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We might all be AI engineers now

• bitwize 7mo ago
  [flagged]
  • miningape 7mo ago
    Seems strange, for decades we allowed developers to use what made them comfortable, you like notepad? go ahead and use it. Don't want an LSP? that's fine disable it. So long as their productivity was on par with the rest of the team there was no issue. Suddenly, everyone needs to use this new tool (which we haven't proven to actually be effective) and if you don't you don't belong in the industry.
    • bitwize 7mo ago
      > So long as their productivity was on par with the rest of the team there was no issue. Emphasis added. And anyway, for most software dev in most shops it wasn't true; most development takes place in whatever IDE the group/organization standardized on for the task, to make sure everyone gets proper tooling and to make collaboration and information sharing easier. Think of all the Java enterprise software developed by legions of drones in the 2000s and 2010s. They all used Eclipse, because Eclipse is what they were given. It's only with the emergence of whiny, persnickety Unix devs who refused to leave the comforting embrace of their editor of choice that shops in the internet/dotcom/startup tradition embraced a "use whatever tools you want" philosophy. They had uncharacteristically enormous leverage over the tech stack being deployed in such businesses and could force employers to make that concession. And anyway, what some of them could do with vi blew the boss's mind. It is true that we don't have a whole lot of hard data from large organizations that show AI productivity improvements. But absence of evidence is not evidence of absence. Turns out, most large organizations just haven't adopted AI in the amount and ways that could make a big impact. But we have enough anecdata from competent developers to suggest that the productivity gains are huge. So big, AI not only lets you do your normal tasks many times faster, it puts projects within reach that you would not have countenanced before because they were too complex or tedious to be worth the payoff. So no. Refusing to use AI is just pure bloodymindedness at this point—like insisting on using a keypunch while everyone around you discovers the virtues of CRT terminals and timesharing. There were people like this even in the 1970s when IBM finally came around and made timesharing available in their mainframes. Those people either got up to speed or moved on to a different profession. They couldn't keep working the way they'd been working because the productivity expectations changed with the availability of new technology.
      • bigfishrunning 7mo ago
        > It's only with the emergence of whiny, persnickety Unix devs who refused to leave the comforting embrace of their editor of choice that shops in the internet/dotcom/startup tradition embraced a "use whatever tools you want" philosophy. They had uncharacteristically enormous leverage over the tech stack being deployed in such businesses and could force employers to make that concession. And anyway, what some of them could do with vi blew the boss's mind. They had enormous leverage because they were more productive then the drones who use whatever tools they are handed and lack the curiosity to use anything else. These breathless reports of increased productivity are constant, but why is there no evidence of that productivity increase otherwise? Why hasn't there been a surge of side-project video games on Steam? Why is github down so often despite Microsoft's commitment to AI? The AI tools make it easier to do things that were already easy, but the minute your code gets interesting these tools are an absolute mess.
  • deleted 7mo ago
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  • slopinthebag 7mo ago
    What an incredibly stupid, tasteless, reductionist opinion. Go log off for a while and reevaluate your life.
  • wk320189 7mo ago
    [flagged]
• noemit 7mo ago
  Not a day goes by that a fellow engineer doesn't text me a screenshot of something stupid an AI did in their codebase. But no one ever mentions the hundreds of times it quietly wrote code that is better than most engineers can write. The catch about the "guided" piece is that it requires an already-good engineer. I work with engineers around the world and the skill level varies a lot - AI has not been able to bridge the gap. I am generalizing, but I can see how AI can 10x the work of the typical engineer working in Startups in California. Even your comment about curiosity highlights this. It's the beginning of an even more K-shaped engineering workforce. Even people who were previously not great engineers, if they are curious and always enjoyed the learning part - they are now supercharged to learn new ways of building, and they are able to try it out, learn from their mistakes at an accelerated pace. Unfortunately, this group, the curious ones, IMHO is a minority.
  • input_sh 7mo ago
    Quite frankly, if AI can write better code than most of your engineers "hundreds of times", then your hiring team is doing something terribly wrong.
    • theshrike79 7mo ago
      The "most engineers" not "most engineers we've hired". But also "most engineers" aren't very good. AIs know tricks that the average "I write code for my dayjob" person doesn't know or frankly won't bother to learn.
      • input_sh 7mo ago
        Even speaking from a pure statistical perspective, it is quite literally impossible for "AI" that outputs world's-most-average-answer to be better than "most engineers". In fact, it's pretty easy to conclude what percentage of engineers it's better than: all it does is it consumes as much data as possible and returns the statistically most probable answer, therefore it's gonna be better than roughly 50% of engineers. Maybe you can claim that it's better than 60% of engineers because bottom-of-the-barrel engineers tend to not publish their works online for it to be used as training data, but for every one of those you have a bunch of non-engineers that don't do this for a living putting their shitty attempts at getting stuff done using code online, so I'm actually gonna correct myself immediately and say that it's about 40%. The same goes for every other output: it's gonna make the world's most average article, the most average song in a genre and so on. You can nudge it to be slightly better than the average with great effort, but no, you absolutely cannot make it better than most.
• ChrisMarshallNY 7mo ago
  > The problem is: you can’t justify this throughput to someone who doesn’t understand real software engineering. They see the output and think “well the AI did it.” No. The AI executed it. I designed it. I knew what to ask for, how to decompose the problem, what patterns to use, when the model was going off track, and how to correct it. That’s not prompting. That’s engineering. That’s the “money quote,” for me. Often, I’m the one that causes the problem, because of errors in prompting. Sometimes, the AI catches it, sometimes, it goes into the ditch, and I need to call for a tow. The big deal, is that I can considerably “up my game,” and get a lot done, alone. The velocity is kind of jaw-dropping. I’m not [yet] at the level of the author, and tend to follow a more “synchronous” path, but I’m seeing similar results (and enjoying myself).
  • noemit 7mo ago
    There are two types of engineers who use AI: - Ones who see it generated something bad, and blame the AI. - Ones who see it generated something bad, and revert it and try to prompt better, with more clarity and guidance.
    • ChrisMarshallNY 7mo ago
      Three types: - Ones that use it as a “pair partner,” as opposed to an employee. Thanks for the implicit insult. That was helpful.
    • miningape 7mo ago
      - Ones who see it generated something bad, and realise it'd be faster to just hand fix the issues than babysit an LLM
      • bitwize 7mo ago
        That's a PEBKAC issue.
        • bigfishrunning 7mo ago
• amelius 7mo ago
  > Building systems that supervise AI agents, training models, wiring up pipelines where the AI does the heavy lifting and I do the thinking. Honestly? I’m having more fun than ever. I'm sure some people are having fun that way. But I'm also sure some people don't like to play with systems that produce fuzzy outputs and break in unexpected moments, even though overall they are a net win. It's almost as if you're dealing with humans. Some people just prefer to sit in a room and think, and they now feel this is taken away from them.
  • nbvkappowqpeop 7mo ago
    I'm just an old school programmer who loves writing code, and the recent AI developments have just taken the most fun part away from me.
    • kirito1337 7mo ago
      fr, like in 2020 I started to learn programming in C/C++ at 9 and in 2023 when the AI bubble just went on, it feels like I did it all for nothing
    • coldtea 7mo ago
      And "taking the fun out" is one thing. Making 50% or more of coders redandunt is a whole other can of worms.
    • sn0wflak3s 7mo ago
      I get this. I don't think either of you is wrong. There's a real loss in not writing something from scratch and feeling it come together under your hands. I'm not dismissing that. I have immense respect for the senior engineers who came before me. They built the systems and the thinking that everything I do now sits on top of. I learned from people. Not from AI. The engineers who reviewed my terrible pull requests, the ones who sat with me and explained why my approach was wrong. That's irreplaceable. The article is about where I think things are going, not about what everyone should enjoy.
  • deleted 7mo ago
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• Bukhmanizer 7mo ago
  This essay somehow sounds worse than AI slop, like ChatGPT did a line of coke before writing this out. I use AI everyday for coding. But if someone so obviously puts this little effort into their work that they put out into the world, I don’t think I trust them to do it properly when they’re writing code.
  • sn0wflak3s 7mo ago
    I wrote it myself. But the irony isn't lost on me. "Who did what" is kind of the whole point of the article. Appreciate the feedback.
    • jascha_eng 7mo ago
      FWIW I reported your post to the mods because it reads completely AI generated to me. My judgement was that it might have been slightly edited but is largely verbatim LLM output. Some tells that you might wanna look at in your writing, if you truly did write it yourself without Any LLM input are these contrarian/pivoting statements. Your post is full of these and it is imo the most classic LLM writing tell atm. These are mostly variants of the 'Its not X but Y" theme: - "Not whether they've adopted every tool, but whether they're curious" - "I still drive the intuition. The agents just execute at a speed I never could alone." - "The model doesn't save you from bad decisions. It just helps you make them faster." - "That foundation isn't decoration. It's the reason the AI is useful to me in the first place." - "That's not prompting. That's engineering" It is also telling that the reader basically cant take a breather most of the sentences try to emphasize harder than the last one. There is no fluff thought, no getting side tracked. It reads unnatural, humans do not think like this usually.
      • abathologist 7mo ago
        The LLMs are training "us" now. First we develop the machines, then we contort the entire social and psychic order to serve their rhythms and facilitate their operation.
      • deleted 7mo ago
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• octoclaw 7mo ago
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• deleted 7mo ago
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• roli64 7mo ago
  Lost me at "I’m building something right now. I won’t get into the details. You don’t give away the idea."
  • rl3 7mo ago
    Perhaps execution is cheap now and ideas aren't? Personally I'm quite pleased with this inversion.
    • bena 7mo ago
      Ideas are always cheap. Eventually you will have to tell people what the idea is, even if it is at product launch. And then, if execution is as cheap and easy as they claim, then anyone can replicate the idea without having to engage with the person in the first place. Ideas will never not be cheap.
      • rl3 7mo ago
        >Ideas will never not be cheap. Never say never. Besides, there's still non-technical moats aplenty.
    • phil21 7mo ago
      As someone else implied in their comment... If execution no longer matters, then what possible ideas exist out there that both are highly valuable as well as only valuable to the first mover? If the second person to see the value in the idea can execute it in a weekend using AI tools, what value is there in the idea to begin with? In fact the second mover advantage seems to me to be even larger than before. Let someone else get the first version out the door, then you just point your AI bot at the resulting product to copy it in a fraction of the time it took the original person to execute on it. If anything, ideas seem to be even cheaper to me in this new world. It probably just moves what bits of execution matter even more towards sales and marketing and hype vs. executing on the actual product itself. I think there might be some interesting spaces here opening up in the IP combined with "physical product" space. Where you need the idea as well as real-world practical manufacturing skills in order to execute. That will still be somewhat of a moat for a little while at least, but mostly at a scale where it's not worth an actual manufacturer from China to spin up a production line to compete with you at scale.
• duggan 7mo ago
  Very much on the same page as the author, I think AI is a phenomenal accelerant. If you're going in the right direction, acceleration is very useful. It rewards those who know what they're doing, certainly. What's maybe being left out is that, over a large enough distribution, it's going to accelerate people who are accidentally going in the right direction, too. There's a baseline value in going fast.
  • salawat 7mo ago
    >There's a baseline value in going fast. Maybe to the people writing the invoices for the infra you're renting, sure. Or to the people who get paid to dig you out of the consequences you inevitably bring about. Remember, the faster the timescale, the worse we are wired to effectively handle it as human beings. We're playing with a fire that catches and spreads so fast, by the time anyone realizes the forest is catching and starting to react, the entire forest is already well on the way to joining in the blaze.
    • duggan 7mo ago
      > We're playing with a fire that catches and spreads so fast, by the time anyone realizes the forest is catching and starting to react, the entire forest is already well on the way to joining in the blaze. I suspect this has been said in one form or another since the discovery of fire itself.
      • salawat 7mo ago
        Even if it is as perennial as contempt for descendents, when the fact is that signals are getting so fast they trigger downstream responses faster than a neuron can finish it's refractory period renders it not exactly a trivially dismissable observation.
• CrzyLngPwd 7mo ago
  It sounds a bit no-true-scotsman to me.
• bambax 7mo ago
  I agree wholeheartedly with all that is said in this article. When guided, AI amplifies the productivity of experts immensely. There are two problems left, though. One is, laypersons don't understand the difference between "guided" and "vibe coded". This shouldn't matter, but it does, because in most organizations managers are laypersons who don't know anything about coding whatsoever, aren't interested by the topic at all, and think developers are interchangeable. The other problem is, how do you develop those instincts when you're starting up, now that AI is a better junior coder than most junior coders? This is something one needs to think about hard as a society. We old farts are going to be fine, but we're eventually going to die (retire first, if we're lucky; then die). What comes after? How do we produce experts in the age of AI?
  • jstanley 7mo ago
    I think the problem is overstated. People always learn the things they need to learn. Were people clutching their pearls about how programmers were going to lack the fundamentals of assembly language after compilers came along? Probably, but it turned out fine. People who need to program in assembly language still do. People who need to touch low-level things probably understand some of it but not as deeply. Most of us never need to worry about it.
    • coldtea 7mo ago
      >People always learn the things they need to learn. No, they don't. Which why a huge % of people are functionaly illiterate at the moment, know nothing about finance and statistics and such and are making horrendous decisions for their future and their bottom line, and so on. There is also such a thing as technical knowledge loss between generations.
    • bambax 7mo ago
      I don't think the comparison (that's often made) between AI and compilers is valid though. A compiler is deterministic. It's a function; it transforms input into output and validates it in the process. If the input is incorrect it simply throws an error. AI doesn't validate anything, and transforms a vague input into a vague output, in a non-deterministic way. A compiler can be declared bug-free, at least in theory. But it doesn't mean anything to say that the chain 'prompt-LLM-code' is or isn't "correct". It's undecidable.
• rimmontrieu 7mo ago
  > But guided? The models can write better code than most developers. That’s the part people don’t want to sit with. When guided. Where do you draw the line between just enough guidance vs too much hand holding to an agent? At some point, wouldn't it be better to just do it yourself and be done with the project (while also build your muscle memory, experiences and the mental model for future projects, just like tons of regular devs have done in the past)
  • sn0wflak3s 7mo ago
    The line is scope. I'm not asking an agent to build me a full-stack app. That's where you end up babysitting it like a kindergartener and honestly you'd be faster doing it yourself. The way I use agents is focused, context-driven, one small task at a time. For example: i need a function that takes a dependency graph, topologically sorts it, and returns the affected nodes when a given node changes. That's well-scoped. The agent writes it, I review it, done. But say I'm debugging a connection pool leak in Postgres where connections aren't being released back under load because a transaction is left open inside a retry loop. I'm not handing that to an agent. I already know our system. I know which service is misbehaving, I know the ORM layer, I know where the connection lifecycle is managed. The context needed to guide the agent properly would take longer to write than just opening the code and tracing it myself. That's the line. If the context you'd need to provide is larger than the task itself, just do it. If the task is well-defined and the output is easy to verify, let the agent rip. The muscle memory point is real though. i still hand-write code when I'm learning something new or exploring a space I don't understand yet. AI is terrible for building intuition in unfamiliar territory because you can't evaluate output you don't understand. But for mundane scaffolding, boilerplate, things that repeat? I don't. llife's too short to hand-write your 50th REST handler.
• jruz 7mo ago
  I find really sad how people are so stubborn to dismiss AI as a slop generator. I completely agree with the author, once you spend the time building a good enough harness oh boy you start getting those sweet gains, but it takes a lot of time and effort but is absolutely worth it.
  • holyra 7mo ago
    Personally, I dismiss AI, mainly agenetic ones, because of its environmental impact. I hope that one day everyone will be held accountable for it.
• yanis_t 7mo ago
  They will never admit it, but many are scared of losing their jobs. This threat, while not yet realized, is very real from a strictly economic perspective. AI or not, any tool that improves productivity can lead to workforce reduction. Consider this oversimplified example: You own a bakery. You have 10 people making 1,000 loaves of bread per month. Now, you have new semi-automatic ovens that allow you to make the same amount of bread with only 5 people. You have a choice: fire 5 people, or produce 2,000 loaves per month. But does the city really need that many loaves? To make matters worse, all your competitors also have the same semi-automatic ovens...
  • hansmayer 7mo ago
    > Consider this oversimplified example: You own a bakery. You have 10 people making 1,000 loaves of bread per month. Now, you have new semi-automatic ovens that allow you to make the same amount of bread with only 5 people. That is actually the case with a lot of bakeries these days. But the one major difference being,the baker can rely with almost 100% reliability that the form, shape and ingredients used will be exact to the rounding error. Each time. No matter how many times they use the oven. And they don't have to invent strategies on how to "best use the ovens", they don't claim to "vibe-bake" 10x more than what they used to bake before etc... The semi-automated ovens just effing work! Now show me an LLM that even remotely provides this kind of experience.
    • therealdrag0 7mo ago
      Eh accuracy and reliability is a different topic hashed out many times on HN. This thread is about productivity. I’m a staff engineer and I don’t know a single person not using AI. My senior engineers are estimating 40% gains in productivity.
      • maltelau 7mo ago
        And every time the issue is side-stepped by chatbot proponents. Accuracy and reliability are necessary to know real productivity. If you have produced code that doesn't work right, you haven't "produced" anything (except in the economic sense of managing to get someone to pay for it). For example, if you produce 5x more code at 5% reliability, the net result is a -75% change in productivity (ignoring the overhead costs of detecting said reliability).
• holyra 7mo ago
  what about the environmental impact of AI, especially agentic AI? I keep reading praise for AI on the orange site, but its environmental impact is rarely discussed. It seems that everyone has already adopted this technology, which is destroying our world a little more.
  • bob1029 7mo ago
    I believe the orange site's consensus was that it's approximately one additional mini fridge or dish washer worth of consumption on average. You've got users who use these tools barely 1k tokens per week. Assuming it's all batched ideally that's like running an LED floodlight for a minute or so. The other end of the spectrum can be pretty extreme in consumption but it's also rare. Most people just use the adhoc stuff.
  • wartywhoa23 7mo ago
    All environmental impacts are equal, but some of them are more equal than the others!
    • holyra 7mo ago
      This comes from a dystopian book (Animal Farm). What is your point?
      • wartywhoa23 7mo ago
        If you read the book, my point should be crystal clear - that environmental impact which aligns with The Party goals (shareholder profits) the best, is painted the least concerning of all.
  • dist-epoch 7mo ago
    The environmental impact of AI replacing a human programmer is orders of magnitude lower than the environmental impact of that programmer. Look up average US water consumption and CO2 emissions per capita. And then add on top the environmental impact of all of the money that programmer gets from programming - travels around the world, buying large houses, ... If you care about the environment, you should want AI's replacing humans at most jobs so that they can no longer afford traveling around the world and buying extravagant stuff.
• v3xro 7mo ago
  The only way I see out of this crisis (yes I'm not on the token-using side of this) is strict liability for companies making software products (just like in the physical world). Then it doesn't matter if the token-generator spits out code or a software engineer spits out code - the company's incentives are aligned such that if something breaks it's on them to fix it and sort out any externalities caused. This will probably mean no vibe-coded side hustles but I personally am OK with that.
  • _dwt 7mo ago
    I think this is coming, alongside professional licensure for "software engineers". Every public-facing project will need someone to put a literal stamp of approval on the code, and regardless whether Claude or Codex wrote the bulk of it, it'll be that person's head on a pike when something goes wrong. This isn't what many of us probably would have wanted, but I think the public blowback when "AI-coded" systems start failing is going to drive us there. (Note to passing hype-men: I did not say they will fail at higher rates than human-coded systems! I happen to believe this, but it is not germane to the argument - only the public perception matters here.)
    • twodave 7mo ago
      This already exists. They’re called software audits, and the more risk-averse your customers are they more required they become.
• thefounder 7mo ago
  The issue is that you become lazy after a while and stop “leading the design”. And I think that’s ok because most of the code is just throwaway code. You would rewrite your project/app several times by the time it’s worth it to pay attention to “proper” architecture. I wish I had these AIs 10 years ago so that I could focus on everything I wanted to build instead to become a framework developer/engineer.
  • sd9 7mo ago
    I agree. I've got more lazy over time too. But the cost of creating code is so cheap... it's now less important to be perfect the first time the code hits prod (application dependant). It can be rewritten from scratch in no time. The bar for 'maintainability' is a lot lower now, because the AI has more capacity and persistence to maintain terrible code. I'm sure plenty of people disagree with me. But I'm a good hand programmer, and I just don't feel the need to do that any more. I got into this to build things for other people, and AI is letting me do that more efficiently. Yes, I've had to give up a puritan approach to code quality.
  • ValentineC 7mo ago
    > I wish I had these AIs 10 years ago so that I could focus on everything I wanted to build instead to become a framework developer/engineer. I think frameworks (especially those that have testing built-in) are even more important as guardrails now.
• jwr 7mo ago
  Finally a take that I can agree with.
• pdh 7mo ago
  I would think an AI engineer is one who is, you know, engineering AI. We might all be AI users now, though.
• jjmarr 7mo ago
  I vibe coded a Kubernetes cluster in 2 days for a distributed compilation setup. I've never touched half this stuff before. Now I have a proof of concept that'll change my whole organization. That would've taken me 3 months a year ago, just to learn the syntax and evaluate competing options. Now I can get sccache working in a day, find it doesn't scale well, and replace it with recc + buildbarn. And ask the AI questions like whether we should be sharding the CAS storage. The downside is the AI is always pushing me towards half-assed solutions that didn't solve the problem. Like just setting up distributed caching instead of compilation. It also keeps lying which requires me to redirect & audit its work. But I'm also learning much more than I ever could without AI.
  • truetraveller 7mo ago
    You perhaps just introduced one more moving part, that you don't understand well. Instead of thinking of a simpler solution.
  • _dwt 7mo ago
    I hope we get a follow-up in six months or a year as to how this all went.
  • sph 7mo ago
    > I vibe coded a Kubernetes cluster in 2 days for a distributed compilation setup. I've never touched half this stuff before. Now I have a proof of concept that'll change my whole organization. Dunning-Kruger as a service. Thank God software engineers are not in charge of building bridges. Looking forward to your post-mortem.
  • slopinthebag 7mo ago
    > that would've taken me 3 months a year ago, just to learn the syntax This is hyperbole, right? In what world does it take 3 months to learn the syntax to anything? 3 days is more than enough time.
• wk320189 7mo ago
  Strangely we never hear gushing pieces on how great gcc is. If you have to advertise that much or recruit people with AI mania, perhaps your product isn't that great.
  • ericd 7mo ago
    Maybe when they've also been doing their thing for almost 40 years, people will be past this phase for LLMs, too ;-)
  • doug_durham 7mo ago
    You must be new to Hacker News. There have been plenty of pieces praising the GCC toolchain.
• deleted 7mo ago
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• egl2020 7mo ago
  "You can learn anything now. I mean anything." This was true before before LLMs. What's changed is how much work it is to get an "answer". If the LLM hands you that answer, you've foregone learning that you might otherwise have gotten by (painfully) working out the answer yourself. There is a trade-off: getting an answer now versus learning for the future. I recently used an LLM to translate a Linux program to Windows because I wanted the program Right Now and decided that was more important than learning those Windows APIs. But I did give up a learning opportunity.
  • tsunamifury 7mo ago
    Books are for the mentally enfeebled who can't memorize knowledge. - Socrates
    • aozgaa 7mo ago
      I can’t tell if this is a genuine quote or not. Can you provide a citation? (I think something like this comes up in the Phaedrus)
    • goatlover 7mo ago
      Written by Plato.
    • nightski 7mo ago
      Aren't books to communicate knowledge?
    • sdf2df 7mo ago
      Wrong person you're quoting but he did not foresee the benefit of leveraging the work of others to extend and build-on-top.
  • twodave 7mo ago
    I am beginning to disagree with this, or at least I am beginning to question its universal truth. For instance, there are so many times when "learning" is an exercise at attempting to apply wrong advice many times until something finally succeeds. For instance, retrieving the absolute path an Angular app is running at in a way that is safe both on the client and in SSR contexts has a very clear answer, but there are a myriad of wrong ways people accomplish that task before they stumble upon the Location injectable. In cases like the above, the LLM is often able to tell you not only the correct answer the first time (which means a lot less "noise" in the process trying to teach you wrong things) but also is often able to explain how the answer applies in a way that teaches me something I'd never have learned otherwise. We have spent the last 3 decades refining what it means to "learn" into buckets that held a lot of truth as long as the search engine was our interface to learning (and before that, reading textbooks). Some of this rhetoric begins to sound like "seniority" at a union job or some similar form of gatekeeping. That said, there are also absolutely times (and sometimes it's not always clear that a particular example is one of those times!!) when learning something the "long" way builds our long term/muscle memory or expands our understanding in a valuable way. And this is where using LLMs is still a difficult choice for me. I think it's less difficult a choice for those with more experience, since we can more confidently distinguish between the two, but I no longer think learning/accomplishing things via the LLM is always a self-damaging route.
• nickstinemates 7mo ago
  I've been programming for literally my entire life. I love it, it's part of me, and there hasn't been more than a week in 30 years that I haven't written some code. This is the first time that I feel a level of anxiety when I am not actively doing it. What a crazy shift that I am still so excited and enamored by the process after all of this time. But there's also the double edged sword. I am also having a really hard time moderating my working hours, which I naturally struggle with anyway, even more. Partly because I am having so much fun and being so productive. But also because it's just so tempting to add 1 more feature, fix one more bug.
• holoduke 7mo ago
  I think he is absolutely right. But what if he is not right? Then he is also absolutely right. He is just always absolutely right right?. Even when he is not right? Yes he is always absolutely right.
• nabbed 7mo ago
  >I think we all might be AI Engineers now, and I’m not sure how I feel about that. Except the rest of the article strongly implies he feels pretty good about it, assuming you can properly supervise your agents.
• arikrahman 7mo ago
  The perception seems to be that AI is only causing security vulnerabilites (see: openclaw injection in npm (Clinejection)). But the article's optimistic tone much reflects my own, and if it were all bad, then nobody would be using AI. But it's mostly good, and with the benchmarks, it's a statistical fact that it helps more than it hurts. It's just math at a certain point.
• nabbed 7mo ago
  I'm glad I am no longer in tech because I just don't want to do this. This is not a dig at AI. If I take this article at face value, AI makes people more productive, assuming they have the taste and knowledge to steer their agents properly. And that's possibly a good thing even though it might have temporary negative side effects for the economy. >But the AI is writing the traversal logic, the hashing layers, the watcher loops, But unfortunately that's the stuff I like doing. And also I like communing with the computer: I don't want to delegate that to an agent (of course, like many engineers I put more and more layers between me and the computer, going from assembly to C to Java to Scala, but this seems like a bigger leap).
  • drchickensalad 7mo ago
    I wish I moved to HCOL earlier so I could have saved enough fast enough to be you. I thought it would take more time before the end...
    • Ancalagon 7mo ago
      Well, at least you will have lots of company (me included).
  • TRiG_Ireland 7mo ago
    I'm a developer who was made redundant, and I'm now casting around for an entirely new job because, likewise, I have no interest in working with AI. It sounds boring, and the concept squicks me out, to be honest.
    • simonw 7mo ago
      Out of interest what kind of fields are you looking at? I expect there are going to be a bunch of people in similar situations to you over the next few years, I'm interested to know where they end up.
      • gavinray 7mo ago
        I'm reminded of the "MongoDB is WebScale" video: as of this moment I officially resigned from my job as software engineer and will take up work on the farm shoveling pig shit and administering anal suppositories to sick horses because that will be a thousand times more tolerable than being in the same industry as dipshits like you https://www.youtube.com/watch?v=b2F-DItXtZs https://www.youtube.com/watch?v=b2F-DItXtZs
• voxleone 7mo ago
  I’ve always designed systems along the classic path: requirements → use cases → schematization. With AI, I continue in the same spirit (structure precedes prompting), but now the foundational layer of my systems is axioms and constraints, and the architecture emerges through structured prompts. Any AI on the shift is an aide in building systems that are logically grounded. This is where the “all of us as AI engineers” claim becomes subtle. Yes, anyone can generate code, but real engineering remains about judgment and structure. AI amplifies throughput, but the bottleneck is still problem framing, abstraction choice, and trade-off reasoning.
• scroogedhard 7mo ago
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• pjmlp 7mo ago
  No we can't, because the teams are being reduced in headcount to the few lucky ones allowed to wear the AI hat.
• jihadjihad 7mo ago
  A 2026 AI Engineer is a 1996 Software Architect. I don't need to be the one manually implementing the individual widgets of a system, I can delegate their implementation to developers (agents). I'm being a little facetious, but I don't think it's far off the mark from what TFA is saying, and it matches my experience over the past few months. The worst architects we ever worked with were the ones who couldn't actually implement anything from scratch. Like TFA says, if you've got the fundamentals down and you want to see how far you can go with these new tools, play the role of architect for a change and let the agents fly.
• kseniamorph 7mo ago
  Saw the edit: I think that clarification was important. The core point resonates with me personally. The shift isn't about writing less code, it's about where the real judgment lives. Knowing what to build, how to decompose a problem, which patterns to reach for - and critically, when the model is confidently wrong. Without that foundation you're not moving faster, you're just making bad decisions faster. The scope point resonates too. Small, well-defined tasks with verifiable output is where agents actually shine.
  • t43562 7mo ago
    Without writing some code how will people really know what's right? I've supervised people before - one thinks one knows best and pontificates at them and then when one actually starts working in the codebase onself many issues become clear. If you never get your hands dirty your decisions will tend off towards badness.
• samdixon 7mo ago
  > I’m shipping in hours what used to take days. Not prototypes. Real, structured, well-architected software. > If I don’t understand what it’s doing, it doesn’t ship. That’s non-negotiable. Holy LinkedIn
  • getnormality 7mo ago
    Everyone who is really into blogging about their AI use sounds exactly like this. Hmm, I wonder why!
• jordanekay 7mo ago
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• ontouchstart 7mo ago
  I am running local offline small models in the old fashioned REPL style, without any agentic features. One prompt at a time. Instead of asking for answers, I ask for specific files to read or specific command line tools with specific options. I pipe the results to a file and then load it into the CLI session. Then I turn these commands into my own scripts and documentation (in Makefile). I forbid the model wandering around to give me tons of irrelevant markdown text or generated scripts. I ask straight questions and look for straight answers. One line at a time, one file at a time. This gives me plenty of room to think what I want and how I get what I want. Learning what we want and what we need to do to achieve it is the precious learning experience that we don’t want to offload to the machine.
  • FitchApps 7mo ago
    This. I'm also using an LLM very similarly and treat it like a knowledgeable co-worker I can ask for an advice or check something. I want to be the one applying changes to my codebase and then running the tests. Ok, agents may improve the efficiency but it's a slippery slope. I don't want to sit here all day watching the agents modify and re-modify my codebase, I want to do this myself because it's still fun though not as much fun as it was pre-AI
    • ontouchstart 7mo ago
      And you don't know what might trigger AI into overthinking. ;-) https://gist.github.com/ontouchstart/bc301a60067f687b65dad6412be08174 https://gist.github.com/ontouchstart/bc301a60067f687b65dad64... (This is an ongoing experiment, it doesn't matter what model I use.)
  • pragma_x 7mo ago
    > I ask straight questions and look for straight answers. One line at a time, one file at a time. I've also taken to using the Socratic Method when interrogating an LLM. No loaded questions, squeaky clean session/context, no language that is easy to misinterpret. This has worked well for me. The information I need is in there, I just need to coax it back out. I did exactly this for an exercise a while back. I wanted to learn Rust while coding a project and AI was invaluable for accelerating my learning. I needed to know completely off-the-wall things that involved translating idioms and practices from other languages. I also needed to know more about Rust idoms to solve specific problems and coding patterns. So I carefully asked these things, one at a time, rather than have it write the solution for me. I saved weeks if not months on that activity, and I'm at least dangerous at Rust now (still learning).
• sheepscreek 7mo ago
  “Hey AI, clone yourself” We’re getting there..
  • jgilias 7mo ago
    I’ve kind of done this. To an extent. “Hey Claude, you have a bunch of skills defined, some mcps, and memory filled with useful stuff. I want to use you on a machine accessible over SSH at <host>, can you clone yourself over?”
• red_hare 7mo ago
  Right now I'm working two AI-jobs. I build agents for enterprises and I teach agent development at a university. So I'm probably too deep to see straight. But I think the future of programming is english. Agent frameworks are converging on a small set of core concepts: prompts, tools, RAG, agent-as-tool, agent handoff, and state/runcontext (an LLM-invisible KV store for sharing state across tools, sub-agents, and prompt templates). These primitives, by themselves, can cover most low-UX application business use cases. And once your tooling can be one-shotted by a coding agent, you stop writing code entirely. The job becomes naming, describing, and instructing and then wiring those pieces together with something more akin to flow-chart programming. So I think for most application development, the kind where you're solving a specific business problem, code stops being the relevant abstraction. Even Claude Code will feel too low-level for the median developer. The next IDE looks like Google Docs.
  • sdevonoes 7mo ago
    You think prompting is here to stay? Sql has survived a long period of time. Servlets haven’t. We moved from assembly to higher languages. Flash couldn’t make it. So, im not sure for how long we will be prompting. Sure it looks great right now (just like Flash, servlets and assembly looked back then) but I think another technology will emerge that perhaps is based on promps behind the curtains but doesn’t look like the current prompting. I would say prompting is not here to stay. It’s just temporary “tech”
  • skydhash 7mo ago
    > The job becomes naming, describing, and instructing and then wiring those pieces together with something more akin to flow-chart programming. That's precisely what peoples are bad at. If people don't grasp (even intuitively) the concept of finite state machine and the difference between states and logic, LLMs are more like a wishing well (vibes) than a code generator (tooling for engineering). Then there's the matter of technical knowledge. Software is layers of abstraction and there's already abstraction beneath. Not knowing those will limit your problem solving capabilities.
  • mortsnort 7mo ago
    Can you share a link to your agent class or another one you think is good?
• JBorrow 7mo ago
  Maybe I'm entirely out of the loop and a complete idiot, but I am really not sure at all what people mean when they talk about this stuff. I use AI agents every day, but people who say they spend 'most of my time writing agents and tools' must be living in an absolutely different world. I don't understand how people are making anything that has any level of usefulness without a feedback loop with them at the center. My agents often can go off for a few minutes, maybe 10, and write some feature. Half of the time they will get it wrong, I realize I prompted wrong, and I will have to re-do it myself or re-do the prompt. A quarter of the time, they have no idea what they're doing, and I realize I can fix the issue that they're writing a thousand lines for with a single line change. The final quarter of the time I need to follow up and refine their solution either manually or through additional prompting. That's also only a small portion of my time... The rest is curating data (which you've pretty much got to do manually), writing code by hand (gasp!), working on deployments, and discussing with actual people. Maybe this is a limitation of the models, but I don't think so. To get to the vision in my head, there needs to be a feedback loop... Or are people just willing to abdicate that vision-making to the model? If you do that, how do you know you're solving the problem you actually want to?
• overgard 7mo ago
  I don't agree with the headline of "we're all AI engineers now", but I do agree that AI is more of a multiplier than anything. If you know what you're doing, you go faster, if you don't, you're just making a mess at a record pace. I'm not sure how this sustains though; like, I can't help but think this technology is going to dull a lot of people's skills, and other people just aren't going to develop skills in the first place. I have a feeling a couple years from now this is going to be a disaster (I don't think AGI is going to take place and I think the tools are going to get a lot more expensive when they start charging the true costs)
  • ataraxao 7mo ago
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• t43562 7mo ago
  So far the issue for me is that you can generate more crap by far than you can keep an eye on. Once you have your 50k line program that does X are you really going to go in there and deeply review everything? I think you're going to end up taking more and more on trust until the point where you're hostage to the AI. I think this is what happens to managers of course - becoming hostage to developers - but which is worse? I'm not sure.
• berns 7mo ago
  > I can still reverse a binary tree without an LLM. I can still reason about time complexity, debug a race condition by reading the code, trace a memory leak by thinking. All your incantations can't protect you
• ratrace 7mo ago
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• lazarus01 7mo ago
  < I enjoy writing code. Let me get that out of the way first. < I haven’t written a boilerplate handler by hand in months. I haven’t manually scaffolded a CLI in I don’t know how long. I don’t miss any of it. Sounds like the author is confused or trying too hard to please the audience. I feel software engineering has higher expectation to move faster now, which makes it more difficult as a discipline. I personally code data structures and algorithms for 1 - 2 hrs a day, because I enjoy it. I find it also helps keeps me sharp and prevents me from building too much cognitive debt with AI generated code. I find most AI generated code is over engineered and needs a thorough review before being deployed into production. I feel you still have to do some of it yourself to maintain an edge. Or at least I do at my skill level.
  • ryan_n 7mo ago
    "I personally code data structures and algorithms for 1 - 2 hrs a day" What does this mean? You do leet code problems a few hours a day? Or go through a text book? Genuinely curious.
    • lazarus01 7mo ago
      I am taking a course through a website called neetcode.io It is a clone of leetcode, designed to help you build intuition in a programmatic way, to learn the top 75 - 150 coding questions, common in interviews. Each lesson comes with detailed video explanation, with practice problems. The practice problems too come with video solutions. If you go to the main site, you will see a link to the different courses they offer and also a roadmap. The roadmap organizes the algorithms in a hierarchy, from simple complex, to help you reduce your blindspots, as you build your intuition. I'm nearly complete with the beginner course and will move to advanced soon. For me personally, it works quite well, because I need a human to explain things to me in detail in order to understand the complexity. Hope this helps
• gzoo 7mo ago
  "But guided? The models can write better code than most developers. " <- THIS PART! I get that "senior" developers feel a certain kind of way about it but the truth is that AI really DOES write better code than most developers. I'm not saying ALL developers but AI (at least in my experience with Claude) does the "coding" part much better. They might not be ready to get it perfect yet but they're getting closer every couple of months. It won't be long now. This scares people. I prefer to embrace this AI movement. There is no stopping it no matter how much people complain about it. We all know that. What I'm realizing is that instead of spending all that time actually WRITING the code I have more time to THINK about what I want to do. It reduces the cognitive load :)
• ceroxylon 7mo ago
  > Honestly? oh no... this is one of my "uncanny valley" AI tropes
• inder1 7mo ago
  The "K-shaped workforce" framing is real and probably underappreciated. Senior engineers get more out of AI because they can evaluate the output, catch the architectural mistakes, and debug the edge cases. Juniors using AI to write code they can't read aren't building the debugging instinct that makes senior engineers valuable. That gap compounds over 2-3 years. The question isn't whether to use AI. It's whether you're actually understanding what it produces.
• sjeiuhvdiidi 7mo ago
  Pure, unadulterated, 100% complete political nonsense.
• Kaa708 7mo ago
  hi
• maciver 7mo ago
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• priowise 7mo ago
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• SexySluttyStar 7mo ago
  Hey!! I grew up off the grid without a toilet or a tv. Now I'm researching (not to mention reopening) a series of historic CSC crimes that had been long buried. I lack financial or social resources and AI has given me the tools I need to research quickly and then read case law and examine sources.