8 ms·

> So if Bob can do things with agents, he can do things. The problem arrises when Bob encounters a problem too complex or unique for agents to solve. To me, i

• jacquesm 6mo ago
  Precisely. The first 10 rungs of the ladder will be removed, but we still expect you to be able to get to the roof. The AI won't get you there and you won't have the knowledge you'd normally gain on those first 10 rungs to help you move past #10.
  • omega3 6mo ago
    That’s a good analogy but I think we’ve already went from 0 to 10 rungs over the last couple of years. If we assume that the models or harnesses will improve more and more rungs will be removed. Vast majority of programmers aren’t doing novel, groundbreaking work.
    • sweezyjeezy 6mo ago
      I think this was an unpopular opinion mainly because it's scary, rather than there being an obvious reason to think otherwise.
  • threatofrain 6mo ago
    But AI might actually get you there in terms of superior pedagogy. Personal Q&A where most individuals wouldn't have afforded it before.
  • wongarsu 6mo ago
    There are a lot of people in academia who are great at thinking about complex algorithms but can't write maintainable code if their life depended on it. There are ways to acquire those skills that don't go the junior developer route. Same with debugging and profiling skills But we might see a lot more specialization as a result
    • iterateoften 6mo ago
      They can’t write maintainable code because they don’t have real world experience of getting your hands dirty in a company. The only way to get startup experience is to build a startup or work for one
      • wongarsu 6mo ago
        Duh, the only way to get startup experience is indeed to get startup experience. My point is that getting into the weeds of writing CRUD software is not the only way to gain the ability to write complex algorithms, or to debug complex issues, or do performance optimization. It's only common because the stuff you make on the journey used to be economically valuable
        • iterateoften 6mo ago
          > write complex algorithms, or to debug complex issues, or do performance optimization That’s the stuff that ai is eating. The stuff I’m talking about (scaling orgs, maintaining a project long term, deciding what features to build or not build etc) is stuff very hard for ai
          • 8note 6mo ago
            I dont know if id call it "hard for ai" so much as "untreaded ground" agents might be better at it than people are, given the right structure
          • cweld510 6mo ago
            AI is only eating some of that though. For instance, everyone who does performance work knows that perhaps the most important part of optimization is constructing the right benchmark. This is already the thing that makes intractable problems tractable. That effect is now exacerbated — AI can optimize anything given a benchmark —- but AI isn’t making great progress at constructing the benchmark itself.
  • NiloCK 6mo ago
    People would have said the same about graphing calculators or calculators before that. Socrates said the same thing about the written word. The determining factor is always "did I come up with this tool". Somehow, subsequent generations always manage to find their own competencies (which, to be fair, may be different). This isn't guaranteed to play out, but it should be the default expectation until we actually see greatly diminishing outputs at the frontier of science, engineering, etc.
    • lukev 6mo ago
      I think that's too easy an analogy, though. Calculators are deterministically correct given the right input. It does not require expert judgement on whether an answer they gave is reasonable or not. As someone who uses LLMs all day for coding, and who regularly bumps against the boundaries of what they're capable of, that's very much not the case. The only reason I can use them effectively is because I know what good software looks like and when to drop down to more explicit instructions.
      • yunwal 6mo ago
        Determinism just means you don't have to use statistics to approach the right answer. It's not some silver bullet that magically makes things understandable and it's not true that if it's missing from a system you can't possibly understand it.
        • lukev 6mo ago
          That's not what I mean. If I use a calculator to find a logarithm, and I know what a logarithm is, then the answer the calculator gives me is perfectly useful and 100% substitutable for what I would have found if I'd calculated the logarithm myself. If I use Claude to "build a login page", it will definitely build me a login page. But there's a very real chance that what it generated contains a security issue. If I'm an experienced engineer I can take a quick look and validate whether it does or whether it doesn't, but if I'm not, I've introduced real risk to my application.
• roenxi 6mo ago
  That doesn't sound like much of an issue. Bob was already going to encounter problems that are too large and complex for him to solve, agents or otherwise. Life throws us hard problems. I don't recall if we even assumed Bob was unusually capable, he might be one of life's flounderers. I'd give good odds that if he got through a program with the help of agents he'll get through life achieving at least a normal level of success. But there is also a more subtle thing, which is we're trending towards superintelligence with these AIs. At the point, Bob may discover that anything agents can't do, Alice can't do because she is limited by trying to think using soggy meat as opposed to a high-performance engineered thinking system. Not going to win that battle in the long term. > The market will always value the exact things LLMs can not do, because if an LLM can do something, there is no reason to hire a person for that. The market values bulldozers. Whether a human does actual work or not isn't particularly exciting to a market.
  • uoaei 6mo ago
    "Things that have never been done before in software" has been my entire career. A lot of it requires specific knowledge of physics, modelling, computer science, and the tradeoffs involved in parsimony and efficiency vs accuracy and fidelity. Do you have a solution for me? How does the market value things that don't yet exist in this brave new world?
  • mattmanser 6mo ago
    The authors point went a little over your head. It doesn't matter if Bob can be normal. There was no point to him being paid to be on the program. From the article: If you hand that process to a machine, you haven't accelerated science. You've removed the only part of it that anyone actually needed.
    • lelanthran 6mo ago
      > It doesn't matter if Bob can be normal. There was no point to him being paid to be on the program. Yeah, I'm surprised at the number of people who read the article and came away with the conclusion that the program was designed to churn deliverables, and then they conclude that it doesn't matter if Bob can only function with an AI holding his hand, because he can still deliver. That isn't the output of the program; the output is an Alice. That's the point of the program. They don't want the results generated by Alice, they want the final Alice.
• b112 6mo ago
  Worse, soon fewer and fewer people will taste good food, including even higher and higher scale restaurants just using pre-made. As fewer know what good food tastes like, the entire market will enshitify towards lower and lower calibre food. We already see this with, for example, fruits in cold climates. I've known people who have only ever bought them from the supermarket, then tried them at a farmers when they're in season for 2 weeks. The look of astonishment on their faces, at the flavour, is quite telling. They simply had no idea how dry, flavourless supermarket fruit is. Nothing beats an apple picked just before you eat it. (For reference, produce shipped to supermarkets is often picked, even locally, before being entirely ripe. It last longer, and handles shipping better, than a perfectly ripe fruit.) The same will be true of LLMs. They're already out of "new things" to train on. I question that they'll ever learn new languages, who will they observe to train on? What does it matter if the code is unreadable by humans regardless? And this is the real danger. Eventually, we'll have entire coding languages that are just weird, incomprehensible, tailored to LLMs, maybe even a language written by an LLM. What then? Who will be able to decipher such gibberish? Literally all true advancement will stop, for LLMs never invent, they only mimic.
  • CuriouslyC 6mo ago
    Ironically, apples are one of the fruits where tree ripening isn't a big deal for a lot of varietals. You should have used tomato as the example, the difference there is night and day pretty much across the board. If humans can prove that bespoke human code brings value, it'll stick around. I expect that the cases where this will be true will just gradually erode over time.
    • b112 6mo ago
      If humans can prove that bespoke human code brings value, it'll stick around. Value to who, and which type of value? Will that defining value be purely economic in nature? While it be purely defined by mega-corps, and their perception of value? The market moves, the money flows to those which control its direction. We already see it today, with some firms literally forcing people to use LLM coding tools. The stories abound, of simply being forced to use whatever it spits out. Value, is often designed by cost, and code maintainability 5 years later isn't an immediate, quarter-profit induced concern. It feels like you're glossing over a lot of my point. In terms of new coding languages, it's rare to see new coding languages gain any traction, rust is the only recent one I know, and it's had a larger backer behind it since its release 15 years ago. It was supported in house for almost a decade before even seeing the light of day. Will that happen now? And created (or at least managed) by a human? If not, what would a new language look like? Would it be human maintainable? Understood? To me, this goes right back to the classic "buying a car with the hood welded shut". No way to maintain, repair, or even evaluate the quality of the thing under you.
• raldi 6mo ago
  To me it feels more like learning to cook versus learning how to repair ovens and run a farm. Software engineering isn’t about writing code any more than it’s about writing machine code or designing CPUs. It’s about bringing great software into existence.
  • victorbjorklund 6mo ago
    Or farming before and after agricultural machines. The principles are the same but the ”tactical” stuff are different.
• CuriouslyC 6mo ago
  Just because Bob doesn't know e.g. Rust syntax and library modules well, doesn't mean that Bob can't learn an algorithm to solve a difficult problem. The AI might suggest classes of algorithms that could be applicable given the real world constraints, and help Bob set up an experimental plan to test different algorithms for efficacy in the situation, but Bob's intuition is still in the drivers's seat. Of course, that assumes a Bob with drive and agency. He could just as easily tell the AI to fix it without trying to stay in the loop.
  • bigfishrunning 6mo ago
    But if Bob doesn't know rust syntax and library modules well, how can he be expected to evaluate the output generating Rust code? Bugs can be very subtle and not obvious, and Rust has some constructs that are very uncommon (or don't exist) in other languages. Human nature says that Bob will skim over and trust the parts that he doesn't understand as long as he gets output that looks like he expects it to look, and that's extremely dangerous.
    • ndriscoll 6mo ago
      Then perhaps Bob should have it use functional Scala, where my experience is that if it compiles and looks like what you expect, it's almost certainly correct.
      • bigfishrunning 6mo ago
        Sure, but bob is very unlikely to do that unless his AI tool of choice suggests it.
• zozbot234 6mo ago
  Real-world cooks don't exactly avoid those newfangled microwave ovens though. They use them as a professional tool for simple tasks where they're especially suitable (especially for quick defrosting or reheating), which sometimes allows them to cook even better meals.
• cfloyd 6mo ago
  I held this point of view for a while but I came to the (possibly naive) conclusion that it was just forced self-assurance. Truth is, the issues with sub-par output are just a prompting and supervision deficiency. An agent team can produce better end product if supervised and promoted correctly. The issue is most don’t take the time to do that. I’m not saying I like that this is true, quite the opposite. It is the reality of things now.
  • vrganj 6mo ago
    At some point the herding of idiot savants becomes more work than just doing the damn thing yourself in the first place.
    • lxgr 6mo ago
      I'm happy to herd idiots all my life if they come out of it smarter than they went in. The real tragedy with current LLM agents is that they're effectively stateless, and so all the effort of "educating" them feels wasted. Once continuous learning is solved, I predict the problem addressed by TFA to become orders of magnitude bigger: What's the motivation for anyone to teach a person if an LLM can learn it much faster, will work for you forever, and won't take any sick days or consider changing careers?
      • vrganj 6mo ago
        At that point, I think it'll be time to admit to ourselves that capitalism is over. The only reason we somewhat made it work is due to the interdependence between labor and capital. Once that's broken, the wheels will start falling off.
  • bigstrat2003 6mo ago
    > Truth is, the issues with sub-par output are just a prompting and supervision deficiency. An agent team can produce better end product if supervised and promoted correctly. Which is more work, and less fun, than doing it myself. No thanks.
• jnovek 6mo ago
  How many people who cook professionally are gourmet chefs? I think it ends up that gourmet cooking is so infrequently needed that we don’t require everyone who makes food to do it, just a small group of professionally trained people. Most people who make food for a living work somewhere like McDonald’s and Applebee’s where a high level of skill is not required. There will still be programming specialists in the future — we still have assembly experts and COBOL experts, after all. We just won’t need very many of them and the vast majority of software engineers will use higher-level tools.
  • ThrowawayR2 6mo ago
    That's the problem though: programmers who become the equivalent of McDonald's workers will be paid poorly like McDonald's workers and be treated as disposable like McDonald's workers.
    • benlivengood 6mo ago
      The problem is that mcdonalds workers are treated as disposable. Countries with proper human rights and labor laws don't do that.
• bitwize 6mo ago
  Bob+agents is going to be able to solve much more complex problems than Bob without agents. That's the true AI revolution: not the things it can accelerate, the things it can put in reach that you wouldn't countenance doing before.
• skippyboxedhero 6mo ago
  The correct distinction is: if you can't do something without the agent, then you can't do it. The problem that the author describes is real. I have run into it hundreds of times now. I will know how to do something, I tell AI to do it, the AI does not actually know how to do it at a fundamental level and will create fake tests to prove that it is done, and you check the work and it is wrong. You can describe to the AI to do X at a very high-level but if you don't know how to check the outcome then the AI isn't going to be useful. The story about the cook is 100% right. McDonald's doesn't have "chefs", they have factory workers who assemble food. The argument with AI is that working in McDonald's means you are able to cook food as well as the best chef. The issue with hiring is that companies won't be able to distinguish between AI-driven humans and people with knowledge until it is too late. If you have knowledge and are using AI tools correctly (i.e. not trying to zero-shot work) then it is a huge multiplier. That the industry is moving towards agent-driven workflows indicates that the AI business is about selling fake expertise to the incompetent.
• klabb3 6mo ago
  > The problem arrises when Bob encounters a problem too complex or unique for agents to solve. It’s actually worse than that: the AI will not stop and say ”too complex, try in a month with the next SOTA model”. Rather, it will give Bob a plausible looking solution that Bob cannot identify as right or wrong. If Bob is working on an instant feedback problem, it’s ok: he can flag it, try again, ask for help. But if the error can’t be detected immediately, it can come back with a vengeance in a year. Perhaps Bob has already gotten promoted by then, and Bobs replacement gets to deal with it. In either case, Bob cannot be trusted any more than the LLM itself.
  • noisy_boy 6mo ago
    How is that Bob's problem? When he said we need more time to do this properly, he was labelled slow. They pushed him to use AI all day long and told at the all hands that there will be programmers who use AI and those who don't will be left behind. So he said fuck doing it right for the project, let me do it right for myself. Now he got his promotion, they will hire 3 people in a cheaper location to handle various issues that are coming up (product will always have bugs you see). Given his excellent speed of delivery, they will report to him. Good for Bob.
    • klabb3 6mo ago
      > How is that Bob's problem? It isn’t. Bob has a different problem: that there are millions of Bobs with access to the same tools, meaning the value of Bobs labor is commodity priced. That may be good for some Bobs and bad for others.
      • noisy_boy 6mo ago
        No different than when all Bobs had access to similar power drills.
• latexr 6mo ago
  > The problem arrises when Bob encounters a problem too complex or unique for agents to solve. Or even sooner, when Bob’s internet connection is down, or he ran out of tokens, or has been banned from his favourite service, or the service is down, or he needs to solve a problem with a machine unable to run local models, or essentially any situation where he’s unable to use an LLM.
• mtrifonov 6mo ago
  I agree with the observation but want to note that it's specific to the particular (and these days, often too common) setup of AI as agent, doing Bob's work for him. There's a different version where the AI is just present in the conversation. It has opinions, it pushes back, it tells Bob his approach is wrong. In that setup Bob is still the one doing the thinking. The year doesn't happen around him because nothing got delegated. The drift in the article is a design choice. It comes from the agent frame, not from AI itself.