry rebuttal.
|
| The structure is familiar: first, a summary of the breathless
| hype that AI will change everything. Then, a collection of
| counterpoints suggesting it's all overblown. The grand
| conclusion? That everything is confusing, nobody knows anything
| for sure, and the wisest stance is to take it all with a "large
| grain of salt."
|
| The truth is, we know an immense amount about AI, and pretending
| otherwise is not a sign of wisdom, but an excuse to disengage
| from the most important technological shift of our time.
|
| First, a note on the sloppy analogy of the "economic sacrificial
| lamb," referring to those first disrupted by AI. This analogy is
| not just melodramatic; it's incorrect. Developers aren't being
| passively offered up to some AI deity. They are the first to feel
| the effects because they are the ones building, implementing, and
| integrating the technology. They are not the lamb; they are the
| blacksmiths forging a new kind of hammer and, in the process,
| figuring out how it changes their own workshop. Their proximity
| to the change is a consequence of their agency, not their
| victimhood.
|
| The most frustrating claim, however, is the idea that "we don't
| yet know anything for sure." To anyone working with or studying
| these systems, this is patently absurd. While the long-term
| societal outcome is uncertain, we have a vast and growing body of
| practical, empirical knowledge about how these models work.
|
| We know, for example, that providing specific context and
| reference material dramatically improves answer quality and
| reduces hallucinations--the entire principle behind the now-
| dominant RAG (Retrieval-Augmented Generation) architecture. We
| know about scaling laws, prompt engineering best practices, and
| fine-tuning methodologies. We have gigabytes of data on what
| tasks AI excels at (boilerplate code, synthesis, translation) and
| where it fails (complex reasoning, factual accuracy, planning).
| To dismiss this mountain of hard-won engineering knowledge is to
| be aggressively ignorant.
|
| Then there is the Double Standard. Cal Newport has built his
| brand as a productivity expert, offering systems for "deep work"
| and focus. Yet, as any psychologist or organizational behavior
| expert can attest, human productivity is a field where "moving
| the needle predictably" is a notoriously difficult, almost
| impossible task. It's a domain riddled with individual
| differences, cultural nuances, and contradictory findings. For a
| guru from a field that lacks hard empirical certainty to demand
| it from the nascent field of AI exposes a glaring double
| standard. He is holding AI to a standard of proof that the
| behavioral sciences--the foundation of his own work--have never
| been able to meet. It's a rhetorical move that positions him as a
| wise skeptic, but to me, it comes off as hypocrisy.
|
| And then the final, tired advice: be skeptical. Take it with a
| grain of salt. This isn't insight; it's a cliche that has been
| the default take for every technological shift of the last thirty
| years. It's safe, lazy, and frankly, boring. We don't need more
| generic skepticism. We need engaged, critical, hands-on analysis.
| The interesting work isn't in declaring the future unknowable
| from an armchair by has-been intellectuals that are unable or
| unwilling to keep up with recent developments.
| no_wizard wrote:
| >The truth is, we know an immense amount about AI
|
| We (as researchers and developers in the field) know alot about
| how its technically implemented, like building models, making
| improvements etc. These can be quantified and tracked.
|
| The heart of the matter is this:
|
| >societal outcome is uncertain
|
| I think all speculation around AI is heavily weighted about
| _that_ as opposed to _what do we know about AI from a technical
| perspective?_ which isn 't even usually part of the discourse,
| unless we're talking about AI safety, which the bad actors try
| to pretend the technology isn't built in a well known way or
| can have predictable results etc.
|
| A good chunk of the problem (certainly more than half) is that
| you have bad actors that need to sell the world on AI, and you
| have actual technical implementors who really know alot about
| these systems but are most often employed by folks who benefit
| from gatekeeping the technology and refuse any attempts at
| oversight, often claiming we _don 't_ know alot about how these
| systems work while simultaneously employing people who
| definitely know how these systems work.
|
| The industry has done this to itself, by making false claims
| and talking out of both sides of their mouth, while the actual
| technically skilled folks are for various reasons, largely
| stuck in the middle without much room at the broader discussion
| table
| jtrn wrote:
| An observation mostly perfectly explained by failure to
| differentiate scientists from journalists.
|
| And what do you mean "done this to itself". What is this?
| jtrn wrote:
| And you do realize I was specifically contrasting how much
| and how we know about AI versus how much we know, for
| instance, in the field of productivity psychology. In
| addition to how idiotic it is to say we know nothing.
|
| If we know nothing about AI, then by the same standard, we
| know nothing about anything.
|
| Or let me put it simply to you. If we had a random average
| firm, and we either gave them a copy of Newport's book on
| productivity or a subscription to Gemini, with all we surely
| must KNOW regarding productivity, the book version of the
| firm would become massively more productive, no?
| ninetyninenine wrote:
| You used AI to write this.
| jtrn wrote:
| No, I didn't. I am getting tired of the accusations every
| time I write something I believe is thoughtful. I challenge
| every person who throws this at me to a live debate to see if
| it's me thinking these thoughts or just an AI. If you
| decline, I assume it's because you are so limited that you
| can't imagine anyone thinking for themselves, because you
| project your own inabilities onto others.
| ninetyninenine wrote:
| It is thoughtful and well written. But it's done by AI.
| Nothing wrong with that.
| ceejayoz wrote:
| You, a few hours ago: "The LLMs are displaying output and
| behavior that is consistent with people who are
| conscious." -
| https://news.ycombinator.com/item?id=44671061
|
| You, now: "I can tell you didn't write that. AI did it!"
|
| You really ought to make up your mind.
| ninetyninenine wrote:
| It is displaying output consistent with consciousness.
| Doesn't mean it is conscious. But the textual output is
| indistinguishable. My statements HAVE not changed, and
| remain true.
|
| >You, now: "I can tell you didn't write that. AI did it!"
|
| It's more of a parody of what he's saying. He's making
| claims yet he can't even prove if what he wrote is AI.
| einrealist wrote:
| It's hard "to tune out" from the topic when investments in LLM
| technology surpasses revenues of nation states, and when US
| policy is not trying to prevent harm to society, but making it
| more likely. By 'harm', I don't mean some 'rogue AI' sci-fi
| scenario. I mean a financial time bomb that far exceeds the 2008
| subprime mortgage crisis.
| StarterPro wrote:
| For text LLMs, on a basic level, isn't it just aggregating the
| percentage chance of a specific word order based on the
| topic/genre?
|
| I've just started looking into them, but it feels like A BUNCH of
| stats hidden beneath a layer of if/else statements.
|
| It only seems to work given an unlimited amount of money being
| thrown at it. Which would be possible if it were nationalized,
| but they're too greedy for that to happen.
| ike2792 wrote:
| I think the first set of quotes are from people trying to sell
| something, while the second set are based on real data and people
| who have actually worked with AI. I'm a engineering manager over
| some infrastructure teams and we've tried to use it for network
| monitoring without any success. It seems like it would be handy;
| who doesn't want to query the state of your infra in natural
| language? The problem is it gives non-deterministic results and
| occasionally just makes things up. All the developers I know who
| use Github Copilot say it's very buggy and often makes coding
| take more time if they use it for any autogeneration.
| rudderdev wrote:
| Love the balance this post shows in supporting and dismissing ai
| impact, unlike the other post on hn today ;)
| eddythompson80 wrote:
| Why was the title changed again? The article has the title "No
| One Knows Anything About AI". The post started here with that
| title, then changed to "Two narratives about AI". Why
| editorialize the title?
| throwaway328 wrote:
| Yeah, seriously, what is this about? Dang, etc? Anyone?
| afro88 wrote:
| Sigh, there's that study again, quoted without any "early 2025"
| context. In early 2025 AI wasn't very effective, especially when
| used by engineers that didn't have an intuition for what to and
| what not to use it for.
|
| It's different in mid 2025. The next quote is simonw in mid 2025
| saying don't quit engineering. Right now it's as if we're
| carpenters and the buzz saw was just invented. Shouldn't that be
| in the first group of quotes?
|
| If you look at his set of quotes through another lens it's
| saying: Software engineering is changing due to AI. AI wasn't
| great in early 2025, but recently got a lot better. Some CEOs and
| plenty of journos are giddy at the possibility of layoffs.
| Layoffs aren't actually happening though.
|
| That's a far cry from "no one knows anything about AI".
| xnx wrote:
| > No One Knows Anything About AI
|
| Projection
| senko wrote:
| The narratives are opposite extremes on spectrum of opinions and
| anecdotal.
|
| I find it more useful to split the narratives into "AI hype" and
| "pragmatic AI": https://senkorasic.com/articles/pragmatic-vs-
| hype-ai
|
| TLDR: The technology is real. A lot of companies are working on
| it and evaluating how to integrate it into their products or
| processes. Many people use ChatGPT and other tools daily for a
| wide variety of tasks.
|
| At the same time, there's an enormous amount of hype. Some of it
| comes from a poor understanding of the technology: not everyone
| can be an AI expert. But a lot of it is companies adopting AI in
| name only to ride the hype wave. We're being bombarded with
| claims about the imminent arrival of "Artificial General
| Intelligence" (AGI) or even "Artificial Superintelligence" (ASI).
| AI companies tell us to "stop hiring humans" or announce plans to
| lay off hundreds or thousands of employees as they're replaced by
| AI agents.
|
| This is AI being used for marketing, not productivity. It doesn't
| even require the tech itself--the story is what sells, and the
| more controversial or hyped, the better.
| metalrain wrote:
| I feel like AI is great tool to expand the environment of your
| knowledge, kind of like wikipedia (I wonder why ).
|
| But poor as accurate source of knowledge or provider of accurate
| answers.
| freshtake wrote:
| The article captures the two agendas at work. The reality is
| somewhat dependent on your situation.
|
| If you understand _how_ you should be using AI in engineering,
| then AI can speed you up because you know what you're trying to
| build, you understand the fundamentals, and you are the pilot
| delegating granular tasks. When bugs pop up or requirements
| change, you'll have the knowledge required to frame and steer the
| AI to ensure goals are met, and met properly. When AI gets stuck,
| you'll be able to quickly jump in and work the problem. Your
| experience will continue to evolve and improve over time because
| you're plugged into the work and the code. You'll leverage your
| experience in unexpected ways in future projects, and perhaps
| your communication skills will improve as well.
|
| Alternatively, if AI is used improperly, it may provide the
| illusion of velocity up until the point where you realize that
| your lack of knowledge or involvement actually prevents the AI
| from making progress. You want to move beyond a simple
| implementation, bugs pop up that can't be fixed, or new
| requirements can't be met. You aren't able to dive in yourself,
| either because you weren't paying attention to the work or were
| operating too far outside of your expertise. In either case, the
| progress you thought you were making might actually be a pile of
| wasted time and technical debt.
| tim333 wrote:
| The carpentry analogy seems quite good
|
| >Quitting programming as a career right now because of LLMs would
| be like quitting carpentry as a career thanks to the invention of
| the table saw
|
| I presume carpenters can make a given item much quicker than they
| could in centuries past but there are still presumably a lot
| still employed, just doing slightly different things, like maybe
| sorting fancy custom staircases for new housing rather than
| churning out chests of draws.
| fleebee wrote:
| The analogy is pretty generous towards LLMs. I like Eevee's
| response to it in her blog post[1]:
|
| >What I do know is that a table saw quickly cuts straight
| lines. That is the thing it does. It doesn't do Whatever. It
| doesn't sometimes cut wavy lines and sometimes glue pieces
| together instead. It doesn't roll some dice and guess what
| shape of cut you are statistically likely to want based on an
| extensive database of previous cuts. It cuts a straight f*cking
| line.
|
| >If I were a carpenter, and my colleagues got really into this
| new thing where you just chuck 2x4s at a spinning whirling mass
| of blades until a chair comes out the other side... you know, I
| just might want to switch careers.
|
| [1]: https://eev.ee/blog/2025/07/03/the-rise-of-whatever/
| tropicalfruit wrote:
| coding is a means to an end.
|
| if AI can do it faster or cheaper, it wins. simple.
|
| i think it's good if AI could just do 99% of the work.
|
| but what is that 1%. and what will be the barriers to entry.
| rambambram wrote:
| So there are two narratives... but,
|
| > AI is important. But we don't yet fully know why.
|
| What about the narrative that AI is not important at all? As in,
| completely not. What about that side of the story?
| mwkaufma wrote:
| Claims were made by people with financial incentives, and then
| refuted by professionals and researchers who actually have to
| deal with the systems. That's not "two narratives" and
| recommending that you "tune out" is anti-critical thinking.
| FlingPoo wrote:
| AI coding assistants significantly accelerate repetitive tasks,
| but they lack true contextual reasoning, long-term architectural
| insight, and accountability. Human developers remain essential
| for critical problem-solving and design.
| andrewstuart wrote:
| IMO job cuts are much more about interest rates than AI.
| adrianwaj wrote:
| I doubt AI is actually intelligent or artificial, it's more like
| Attempted Insertions.
|
| Can it train on your own code or work to give results that make
| more sense? At least with more control, you can have better
| expectations. In other words, how can you be sure it'll never get
| ill? Does it learn about each user to give you what you want?
| Does it conform to you or vice versa?
|
| Is there a proof-of-work coin that can be used to handle the
| processing load? It's like a guilty pleasure right now. What'll
| be the long-term costs and risks of dependency? At least by
| reading from a human directly, there's that chance of a
| meaningful connection.
| h3lp wrote:
| The AI discussion reminds me of the assembly vs high-level
| languages (HLL) debate of my youth. The claim was that expert
| assembly language programmers could write optimized code that was
| much faster than compiled code, and therefore HLLs will always be
| the 'second best'. Obviously, that was a misunderstanding:
| compilers got so much better that, on average, they beat human
| assembly programmers, especially on large code bases where
| careful machine language optimization does not scale. There's
| still a place for optimized assembly language programming, but
| it's exclusively in high-performance highly reusable libraries.
|
| I think a similar pattern will emerge for AI: it'll be used for
| routine code, while freeing skilled programmers for algorithm
| development and similar high-level tasks.
| cleandreams wrote:
| At first it seemed LLM's were perfect assists for coding because
| they are trained on text and generate text. But code isn't
| typical text. It's basically a machine that requires a very high
| degree of precision and accuracy. Seen this way, LLM's are suited
| for coding only at specific stages -- to generate something like
| boiler plate, to brainstorm, to evaluate diverse approaches,
| identify missing tests. Anything that ties LLMs to actual code
| implementation is asking for trouble in my view.
| Nasrudith wrote:
| Remember that narratives are but a step away from outright lying
| and should always be taken with a grain of salt, especially if
| the best they can call themself is narrative. Narratives aren't
| about telling the truth they are about telling a story.
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