9 ms·

Two narratives about AI

266 points by RickJWagner 1y ago

itqwertz 1y ago
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 1y ago
  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 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 1y ago
    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 1y ago
      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 1y ago
        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
        skydhash 1y ago
        By the time all of this is written, I'm familiar enough with the code to fly over it (Hello, Emacs and Vim). But by then, your tasks are small and targeted fixes, because any new feature requires lot of planning and stakeholder discussions that you can't just go and work on it.
    - n4r9 1y ago
      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 1y ago
      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 1y ago
      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.
    - didibus 1y ago
      > I simply cannot square this with my last few weeks absolutely barnstorming on a project using Claude Code. I don't know, but the interesting data in the study is that they all said the same thing you are saying, but their actual time was 19% slower. And yes, right now it's the only study that seemed to have a good methodology that I've seen that has any data positive or negative.
  - steveklabnik 1y ago
    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 1y ago
      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 1y ago
        You have made the claim that it does extrapolate. Which they themselves do not make.
        almog 1y ago
        How is saying that it's not all clear LLM increase experienced developers productivity an extrapolation? The only extrapolations I've seen on this thread are people shrugging it as using 6 months old LLMs so this whole paper must be invalid today.
        steveklabnik 1y ago
        Okay, so, I re-read your original post: > it's not all that LLMs increase experienced developers productivity (even when they believe that it does): In the present, I am struggling to parse this. When I made my original comment, I understood you to be saying that LLMs do not increase productivity. Synthesizing what you're saying now with that, if I had read > it's not at all clear that LLMs increase then I would have understood you correctly. That's my bad! > The only extrapolations I've seen on this thread are people shrugging it as using 6 months old LLMs so this whole paper must be invalid today. I feel for both sides on this one. I do think that, for me personally, the models they used weren't good, but the ones that exist now are. So I do think there's some issue there. However, I don't think that makes the study invalid, if anything, it's a great way to test this hypothesis: if they do the same thing again, but with newer models, that would lend some weight to that idea. So I also think saying that this is completely irrelevant is missing the point.
  - itsafarqueue 1y ago
    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 1y ago
    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 1y ago
    > 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.
    - arkaic 1y ago
      Here here
oidar 1y ago
The volume of emotion running through the discourse on LLMs feel qualitatively different compared to something like bitcoin.
- poly2it 1y ago
  I'm so tired of it. Lobste.rs has become unusable due to the endless echoes of resentment.
  - logicchains 1y ago
    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.
    - isaacremuant 1y ago
      I think there's just droves of people who came to software thinking it was the new stable, solid, good reputation way to make money sitting in front of a computer. I saw so many people who were not following what they liked but "a good choice". Now many are scared instead of excited and/or skeptical because they don't trust their own self and ability to reinvent all the time. We do change a lot of practices in short periods of time. This is similar to an extent. Learning and guiding this new world is extremely interesting. You don't need to lie like a CEO either. Just solve, guide and build the new challenges.
- johnfn 1y ago
  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 1y ago
  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.
jeanlucas 1y ago
I don't like titles like this :( I don't wanna read it
- ducttapecrown 1y ago
  Here, I asked ChatGPT to summarize it for you: just kidding.
827a 1y ago
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 1y ago
The author is the only one knows something about AI! wink wink wink
- gausswho 1y ago
  If you'd read the article, you'd know that's not what he's purporting.
  - Loic 1y ago
    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 1y ago
      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 1y ago
      >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 1y ago
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 1y ago
  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 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 1y ago
  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 1y ago
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 1y ago
  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 1y ago
    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 1y ago
      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 1y ago
        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.
NickNaraghi 1y ago
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 1y ago
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 1y ago
  > 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 1y ago
    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 1y ago
      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.
fleebee 1y ago
> 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 1y ago
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 1y ago
  Yep. I mentally inserted the subtitle "... especially not Cal Newport"
  - impish9208 1y ago
    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 1y ago
      Being a CS professor informs a person in no way about developer productivity.
      - calf 1y ago
        I couldn't stand Cal Newport's self-help articles 10 years ago, I am triggered today seeing this "article" on the top of HN
- ipaddr 1y ago
  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 1y ago
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 1y ago
  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.
  - isaacremuant 1y ago
    > 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 This is just not true. Specially if your team exists within an organization that works in world wide solutions and interacts with the rest of the world. Remote can be so much faster and efficient because it's decentralized by nature and it can make everyone's workflows as optimized as possible. Just because companies push for "onsite" work to justify their downtown real estate doesn't mean it's more productive.
throwaway20174 1y ago
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 1y ago
  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 1y ago
  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.
  - skydhash 1y ago
    > We still create software largely the same as we did in the 1980s. Developers sitting at keyboards writing code, line by line. That's because the single dimension of code fits how the computer works and we can project any higher order dimension on it. If you go with 2 dimensions like pictures, it no longer fits the computer model, and everything becomes awkward with the higher dimensions of the domain. The only good 2d representation is the grid (spreadsheet, relation dbs, parallel programming..) and even they can be unwieldy. The mental model is the higher dimension structure, that we project on line of codes. Having LLM generating it is like throwing painting on canvas and hoping for the Mona Lisa.
d4mi3n 1y ago
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 1y ago
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 1y ago
  How did you pick the number "about a dozen"? Probably just LLM budget constraint I guess.
20k 1y ago
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 1y ago
  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
JimDabell 1y ago
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-ai https://www.recurse.com/blog/191-developing-our-position-on-...
- softwaredoug 1y ago
  “Carbon capture” seems oddly specific?
  - pchristensen 1y ago
    My guess is that's a specific example of e.g. novel scientific modeling.
- unstuck3958 1y ago
  Anecdotal: definitely a long way to go for systems programming, non-trivial firmware, and critical systems in general. And I say this as a huge fan of LLMs in general. I work as a FW Eng and while they've been of immense value in scripting especially (fuck you powershell), I can only use them as a better autocomplete on our C codebase. Sometimes I'd chat with the codebase, but that's a huge hit or miss.
upquacker 1y ago
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.
0x500x79 1y ago
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 1y ago
  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 1y ago
    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 1y ago
  > 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 1y ago
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 1y ago
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 1y ago
  Solo developers were already multiple times more productive than their coworkers and it never made much difference, even in compensation.
johnwheeler 1y ago
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 1y ago
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?
daxfohl 1y ago
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 1y ago
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 1y ago
  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 1y ago
    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 1y ago
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 1y ago
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 1y ago
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 1y ago
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 cliché 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.
einrealist 1y ago
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 1y ago
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 1y ago
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 1y ago
Love the balance this post shows in supporting and dismissing ai impact, unlike the other post on hn today ;)
eddythompson80 1y ago
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 1y ago
  Yeah, seriously, what is this about? Dang, etc? Anyone?
afro88 1y ago
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 1y ago
> No One Knows Anything About AI Projection
senko 1y ago
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 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 1y ago
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 1y ago
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 1y ago
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.
- testing321123 1y ago
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- fleebee 1y ago
  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 2×4s 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/ https://eev.ee/blog/2025/07/03/the-rise-of-whatever/
  - remich 1y ago
    If the original framing was too generous, the response is at least as ungenerous. Table saws aren't deterministic tools either, and anyone who has used one for more than a minute can tell you that getting it to consistently cut the straight line you want takes skill.
deleted 1y ago
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5350-uiop-1130 1y ago
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 1y ago
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 1y ago
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 1y ago
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 1y ago
IMO job cuts are much more about interest rates than AI.
adrianwaj 1y ago
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 1y ago
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 1y ago
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 1y ago
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.
AITestSomething 1y ago
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266 points by RickJWagner 1y ago

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 1y ago
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 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 1y ago
  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 1y ago
    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 1y ago
      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
      - skydhash 1y ago
        By the time all of this is written, I'm familiar enough with the code to fly over it (Hello, Emacs and Vim). But by then, your tasks are small and targeted fixes, because any new feature requires lot of planning and stakeholder discussions that you can't just go and work on it.
  - n4r9 1y ago
    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 1y ago
    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 1y ago
    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.
  - didibus 1y ago
    > I simply cannot square this with my last few weeks absolutely barnstorming on a project using Claude Code. I don't know, but the interesting data in the study is that they all said the same thing you are saying, but their actual time was 19% slower. And yes, right now it's the only study that seemed to have a good methodology that I've seen that has any data positive or negative.
- steveklabnik 1y ago
  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 1y ago
    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 1y ago
      You have made the claim that it does extrapolate. Which they themselves do not make.
      - almog 1y ago
        How is saying that it's not all clear LLM increase experienced developers productivity an extrapolation? The only extrapolations I've seen on this thread are people shrugging it as using 6 months old LLMs so this whole paper must be invalid today.
        steveklabnik 1y ago
        Okay, so, I re-read your original post: > it's not all that LLMs increase experienced developers productivity (even when they believe that it does): In the present, I am struggling to parse this. When I made my original comment, I understood you to be saying that LLMs do not increase productivity. Synthesizing what you're saying now with that, if I had read > it's not at all clear that LLMs increase then I would have understood you correctly. That's my bad! > The only extrapolations I've seen on this thread are people shrugging it as using 6 months old LLMs so this whole paper must be invalid today. I feel for both sides on this one. I do think that, for me personally, the models they used weren't good, but the ones that exist now are. So I do think there's some issue there. However, I don't think that makes the study invalid, if anything, it's a great way to test this hypothesis: if they do the same thing again, but with newer models, that would lend some weight to that idea. So I also think saying that this is completely irrelevant is missing the point.
- itsafarqueue 1y ago
  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 1y ago
  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 1y ago
  > 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.
  - arkaic 1y ago
    Here here

oidar 1y ago

The volume of emotion running through the discourse on LLMs feel qualitatively different compared to something like bitcoin.

poly2it 1y ago
I'm so tired of it. Lobste.rs has become unusable due to the endless echoes of resentment.
- logicchains 1y ago
  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.
  - isaacremuant 1y ago
    I think there's just droves of people who came to software thinking it was the new stable, solid, good reputation way to make money sitting in front of a computer. I saw so many people who were not following what they liked but "a good choice". Now many are scared instead of excited and/or skeptical because they don't trust their own self and ability to reinvent all the time. We do change a lot of practices in short periods of time. This is similar to an extent. Learning and guiding this new world is extremely interesting. You don't need to lie like a CEO either. Just solve, guide and build the new challenges.
johnfn 1y ago
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 1y ago
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.

jeanlucas 1y ago

I don't like titles like this :( I don't wanna read it

ducttapecrown 1y ago
Here, I asked ChatGPT to summarize it for you: just kidding.

827a 1y ago

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 1y ago

The author is the only one knows something about AI! wink wink wink

gausswho 1y ago
If you'd read the article, you'd know that's not what he's purporting.
- Loic 1y ago
  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 1y ago
    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 1y ago
    >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 1y ago

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 1y ago
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 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 1y ago
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 1y ago

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 1y ago
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 1y ago
  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 1y ago
    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 1y ago
      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.

NickNaraghi 1y ago

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 1y ago

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 1y ago
> 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 1y ago
  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 1y ago
    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.

fleebee 1y ago

> 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 1y ago

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 1y ago
Yep. I mentally inserted the subtitle "... especially not Cal Newport"
- impish9208 1y ago
  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 1y ago
    Being a CS professor informs a person in no way about developer productivity.
    - calf 1y ago
      I couldn't stand Cal Newport's self-help articles 10 years ago, I am triggered today seeing this "article" on the top of HN
ipaddr 1y ago
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 1y ago

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 1y ago
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.
- isaacremuant 1y ago
  > 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 This is just not true. Specially if your team exists within an organization that works in world wide solutions and interacts with the rest of the world. Remote can be so much faster and efficient because it's decentralized by nature and it can make everyone's workflows as optimized as possible. Just because companies push for "onsite" work to justify their downtown real estate doesn't mean it's more productive.

throwaway20174 1y ago

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 1y ago
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 1y ago
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.
- skydhash 1y ago
  > We still create software largely the same as we did in the 1980s. Developers sitting at keyboards writing code, line by line. That's because the single dimension of code fits how the computer works and we can project any higher order dimension on it. If you go with 2 dimensions like pictures, it no longer fits the computer model, and everything becomes awkward with the higher dimensions of the domain. The only good 2d representation is the grid (spreadsheet, relation dbs, parallel programming..) and even they can be unwieldy. The mental model is the higher dimension structure, that we project on line of codes. Having LLM generating it is like throwing painting on canvas and hoping for the Mona Lisa.

d4mi3n 1y ago

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 1y ago

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 1y ago
How did you pick the number "about a dozen"? Probably just LLM budget constraint I guess.

20k 1y ago

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 1y ago
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

JimDabell 1y ago

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-ai https://www.recurse.com/blog/191-developing-our-position-on-...

softwaredoug 1y ago
“Carbon capture” seems oddly specific?
- pchristensen 1y ago
  My guess is that's a specific example of e.g. novel scientific modeling.
unstuck3958 1y ago
Anecdotal: definitely a long way to go for systems programming, non-trivial firmware, and critical systems in general. And I say this as a huge fan of LLMs in general. I work as a FW Eng and while they've been of immense value in scripting especially (fuck you powershell), I can only use them as a better autocomplete on our C codebase. Sometimes I'd chat with the codebase, but that's a huge hit or miss.

upquacker 1y ago

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.

0x500x79 1y ago

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 1y ago
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 1y ago
  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 1y ago
> 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 1y ago

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 1y ago

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 1y ago
Solo developers were already multiple times more productive than their coworkers and it never made much difference, even in compensation.

johnwheeler 1y ago

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 1y ago

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?

daxfohl 1y ago

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 1y ago

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 1y ago
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 1y ago
  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 1y ago

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 1y ago

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 1y ago

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 1y ago

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 cliché 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.

einrealist 1y ago

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 1y ago

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 1y ago

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 1y ago

Love the balance this post shows in supporting and dismissing ai impact, unlike the other post on hn today ;)

eddythompson80 1y ago

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 1y ago
Yeah, seriously, what is this about? Dang, etc? Anyone?

afro88 1y ago

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 1y ago

> No One Knows Anything About AI Projection

senko 1y ago

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 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 1y ago

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 1y ago

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 1y ago

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.

testing321123 1y ago
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fleebee 1y ago
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 2×4s 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/ https://eev.ee/blog/2025/07/03/the-rise-of-whatever/
- remich 1y ago
  If the original framing was too generous, the response is at least as ungenerous. Table saws aren't deterministic tools either, and anyone who has used one for more than a minute can tell you that getting it to consistently cut the straight line you want takes skill.

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5350-uiop-1130 1y ago

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 1y ago

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 1y ago

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 1y ago

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 1y ago

IMO job cuts are much more about interest rates than AI.

adrianwaj 1y ago

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 1y ago

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 1y ago

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 1y ago

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.

AITestSomething 1y ago

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