32 ms·

LLMs are eroding my software engineering career and I don't know what to do

• Kuyawa 4mo ago
  [flagged]
• jruohonen 4mo ago
  "Except that nobody cares anymore." :-(
• tobyhinloopen 4mo ago
  I think this is the first time I saw someone describe so clearly my concerns and experience with LLMs. I have little to add to it, except that I agree completely. Not sure what’s next
  • drsopp 4mo ago
    Many people share this sentiment, many people don't. Who you belong to depend on at least two things: A) How knowledgable is the AI on what you are working on, B) How well do you wield these new tools to work better than before? (Better here can mean many different things).
    • tobyhinloopen 4mo ago
      (A) I spent day and night using and making tools with and for LLMs. (B) As much as I humanly can.
• applfanboysbgon 4mo ago
  > Maybe I should consider transforming my woodworking hobby into a profession... Whatever your feelings on the future of the industry are, it's hard to imagine you'll find more professional success in artisan woodworking than artisan software.
  • lelanthran 4mo ago
    > Whatever your feelings on the future of the industry are, it's hard to imagine you'll find more professional success in artisan woodworking than artisan software. A small percentage of the market, maybe a fraction of a percent, are still willing to pay for hand-built goods - bonus if it's thoroughly modern but retro (steam-punk keyboards, maybe). Exactly zero percent of the market is willing to pay for hand-built software.
    • witx 4mo ago
      > Exactly zero percent of the market is willing to pay for hand-built software. You took this statistic out of your rear end?
      • lelanthran 4mo ago
        > You took this statistic out of your rear end? We are less than a year into good-enough coding agents, and as of right now there is not a single job opening I see that offers a salary for non-AI output.
        • witx 4mo ago
          [flagged]
          • lelanthran 4mo ago
            [flagged]
            • 4mo ago
• trilogic 4mo ago
  >Of course, I'm still employable because someone has to review the code and steer the robot... We will work for the robots, steering them to steer us.
  • verdverm 4mo ago
    The saying goes... first we shape our tools, then they shape us We are now manufacturing intelligence (why it's artificial) and it shall be interesting to see how it shapes us individually and as a whole. While marching on May Day, the woman next to me made the comment that Ai will force every human and humanity to reflect on what it means to be human, all of us at the same time over a short time period. What makes a human valuable beyond their work? Why do we go to other people when their expertise is at everyone's fingertip? What value are we giving, trading, or sharing in the time we have in this world?
    • trilogic 4mo ago
      Interesting Tony, you seen to have been working for the AI since long time. We others are catching up but eventually all of us will be working for it, as directly or indirectly we are already doing. The "robot" was figurative cause we are no different from a machine, but that is too much for humans to comprehend.
      • verdverm 4mo ago
        I work for myself and the world, not for Ai. It's a tool without identity, but a damn good one that multiplies my capabilities. I anticipate the first bifurcation to be wheat from chaff. Ai is going to do better at a job than say half the people, those who don't care about the effort they put in or the quality of their output. These people will have to come to terms with their mediocrity or blandness. I'm still unsure what the good ideas are for when we reach a world without labor scarcity.
        • trilogic 4mo ago
          <I'm still unsure what the good ideas are for when we reach a world without labor scarcity. It should be real creativity the final goal to this life optimization. For now many of us need to fight for survival, for food, shelter... so is a bit difficult to be purely creative. But is also true that given all the benefits (taking off the survival instinct) makes creativity obsolete. >I work for myself and the world, not for Ai. Yourself really? Start by defining "I", "work" or "yourself"... then we may proceed to the next LOL
• leoncos 4mo ago
  The last sentence in the article is correct: "Maybe I should consider transforming my woodworking hobby into a profession." As an AI optimist, I think all forced labor should eventually be done by AI. People can then spend their time pursuing their own hobbies. Just as many people still play Go after AlphaGo appeared, because they genuinely love the game. In the future, coding may return to being an art form. People will no longer focus on utility alone, but instead on the enjoyment of the process of writing code itself.
  • mahogany 4mo ago
    > As an AI optimist, I think all forced labor should eventually be done by AI. People can then spend their time pursuing their own hobbies. Just as many people still play Go after AlphaGo appeared, because they genuinely love the game. And what sort of economic system do you imagine will be in place to support billions of people being able to just play Go all day long? How do you imagine the large capitalistic global powers transitioning into that state?
    • juleiie 4mo ago
      I think that huge deflation will follow for everything except land value. If automation makes producing food so cheap that it is almost free than it is ridiculously easy to acquire it. Similarly automated construction. The way I see it the economy will point towards outer space. That’s where most jobs and flow of economy will be. However most people will have 10x times uplift in purchasing power compared to today so their relative poverty will be ridiculous for us to call it the poverty but they will still think they are poor and troubled. Generally I don’t think it will be utopia for the people living in that moment but if you look from medieval times at today it looks like utopia for serfs from the past. You however wouldn’t call it an utopia because your standards grew as fast as your purchasing power. I think that rich and poor will be separated by accessibility to anti age treatment and other bodily improvements. The tragedy of the poors in the future will be living measly 80 year old life like a today millionaire and that will be considered lower class. Those people with wrinkles we don’t want to look at because of uncomfortable pangs of guilt.
• volume_tech 4mo ago
  [dead]
• litver 4mo ago
  "Except that nobody cares anymore." Noone (from mid-management) cared about it also before. You hit the deadline, get promoted and leave the technical debt to the next one. Even if you're the one to deal with it, you set up the next project, get the budget, prioritize the issues etc. Not much changed in this regard with LLMs
• phase_9 4mo ago
  The glory days are over. In the future, one software engineer will be able to support multiple product areas much like how one HR team can support 1,000's of employees. LLMs have made domain knowledge and reasoning "cheap"; it doesn't matter if the output is lower quality - look around you for countless examples of where cheap wins and "cheap" continues to improve. Good luck out there; we will all need it.
  • dominotw 4mo ago
    This has been said millions of times but yet you felt the need to say this again. maybe our jobs are safe :)
  • emodendroket 4mo ago
    > The glory days are over. In the future, one software engineer will be able to support multiple product areas much like how one HR team can support 1,000's of employees. I mean, it seems within the realm of possibility that much more productive software engineers make more and not less money.
    • pjmlp 4mo ago
      It is already the case that outside SV like scenarios, most devs are plain office workers like everyone else.
      • emodendroket 4mo ago
        I don't see how this proves or disproves what I said. Can you elaborate?
        • pjmlp 4mo ago
          The salary levels are not the values many imagine, and definitely aren't going to go up.
          • emodendroket 4mo ago
• kubb 4mo ago
  I secretly wish LLMs take my job away because I'll get about two years of unprogrammed rest, which I absolutely will not take of my own accord. But it's unlikely to happen.
• lelanthran 4mo ago
  To me looks like, if we're not collectively careful, civilisation will soon be on a path to an evolutionary dead-end. Anything that can replace a deeply experienced s/ware engineer can replace anyone in the employment stack, meaning that only the owners of capital will be left, and they too will soon fade as the economy falls off a cliff and money has no value, because the only value that money has is the value of a human backing that, with thought, with ideas, with human output. Whether you like it or not, "Economic output" is just a different phrase for "Human output that is valuable". When all human output is valued at the fractions of a penny per month of work, there is no future.
  • p-e-w 4mo ago
    > Anything that can replace a deeply experienced s/ware engineer can replace anyone in the employment stack Nope, just knowledge workers. We’re decades away from automating many manual labor professions, even “unskilled” ones. Turns out brains just aren’t as special as we thought.
    • lanfeust6 4mo ago
      The major blocker for manual labor automation in that fashion is cheap energy. China is ahead of the pack with the States' weight behind aggressive expansion of solar tech, and still can't do that.
    • theshackleford 4mo ago
      > Nope, just knowledge workers. Nope, just a specific kind. Those who developed and cultivated only a very specific skill set at the expense of all others. I used to think being a generalist, and having persued technical roles with a people facing element was to my detriment, but it’s turned out to be the best decision I ever made.
      • tempest_ 4mo ago
        I had the opposite thought. Being a generalist was very useful to me 5 years ago. Now AI models have made everyone a generalist. That wide but not terribly deep skillset was immediately devalued by the AI models. You can argue that the models fuck up 20 percent of the time, or that they make poor code but there is a massive part for the industry that is totally fine with that and I think people ignore it to their detriment.
• cassianoleal 4mo ago
  > The company is now hiring again for a few roles and domain familiarity is not a strong differentiator anymore. We used to list "Software Engineer - Area". Now it's just "Software Engineer" and the team assignment comes after the offer is accepted. > Of course, this is good for brilliant engineers that never had the chance to get deep into the domain and now have better chances at getting a job, but it's also sad to think that other brilliant engineers that spent their lives collecting domain knowledge are now competing on the same lane. If the author's vision of the future is correct, then competent software engineers are safe. Domain knowledge can be learnt much quicker than how to apply good engineering principles. Engineers whose main competitive advantage is domain knowledge are probably not that brilliant at engineering. They might still find employment in other areas of the industry where they accumulated domain knowledge.
  • hliyan 4mo ago
    > Domain knowledge can be learnt much quicker than how to apply good engineering principles. There was an entire thread a week ago about how domain expertise has always been the real moat: https://news.ycombinator.com/item?id=48340411 https://news.ycombinator.com/item?id=48340411
    • 9dev 4mo ago
      And I'd still question it. The experience of just… knowing how a good architecture looks like without being able to really put it in words is what makes a good engineer to me. These people can pick up relevant regulations or industry terms and deliver value quickly enough.
      • mattbee 4mo ago
        How is "without being able to really put it in words" a mark of experience? Surely an engineer should be able to justify why an architecture should be arranged the way it is!
        • kloop 4mo ago
• ieie3366 4mo ago
  Yes this has been my experience as well. It's crazy the crazed anti-AI people yelling with foam with their mouth that it's useless, meanwhile Claude for me at work oneshots complex bugs in a massive project with a 95% success rate. And the customer happiness survey has never been as good as it's now btw
• doright 4mo ago
  Realistically, what should we have done instead? Not invent LLMs? What happens when a couple thousand people invent the next disruptive technology and even more of the population loses their jobs? It seems like new tech is something most of us have to lie down and accept as the new reality each time it's invented, barring full-scale rioting. Much as with the Cold War.
  • bluefirebrand 4mo ago
    > Realistically, what should we have done instead? Not invent LLMs Yes, obviously we should not invent technology that seems likely to disrupt society out of existence
• iandanforth 4mo ago
  Wut? I pilot LLMs all day but there's no way in hell I'd agree to be at the helm of a finance product. That first pillar is still there. Maybe the author isn't aware of the impact they have, but I know, with the evidence of reverted PRs, that when I step outside my area of deep knowledge I can no longer call BS on the agents. Our most capable agent, with access to the same kind of distributed systems the author talks about, is regularly wrong, frequently myopic, and just outright dumb constantly. It's the expertise of engineers on the team that push it back on track.
  • keyle 4mo ago
    [flagged]
    • iandanforth 4mo ago
      "I ended up working in software development roles in the domains of finance, bookkeeping and payment processing, where I had great autonomy and a close and candid relationship with Product Managers and stakeholders. I learnt a lot about the domain and how to effectively write programs for it: PCI compliance, double-entry ledgers, escrows, reconciliation, payment lifecycles, bank transfer idempotency, etc. It was, then, obvious that I should focus my career on becoming an expert on that domain to stand out as a professional and differentiate myself in a field that showed signs of an increasing need for domain specialists."
    • stuaxo 4mo ago
      The backend is the bit that "does stuff" so it's the part that needs to be correct. He said "Last year, I got hired by a company in the finance workspace.".
  • jalev 4mo ago
    Unfortunately every software related industry is embracing LLM/Codegen. Your banks, fintechs, insurance. Everyone. Your concerns are the same I'm having, yet it's regularly dismissed or hand-waved away as "don't worry about it the delivery velocity/ROI is worth it"
• snarfy 4mo ago
  The direction I'm given is to take humans out of the loop. As much as possible. Everything AI. Automate everything. If you are in the loop you are overhead.
  • senectus1 4mo ago
    this is the exact WRONG approach. AI is a power tool not a fucking human replacement. Though I doubt I'm telling you anything YOU didnt know...
    • snarfy 4mo ago
      Like I said, this is the direction I'm given. :|
• nkzd 4mo ago
  I am also feeling anxious. I lucked out by having natural inclination towards software development, career which can provide good upper middle class life to anyone. But I feel like writing is on the wall. If I don’t find a way to pivot to something else, I might experience class migration, but in the opposite direction this time.
  • juleiie 4mo ago
    It’s a good time to save and move out to a cheaper country to buy money generating assets here. It’s not easy but if you have at least one million dollars in investment money, it’s arguably wiser than staying in US that penalises such passive lifestyle heavily. Sooner or later some medical bill will leave you bankrupt. Unlike in EU.
• jchw 4mo ago
  Same boat here, just a couple years more experience. Current LLMs are still kind of shit at actually programming so many jobs do still care to have professional programmers. However, I think it's evident that if things stand where they are, employers will care to have far fewer of them, at least of highly paid highly experienced programmers. If this is the state we're in with LLM adoption when they can't help but create the same helper functions 15 times, god knows we're screwed. So we should probably work on clearing out our debts and figuring out what else we might want to do with our time, I reckon. I'm still going to try to do a good job. I'm still trying to learn the best effective ways to apply current LLMs (Right now I still prefer to mostly write code myself but have been using LLMs to bang code into shape via iterative code review; this is a way to exploit LLMs to make better code, especially applicable if your velocity was already good.)
• ThrowawayR2 4mo ago
  He says that taste doesn't matter and it hasn't in the past. However, in an era of "extruded code product" (by analogy to https://tvtropes.org/pmwiki/pmwiki.php/Main/ExtrudedBookProduct https://tvtropes.org/pmwiki/pmwiki.php/Main/ExtrudedBookProd... ) automatically generated by the truckload at negligible cost, the differentiator for software developers will necessarily be the ability to create a product that doesn't reek of extruded code product, i.e. the things like quality that he labels taste. (Whether any one reading this, myself included, survives in the industry long enough to reach the other side of that transition is a different question.) [EDIT] The reason I use books as an example is that 4.2 million books were published in 2025 (https://ideas.bkconnection.com/10-awful-truths-about-publishing https://ideas.bkconnection.com/10-awful-truths-about-publish...); 3.5m self published (with most likely LLM assisted or wholly generated) and the remainder traditionally published. (That's ~9,600 new self-published books a day.) Who actually still sells enough copies to make money in this paradigm and why offers hints as to where the software industry is likely headed.
• discreteevent 4mo ago
  This anonymous article is likely more FUD from the AI industry. "Just give up,you can't beat the machine. Please go quietly, we want to take your place and it's easier for everybody if you don't resist because you believe it's pointless" 'Maybe I should consider woodworking' - Fuck off.
  • peheje 4mo ago
    resistance is futile
    • xpct 4mo ago
      It's futile to race against the money hungry capitalistic machine, but it's not futile to steer your own career into work that's more lucrative or is more enjoyable, be it with our without AI tools.
  • deleted 4mo ago
    [deleted]
• audriusber 4mo ago
  [dead]
• variety8675 4mo ago
  The market still seems to be hot for roles that provide leverage like platform engineers and Staff+ engineers
• enraged_camel 4mo ago
  Code quality and architecture still matter, because they also make it easier for LLMs to reason about the system. That said, Opus 4.8 and Codex 5.5 both can write code that is higher quality than your average engineer. They are not quite there yet in terms of code re-use, but I think that's a solvable problem.
  • kristofferR 4mo ago
    Running a couple of "scan for potential refactors"/"any duplicated code" prompt threads is already a long way there.
  • xpct 4mo ago
    Regarding code quality, the largest issue I've run into is pollution that stems from committing too much unfiltered LLM code. They introduce some type of structures into the codebase that are hard to read for a human, then start reusing them or use them as example to create new ones, then when a human needs to quickly hop in and make changes, it's not as easy to do.
• keyle 4mo ago
  I sympathise with the author being in the same boat, largely. I just want to emphasise a point... Calculators give 100% correct answers and yet we still hire accountants; for the simple fact that we don't want all to be accountants. People will hire software engineers for the simple fact that they do not want to be software engineers.
  • dominotw 4mo ago
    funny i was able to do all my taxes this year with ai help and not needing accountant.
    • dgan 4mo ago
      Lol thats brave on your part, given that a mistake can cost thousands and you have no accountability (punch!) from an LLM
      • sethammons 4mo ago
        Your account has no accountability. Do your taxes wrong and the tax payer is liable. Ask me how I know.
        • dgan 4mo ago
          At least he has a reputational/commercial risk. LLM has none
      • goosejuice 4mo ago
        In the US, all you need to work in tax prep is a high school diploma and most individuals are not worth the cost of an audit. I wouldn't say it's particularly brave, in fact LLMs are probably better at identifying mistakes than most tax payers. The % of Americans using a CPA to file taxes is fairly small.
        • dinkumthinkum 4mo ago
          If you go by percentage of Americans, well consider the percentage of Americans that are actually net taxpayers.
• an0malous 4mo ago
  There’s one force where software engineering is being automated by LLMs, but the other force is that there isn’t really much more software that needs to be built. Even before AI coding became big, back in 2021, we were already in late stage SaaS territory where each new idea was an increasingly minor variation of an existing idea. There were no new GitHubs, Herokus, Stripes, Salesforces, Instagrams, Reddits, just variations of those for more specialized markets. It’s really unfortunate that AI hasn’t raised the ceiling on the space of possibilities as much as it’s raised the floor on how much can be automated, we’re all getting squeezed in the space between.
  • 9rx 4mo ago
    > there isn’t really much more software that needs to be built Yup. Most everything we need was already built in the 1970s. Programmers have been kept busy because we've kept introducing incompatibilities into the mix, like DOS programs needing to be rewritten for Windows, and then the web, and then mobile. And now they're being rewritten for AI platforms. It may be giving the squeeze due to being the first platform that will also help with the rewrite effort, but it is also the thing that kept the industry going. As you point out, there wasn't any work left to do until AI showed up.
  • mike_hearn 4mo ago
    Can't disagree more! There's bottomless demand for more software. Here's a few examples I encountered just in the last few weeks that wouldn't be feasible before LLMs: - More localism. Are you afraid of being cut off from tech by some future US government? Now it's feasible for your local culture to grow its own office suite, operating systems, Active Directory competitor etc. A less interdependent world with more competition does have its advantages. - The building management company for my apartment sucks. Basic problems go unfixed because they appear to suffer extreme labour shortages and serious problems with flaky labour e.g. employees that just randomly go AWOL in the middle of conversations without bothering to tell anyone. A lot of the work of these employees is actually just coordinating and paying contractors in response to problem reports, something that can now be automated by AI ... but they haven't done it yet. - I just finished assembling some flatpack furniture. Every time I do this it reminds me why IKEA dominates the market. Other furniture companies give the strong impression they don't usability test their instruction leaflets. This should and could be massively better: AR assistance during the build would be great, AI stress-testing instructions to verify they make sense would be great, AI checking every packet has the right number of components in it would be great. And there are lots of furniture companies out there. They don't all need to use a single SaaS to do this. + in general robots will require tons of software/models to make them do tasks usefully, especially as they lack training data. That's just a few examples of places software could have made my life easier in just the last few weeks.
• gdiamos 4mo ago
  What I tell my team to do is to drop using so many cloud saas apps, and build more themselves using LLMs. I’m not planning on firing people, but I am planning on building more, using more tokens, and less app subscriptions. One aspect of building that doesn’t erode is human values. LLMs don’t create software with zero direction and although I do have 12 agents building constantly, I run out of attention to increase that to 100.
  • dominotw 4mo ago
    you dont need to vibe code shitty apps. you just need to learn how to use apps like codex, claude desktop.
    • gdiamos 4mo ago
      I don’t get it. That’s what I am using.
  • zaphirplane 4mo ago
    How strange or at least unintuitive. Buying should be cheaper than creating for a customer of 1
    • gdiamos 4mo ago
      Think about the worst enterprise SaaS apps you have used…
      • zaphirplane 4mo ago
        rewrite SAS, salesforce or SAP, will never have the breadth and business know how
• mactavish88 4mo ago
  > I still have one pillar standing, though: code quality and software architecture - what's now being reduced to being called "taste". Genuine question: what exactly is "quality"? It's something I've been trying to understand for a very long time. It seems like it's entirely contextual, and it has both subjective and objective facets (the latter only for quantifiable things, and still entirely contextual).
  • mmcnl 4mo ago
    Good question indeed, I think quality matters less these days because it's trivial for an LLM to increase code quality. Quality is usually observed from a human perspective. But in my experience, codebases that humans would judge as "low quality" are actually fine for LLMs. They don't have as much trouble as we do with spaghetti code. They don't have problems with readability or obscure syntax, it's all perfectly fine for them. They don't care about indentation either. Also it's really easy to increase the quality of the code base. You can just prompt to add unit test coverage and it will. You can prompt the LLM to handle edge cases better and it will (you don't even have to specify which, it helps, but it's optional). If you want to have better separation of concerns, just ask the LLM to have more separation of concerns and you'll have it. Documentation lacking? Just one prompt away. More robust build pipeline? You get the idea.
  • mrkeen 4mo ago
    Off the top of my head: If you're using the product, and you want to question or debug what's going on, you can: * Jump directly to the single relevant part of the frontend responsible * Likewise with the backend. The layout and naming of the code should scream its purpose. * Once you're looking at the code, it should be trivial to run it, right now, instantly, in unit test, or cli. You shouldn't need to stand up a database to see whether your code rounds taxes the expected way. The system contains its own checkability. You can, for instance, just sum up all the incoming money and outgoing money and see if your balance is correct. (It's not enough to have good tests today, if you're working on data that was incorrectly calculated and stored yesterday)
  • dahart 4mo ago
    Ah the age old question: what makes something good? I think you’re already describing it well at a high level; context matters, and there are multiple axes to consider. But that’s extremely vague and doesn’t help you identify or measure quality, so it might be worth listing as many specific axes as you can. Maybe ask the same question about other things. What makes a good guitar? What makes a good chair? What makes a good airplane? What makes a good book? What makes a good song? What makes good art? Each of these has a long list of very specific goals and concerns. And to help define the boundaries, also ask what makes something bad, and what makes something mediocre. Code quality starts with functionality. Does it perform the stated requirements? Does it have testing in place to catch breaking changes in functional requirements? That’s the basic stuff that probably isn’t part of “taste”. A lot of code quality goals center around how code changes over time, and beliefs about designing to avoid functional breakage. For example you can ask things like does the code use minimal dependencies? Is the code organized into clean classes/modules/functions that each have a single clear role? Is the API easy to read, understand, and use? Is the API hard to misuse accidentally? Is all the code easy to read? Is there documentation, and is the documentation useful, and more than a list of contents? Is the code self-documenting? Is the code efficient, both in how it executes, and in its use of code itself? Is the code designed so that it won’t fail when someone runs it with different sized types, or a different compiler or execution environment, or on a different architecture? Is the code surprisingly elegant and fun to use? Those are just the beginning. There are of course more layers of application-specific and environment-specific and audience-specific qualities. The good news is that quality depends on your own goals, you can decide which aspects of taste matter to you, and ignore the ones that don’t. It’s fine if your taste & goals change over time.
• mohsen1 4mo ago
  Maybe just maybe here in HN we are in an echo chamber that is convincing us that there is a theoretical limit to how far the LLMs can make progress. It’s not unthinkable that LLMs will make better overall architectural decisions or follow the good practices better or understand the problem in bigger picture (more access to company/product context already makes a huge difference) Lots of jobs have been automated away and careers based on those jobs faded away in history. Maybe in near future there won’t be a ton of opportunities for software engineers in the traditional form. I’m also embracing for that future. There were people called calculators that did manual calculations in the past. There were people hand weaving all the fabric. There were people painting cars in the factory. All those jobs are gone for the most part. We are sitting here portending there is going to be demand for software engineers managing those engineer robots but let’s be real. The demand for software is not increasing at the rate software engineering is becoming efficient using those robots. Some (many) of us have to find new careers.
• taintlord22 4mo ago
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• torben-friis 4mo ago
  My career path is suprisingly similar to the author's. Weirdly enough, what he takes as the first pillar to fall is the one I see most undamaged currently. LLMs routinely fail at our business specifics: Local tax regulations, particularities of the accounting process, specifics of our ledger implementations. They're great at refactoring, translating between languages, tracing bugs on existing code even, but there is always many things subtly wrong iterating and expanding our domain. This might be because the companies I worked for happen to be tackling complex domains precisely for moat-building reasons. They stay in business explicitly because there's not a book out there you can read to build a clone, the knowhow stays inside. Also, a fintech whose managers recommend speeding up design docs with AI sounds way too careless to be in the money handling business. It's way, way too easy to end up with millions incorrectly allocated, particularly if you deal with high volumes of small transactions. These bugs are always a bitch to deal with because correcting the logic is just step one, you then have to correct all the wrongly calculated data in immutable DBs, move around the red tape and client comms, and your fix is bound to become a gotcha that new features and observability have to take into account ("remember that there's a bump in the data in february 2 because we had incident X".)
  • enraged_camel 4mo ago
    >> LLMs routinely fail at our business specifics: Local tax regulations, particularities of the accounting process, specifics of our ledger implementations. My company also deals with a lot of complex regulations and domain-specific system implementations, which AIs used to struggle with. We were able to solve the problem with well-organized claude.md/agents.md files. On top of that we also implemented supermemory.ai, so newly made decisions are always recalled by AI agents when starting new sessions.
  • worldthruword 4mo ago
    > LLMs routinely fail at our business specifics: Local tax regulations, particularities of the accounting process, specifics of our ledger implementations. Would a skill which forces you and LLM to reach a shared understanding of the product features and the regulations those features are supposed to capture be of help here? The main idea is we provide documents to the LLM and it asks lot of questions which clear ambiguity and possible misconceptions the LLM might have. I would suggest please take a look at skills. They are really helpful. https://www.youtube.com/watch?v=6BB6exR8Zd8 https://www.youtube.com/watch?v=6BB6exR8Zd8
• cejast 4mo ago
  > All my finance and payment domain expertise, all the debugging intuition and distributed system knowledge earned through hours of sweat and tears, is now promptable. Is it really though? Access to information is quicker, but you still need to know what ‘good’ looks like to leverage it effectively. I can prompt my way to a medical diagnosis, but I’d still want to run it by a doctor.
  • zmgsabst 4mo ago
    I’ve found it extremely hard to get LLMs to exit the basin of your current knowledge. One of my tests for new models is to ask about a concept I already know the mathematical model for, but as if I don’t. So far, they all answer the same way: 1. Convoluted explanations about how it kinda-sorta is common terms. 2. If you follow up with the correct mathematical term, it immediately claims that’s correct and the right way to model it. 3. If you ask it why it didn’t use that term for your question, the LLM gives some version of explaining that it tried to match your language. I have no choice but to assume the model behaves similarly other times — and that I am largely trapped in a basin of my own ignorance, when using LLMs.
  • slyzmud 4mo ago
    I don't think that's a good analysis. If the LLM is wrong and gives you a wrong medical diagnosis you end up hurting your health. If an LLM gives you a wrong debugging answer you've just lost 5 minutes. Software engineering is the only knowledge work where mistakes are usually inexpensive except for data breaches. Outside for that nobody cares for bugs. That's not true in most other knowledge jobs. If a lawyer uses AI and hallucinates something there is a legal problem. If someone vibecodes an app and crashes, it can be fixed with more AI and try again
    • cejast 4mo ago
      That’s my point though? Debugging a 5-minute problem is in the shallow end of the spectrum, the real complexity sits where they lean on their domain experience. Finance and payments software mistakes can absolutely be expensive.
• Aerialoo 4mo ago
  I think this experience is universal. The answer is the same as always has been - develop skills that are becoming most important. Right now that is (at least from what I can see): - Data analysis, data pipelines, models, etc. - Tacit business knowledge - architecture and design patterns (always has been, but now the scale os larger so this is even more important) It's harsh but nobody cares if a model or a human made a system. The "good" bits are that now automating anything and providing value from software is much easier. If I have an idea or a nitpick somewhere, I can just do it, up to a limit (which is quickly rising). I have always been a generalist and generally interested in a very wide array of things, and this period has been the most exciting in my engineering career (13y now). Learning about anything is so frictionless, looking back at my first learning experience - picking up a fat C++ book and spending days/weeks debugging, while I can romanticize that, I would never go back. I can also now write software solo or with an extremely small team at a huge scale in comparison, and that is super exciting. A lot of skills that took sleepless nights to acquire, they are "gone", but I still don't regret anything or wouldn't go back. Their "usefulness" has degraded, true, but this has always been the case with engineering. We are now able to spend much more time thinking about utility rather than low level implementation and imo that's great. We have many challenges ahead of us, and there are seriously bad things, the biggest one I have experienced is the hours are increasing and mental load is vastly increasing as well. As capacity, speed and leverage increases, so do expectations and hours, and that is probably a social problem. Sorry for the unstructured stream of thoughts, and this is just an opinion (quite an unpopular one I believe), I hope your distress decays away for a new excitement and new opportunities. Thanks for the article .
• smetj 4mo ago
  > I'm just another off-the-shelf engineer now You're wrong there. You are capable of judging the outcome of the llm. > But I don't know what to think about the long-term. Don't you think it all has taken long enough. When I look back at the beginning of my career and compare what we do now ... I cannot shake the feeling we're essentially still solving he same problems and we have accepted that as being normal. Complexity skyrocketed, (abstraction) layers got added but the needle didn't move exponentially together with that. I think the IT industry as a whole gets what it deserves, thinking that we would remain the maze masters of the mazes we create. > Maybe I should consider transforming my woodworking hobby into a profession... I'm looking for 8 (affordable) oak panel doors with the exact same measurements as my current doors so I can replace them. That shouldn't be too hard to find you'd think right?
• dukeofdoom 4mo ago
  So instead of a programmer, you become a software designer. I recently came across the idea of building fantasy for the player (in context of games), but now that I think more about it. Onlyfans, is just that. Advertising, Beauty products, novels, games, TV shows, and so on. You're really just creating / selling a fantasy for vast majority of people. Most people will never lose that 30 lbs, but you can sell them all kinds of products to fuel the fantasy of them losing that weight, being beautiful, rich, healthy and so on. So an LLM replacing the need for you to write every piece of code, is actually kind of freeing. You as a a former programmer, should embrace your new creative role. Writing code, at least for me was always slow and tedious. I just want to be able to express the ideas I have, so LLMs just make it possible to build things I never could otherwise.
• dmos62 4mo ago
  What work remains valuable when implementation becomes cheap? How about moving closer to ownership? I think that in a product-centric or mission-centric perspective, effective automation is good, because it frees you up to do other important things. E.g., in gardening, time spent weeding, is time not spent surviving slug armageddon.
  • deckar01 4mo ago
    Businesses like a record of reliability, so devs going solo with AI is going to be a hard sell. I think we will know that AI is actually good enough when these AI providers start absorbing project management companies and hiring contractors to use their product instead of selling subscriptions.
• 3D39739091 4mo ago
  The issue is that the people evaluating you don't know the difference between legit domain expertise and pure bullshit.
• viapivov 4mo ago
  I wonder how do people use LLMs so it does not hallucinates. Like 90% of the time the code is impeccable, but the remaining 10%... Let's say I determine the expertise by how well do people act of these 10%. For me, the first pillar is still there, but not in a good condition
  • Lionga 4mo ago
    Easy just add "Make no mistakes" to the proompt, clear skill issue. In reality people who use LLMs so it does not hallucinate are the ones that just have to little knowledge to actually see when it does, because LLMs do and they always will. That is the only thing you can get with a stochastic word predictor.
  • naveen99 4mo ago
    Just pretend you are working with a buggy api with poor misleading documentation. LOL Check your assumptions.
• vagab0nd 4mo ago
  I used to be in the "AI will soon do all your thinking for you" camp, but I was overlooking a scenario: sometimes the gap between what you understand and what you're trying to achieve is so wide that no prompt can bridge it. Simply asking "what's the right question to ask?" doesn't feel enough, no matter how advanced LLMs become.
• normanthreep 4mo ago
  computers are made for automation. programmers were always working on automating things, making other things obsolete, and we have been killing jobs for decades. did you really think we would suddenly stop when it's your job? i'm happy this is happening, genuinely giddy
  • senfiaj 4mo ago
    But this raises the barrier to entry into programming if LLMs are capable of doing the vast majority of junior/mid level tasks. This can ruin the lives of many average people for whom programming was one of the few truly possible jobs. I have a friend whose initial interests are not related to IT and he is not particularly passionate about programming, but it still brought him a decent income (unlike the profession he was passionate about). This is the people I'm talking about, they need some fucking stable job that brings income.
• bix6 4mo ago
  > But now the market is shaping everyone into becoming a generalist. This is interesting because in my field of VC everyone says generalists are dying.
  • deleted 4mo ago
    [deleted]
• pjd7 4mo ago
  Engineering hasn't gone away, you're now just directing things at a higher level. You are now a architect & manager (but you're managing agents not people). Who sometimes has to deep dive & mentor a agent on solving the right problem.
• deanc 4mo ago
  It's not just about it taking the technical competence away from our job, it's taken away the joy [1] which I wrote about. I feel like many of my peers are beating around the bush on this topic and in denial. Even if you accept it can do a large portion of the technical part of our work, we are just supervisors at this point making sure it doesn't do any stupid shit. What is the point? Where is the fun in this? Where is the challenge? At least I have enjoyed building my career over the last 20+ years and building software, but find little joy in the work I'm doing now. I think we're going to see a massive exodus of folks leaving the profession and a huge mental health crisis, long before the folks working in other sectors realise what's hit them. [1] https://deanclatworthy.com/2026/02/09/the-joy-of-programming/ https://deanclatworthy.com/2026/02/09/the-joy-of-programming...
  • neta1337 4mo ago
    The challenge is enduring the hype and pulling through until enough people left the field so we can make more money
• skepticATX 4mo ago
  The reason that I’m looking for an out is that it’s turned everyone I work with into imbeciles. Nobody wants to think anymore. Coworkers are now just intermediaries for their LLMs. Talking to them is just talking to the LLM - sometimes directly copied and pasted, sometimes minimal effort to conceal what they’re doing. It is so disheartening. And the sad part is, LLMs are incredible and can enable you to do much better work if you can stay in the loop, and stop focusing only on shipping speed. But from what I have observed, very few people care to do this. Who cares about substance when middle management thinks your productivity is 10x?
• tsouth2 4mo ago
  I've wondered about this a lot. I am brand new to software engineering, fully powered by AI coding. Traditional software engineers have to pivot hard or the are going to be left in the dust. The slow, methodical, take two days to put a change on a production site approach are over. I'm shipping exponentially faster than a co-worker who hasn't embraced AI yet.
  • xpct 4mo ago
    As someone who's not a programmer, how did you discover HN?
    • tsouth2 4mo ago
      I've came across HN several times over the years, I've been in IT for 15+ years working at MSPs. Never had a reason to post until now. I got assigned a ticket at work that I ended up using AI for, and I haven't stopped building since. I get where all the hate on vibe coding comes from, but if used correctly, AI is a strong force for improvements and efficiency. Used incorrectly, you get slop without a doubt.
  • Anamon 4mo ago
    Come back to tell us how that's been working out 6 or 12 months from now. You describe yourself as a vibe coder. In other words, you don't understand what you're shipping, and somehow that doesn't seem to concern you. I'm not worried about your coworker, I'm worried about your employer allowing you to deploy a mess without requiring someone with knowledge to have challenged it, and I'm worried for your customers.
    • tsouth2 4mo ago
      [flagged]
• ohyes 4mo ago
  LLM is a powerful tool but it still doesn’t have the context that a person would have. A million tokens is a drop in the bucket compared to the overall context that the person guiding the LLM needs to keep it on track and being productive. If you’re not a good engineer and you don’t have the domain knowledge, your token costs will be very high for whatever gets shipped, because you won’t be able to provide the context necessary to prompt machine efficiently. Claude will still very often hallucinate bugs, explanations, domain requirements, that have no basis in reality. It will offer fixes and improvements that are pretty standard but not optimal. This is correctable if you catch it, but you need to review every line of code and comment, because in addition to being obviously wrong, it is often very subtle in the wrongness. For every bit of “slop” there is almost microslop, the places where it just kind of confidently guesses… and doesn’t tell you… but sometimes is correct anyway. The “problem” is there’s less low hanging fruit. You have to know a lot to add value beyond being a middleman gating the slop. You have to really pay attention to the details to find some of the errors that it’s making.
• demorro 4mo ago
  I still struggle to accept this when my colleagues are producing implementations with AI assistance that are consistently broken and don't do what they think they do. As yet I can't square this circle, no one is better at their job than they were before. I feel that I am faster and better, sure, but trusting self perception would be an absurd thing to do.
• GreenSalem 4mo ago
  Software engineers are fungible commodities, in the wake of the LLM.
• mawadev 4mo ago
  I have no idea what you guys are up to, but it is just a job, it is just a role, it says nothing about you or who you are and it is not tied to your meaning. If you make it so and your perception is aligned with that, then you are not in control of what happens to you. What kind of slavery it is to give other people so much control over you is crazy
• gaiagraphia 4mo ago
  There's a certain irony in masters of automation lamenting that their roles are being automated. I wonder whether the jobs their efforts eroded in the past ever got the same thoughts... Programming, logic, etc are skills and toolkits. The optimal state of society is everybody being able to apply them, not just the enlightened compsci caste. There was a time in the past where scribes were paid nice cash for their efforts, too. I guess the lesson to learn here is treating a toolkit as an identity and job for life. By virturee of the essence of the job itself - if the tool gets cheaper and more widespread, it's aactually success, not betrayal.
  • tines 4mo ago
    You say that the optimal state of society is for everyone to apply programming and logic etc. but the obvious final result of these developments is that no one will.
    • gaiagraphia 4mo ago
      Maybe the artform will be lost, but surely humanity will inherently be more 'logical' and systems driven afterwards? Maybe using writing as an analogy is flawed, but most of humanity having 'writing' as a core skill did enable many other things, even if oral storytelling cultures suffered at its hand. At its core, tech is all about breaking through inefficiencies and barriers. Does it matter if people can't code python if people demand government systems be frictionless in the year 2500?
      • jplusequalt 4mo ago
        Sincerely, how is prompting an AI to build software for you building "logic and systems thinking"? The thing many people are ringing the alarms over is the offloading of critical thinking and knowledge work to LLMs.
        • gaiagraphia 4mo ago
          Being able to program isn't the end game of critical thinking. Programming languages are just a way of representing the processes. The thinking underneath was always more important, and there's now technically more time freed up to focus on that. Billions of people now have access to tools which will aid them in reasoning through complex problems without needing a $100k CS degree. Of course some people are using LLMs to get recipe inspiration, but others are now empowered to do things which were impossible for them before. I personally think the alarm ringers are mainly the privileged elite who are scared of their moats beyond filled in. LLMs have effectively broken down the gates of access to knowledge. In a diverse world, having more people being empowered to do more things has to be a net positive.
• gbro3n 4mo ago
  AI is beat thought of as an exoskeleton, you'll be at a huge advantage if you learn how to use it properly, and you will, unfortunately fall behind if you don't. I still think we're going to need people who can reason about code, and the amount of code to reason about is exploding in volume. Think of it as doctors having access to better drugs and techniques - they can can cure more illness, but the bar and expectation of what they can do will just raise. And doctors are still well paid, because what they do is important and needs doing well.
• sreekanth850 4mo ago
  >Agents do a really bad job at keeping codebases organized. If you do a disciplined way of development with agents by keeping all Documentation in markdown format, repo structure, Decision records and architecture, they do absolutely organized. Every new module should be documented and the editor configuration and coding patterns can be given as reference. this worked well for me. and it make enhancements, extensions development without any big troubles.
• himata4113 4mo ago
  While LLM's are beyond junior level at this point, they're still just that. I don't really agree that the first two pillars have been affected. I've shared a story before that between now and 2 years ago a developer who solely relied on AI has produced the same hot garbage instancing system within the same time period. For example back in my day in 2 years I went from writing a system that struggled with few hundred players to one that could handle thousands and far beyond that. The person using AI 2 years ago wrote a system that didn't work and wrote a system 3 months ago that doesn't work. Everyone is saying how great AI is, but they're missing that the driver is just as important AI wouldn't be able to achieve any of this without capable (often seniors) using it and giving it guidance. It's really a difference between "it works" and "it works without flaws". Of course AI can produce things that also "work without flaws" with solved problems and someone "recreating" something that already exists with AI is not that special, a junior developer could accomplish the same thing given the time. But I do agree that AI becoming part of performance reviews and all that is producing more productive developers which is going to drive the cost way down. In a way AI is stealing from a developers salary and giving it to the AI companies which is pretty ironic considering how cold developers seem towards artists.
• cmiles74 4mo ago
  I’ve been using Claude Code with Opus 4.7; it’s not that the code it produces is wrong, it simply tends to write too much of it. In my opinion it’s still worth thinking about a particular feature and finding the best way to fit it into your code because Claude will often just pick a layer of the stack (maybe presentation), and jam it in there. A couple weeks later you need this data somewhere else and Claude can’t reuse the code (maybe in the service layer) so it kind of “ports” it over. Unless a person is paying attention we now have the double the amount of code and duplicate logic. I don’t see AI tools like Claude getting better at this anytime soon. Where I work there’s already pressure to use Opus 4.7 less to save money, someone mentioned using a smaller model for “simple bug fixes”. This might work sometimes but how often do we really know it’s a simple bug fixe ahead of time? I suspect as costs go up we’ll see interest in using these tools to write “all the code” go down. As people migrate to cheaper and less effective models I suspect we’ll see the pressure to skip reviewing that code dissipate as well. We’ll see where we land, maybe it won’t as dramatically different as the author of this post fears.
  • Eridrus 4mo ago
    I have the same criticism of AI writing too much code. It's surprisingly effective to just tell the AI to cut the (prod) line count in half and look at whether there are other libraries it could reuse. I think you could probably also have a refactor bot that spots duplication and pulls it out. None of this comes out of the box atm, but it's not clear that it's not possible.
    • hyperadvanced 4mo ago
      I do this several times per week. You can ask Claude to hunt down duplication, brittle scripty code, overly defensive fallbacks, and footguns.
      • Eridrus 4mo ago
        It's kind of dumb that we have to do this as a separate process, which introduces even more churn and review burden, rather than having this out of the box in the code generation process.
• photochemsyn 4mo ago
  If corporations really thought LLMs were a great cost-savings tool, then the obvious target for replacement are not the lower-paid staff, but the higher-paid staff - the ‘product managers and stakeholders’. That justifies token burn, replacing the 7- and 8-figure people, right? But that’s not the real goal, is it? The goal is to inflate the stock value, take the cream off the top, and dump the whole business on the pension funds, maybe creating a too-big-to-fail scenario where the government steps in an bails out the industry as with the airlines during Covid. This is why all the testimonials and narratives are so suspect - nobody knows what fraction of online posts were created simply to sell the narrative that LLMs are this incredible disruptive tool that will change the world, solely in order to create FOMO in the investor class. In this particular case, I’d like to see links to samples of LLM created codebases for “PCI compliance, double-entry ledgers, escrows, reconciliation, payment lifecycles, bank transfer idempotency”. It should be easy to put an open-source LLM-generated version up on github, right? And if not, why not?
  • dfffsdfdsfds 4mo ago
    The idea is to start with the largest, easiest lever. The one which will accelerate all _other_ automation. That lever is software development itself. Say you are Anthropic and want to shake up the world of law or medicine or whatever. What will you need? Product managers? You need tooling, software, infrastructure and a lot of it and quickly and you need to iterate really F fast on it as well. If you automate the development of software itself you will enter a new era in which automation of All The Things becomes an engineering problem instead of a pipe dream. Besides software engineering there is (AI) research/science and robotics. That is the holy trinity. Crack that and it's over. BTW: "double-entry ledgers, escrows, reconciliation, payment lifecycles, bank transfer idempotency", these all sound like solved problems and also things that are festering with accidental instead of essential complexity. I won't bet my career on those things. Now if you say something like physics or geology, that's a tougher nut to crack.
  • goingbananas 4mo ago
    I agree, we are still waiting to see the billion dollar valuation startup that fully vibe-coded their product
• bob1029 4mo ago
  > Of course, I'm still employable because someone has to review the code and steer the robot. But I'm just another off-the-shelf engineer now. I have no domain expertise that another Sr. engineer steering an LLM cannot match. All my finance and payment domain expertise, all the debugging intuition and distributed system knowledge earned through hours of sweat and tears, is now promptable. Ownership and responsibility are the new currency for the engineering staff. Willingness to implement these tools and then own the consequences of their use is what leadership is looking for. They want their cake while they eat cake, and they will keep those around who enable something approaching that experience. Owning the side effects of LLM use is more challenging than our own natural output because of the radical volume increase and unfamiliarity with low level details. However, I argue it is still possible. It has always been significantly more expedient to poke holes in someone (something) else's work than it is to perform that same work. And, the executives know this. They leverage this capability too. The relationship between the business and the development team has been tenuous at best. I've rarely seen a technology team that was properly subservient to the business that ultimately signed their paychecks. I every case I have personally experienced, it is was like a hostage situation where the business owners are in constant terror of the technology people screwing them over in some infinitely nuanced way they or their lawyers could never understand. Many business owners are looking at this technology as a way out of the hostage situation. They noticed a window that was left unlocked. They are going for it right now. Whether or not they will succeed in their escape is a separate matter. Whether or not them being held hostage was justified is also a separate matter. It really helps to keep these things in their own lanes.
• shreddit 4mo ago
  This doesn’t read to me as someone who is sincerely impressed or rather surprised what ai is capable off. This reads like someone is trying to convince me, that ai is just this good, and that the author is telling me to use more ai. To me this sounds like: Trust me, it’s really bad, i know what I’m talking about. Just lean into it, or change profession.
  • rzmmm 4mo ago
    I was thinking maybe the author really likes Datadog MCP or has some kind of conflict of interest. It's weird to see this content in HN.
  • efortis 4mo ago
    yes, I stopped reading it because of that, and because it felt AI generated.
  • zuzululu 4mo ago
    I didn't get that impression at all, I think there is genuine write off or outdated view of LLMs here. I also see lot of people sharing issues raised by LLMs at tasks that a human would also fail to produce an accurate result. So in this thread there is a mix of genuine edges that LLMs need harness and guidance with tasks that when given to a human will not perform well in that LLM is supposed to suddenly solve. Like the thread above about financial compliance, without knowing specifics it can be very vague in language and confusing unless you apply to precedents and exact scenarios that can give you a range for what is acceptable/unacceptable. Mythos or any LLM isn't going to magically figure these edges out for you because a human would also struggle at such task. My advice is don't let what you read here including my comment dictate your own decisions, but apply the same common sense, apply it in ways that it can help you and figure out when to use determinism vs LLM in the context of your jobs. These lazy comments that simply try to paint a black and white categorization of AI/LLM are just noise.
  • crnkofe 4mo ago
    I find this doomsday interpretation of AI replacing engineers ridiculous. Lots of it also seems to be bot-written spam. Just because an AI seems to know finance/architecture/debugging doesn't devalue authors knowledge of said domain. Its essentially like your coworker having the same knowledge. There's space on the market for both. And if AI gets to the point that it can in fact replace engineers (somehow also claiming accountability?) I'd expect it to be priced competitively enough to make every manager think hard whether to buy and become hopelessly dependent on some 3rd party service or hire an engineer. The market is not a zero sum game.
• huflungdung 4mo ago
  [dead]
• dicroce 4mo ago
  These are the last days of software. Use the AI's and build cool shit NOW.
• mullenba 4mo ago
  I've consulted with some big companies on AI strategy. I tell them there are two approaches to AI. 1) Train AI to replace human work. This gives you 50% quality for 10% cost. 2) Train AI to assist human workers. This gives you 200% quality for 110% cost. Most companies will go with option 1, and it's a race to the bottom. Eventually, someone will go with option 2 and gather up all of the pieces and take over the market.
  • i5heu 4mo ago
    This is not at all how all of this works. If you train an AI in one thing it will become better in the other.
    • mullenba 4mo ago
      That's not true at all. They're entirely different problems. I worked with a global manufacturing company where we were able to cut plant stoppages for custom products by 2/3. When we used AI to handle the repetitive issues in service of human experts, it freed up the humans to see longstanding issues with data and plant processes that nobody had noticed before. Simply replacing the humans wouldn't have given nearly the same benefits.
  • altmanaltman 4mo ago
    Do you have any basis for these numbers or claims or just took it out or your backside and presented it as facts? What companies do you consult and on what
    • mullenba 4mo ago
      Look at Stitch Fix. Initially, they used AI to sort through their offerings and present options to human stylists. The humans were free to make changes however they felt was necessary. Then they brought in a new CEO from Amazon and fired most of the stylists to use straight AI. Satisfaction went down, revenues went down, and the company as a whole suffered greatly.
• deleted 4mo ago
  [deleted]
• effnorwood 4mo ago
  move yourself to regenerative ag. take a look.
• yurish 4mo ago
  So blog with single post hyping LLMs. Oh and the domain name "human-in-the-loop". Call me suspicious.
• phyzix5761 4mo ago
  LLMs are good at general solutions but not specific solutions. As industries evolve and laws, regulations, and practices change LLMs will struggle because those things are not included in its training set yet. We'll always need humans to push companies in new directions in order to compete, unless we eradicate capitalism altogether and then we're all out of luck. No competition means no incentive to try and be better than the next guy which means no new products and services for humans to develop that AI hasn't seen already.
• CircuitSeuss 4mo ago
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• ozim 4mo ago
  I am kind of like of in the same place though roughly 5 years more than author. I thought about going back to college, learning Math, Statistics, advanced Machine Learning and applying for research role at a frontier lab. That's a super silly take. As much as I did math and even course on machine learning back in the days and I was making basic perceptron in code at university - to get back and be able to do so on frontier level that's years I don't have anymore. Anthropic is doing all that also with their LLMs so that ship sailed. Big thing is — business people are not going to spend time prompting LLM to make an application. If they do then they will become "programmers" and we all (experienced developers) know — you touch it you own it — they (business) will not bother running or taking responsibility. Right now on r/sysadmin there was bunch of posts where admins have "vibe coded apps" requested to be "productionized". Those business types requesting don't know yet — you touch it you own it — they think they can vibe code app drop it at ops and it is all fun and games. When people will start requesting features, start nagging about bugs, start cursing on whatever changes they introduced it will be back to "hey maybe we will just get someone to do that for us". You might not need as deep software dev knowledge but with deep software dev knowledge you still will be faster operating LLM to build systems than non-dev
  • liglam 4mo ago
    [dead]
• nxy 4mo ago
  [flagged]
• hypeatei 4mo ago
  I'm not worried. You cannot hold a machine accountable and there's no way OpenAI, Anthropic, etc. are going to take on that kind of liability if some code resulted in a major outage or a lawsuit. Perhaps that's the signal I'd be looking for: so much confidence in the product that they put their money where their mouth is. Besides, you can look at the websites/apps/software you use everyday and evaluate whether or not the agentic era has produced better results. Personally, there's still plenty of bugs and annoyances. Banks still using SMS 2FA, library breakages in minor version bumps, inconsistent UIs between web and mobile, etc. If all that was a hurdle before... because humans, regulations, or something else... then surely these magical machines that can supposedly replace us and do it much faster would've handled it by now? And they wouldn't introduce more bugs[0], would they? ;) 0: https://www.0xsid.com/blog/meta-account-takeover-fiasco https://www.0xsid.com/blog/meta-account-takeover-fiasco
  • mschuster91 4mo ago
    > You cannot hold a machine accountable Well... accountability is a myth, primarily used to justify obscene paychecks for executives aka "you can't get fired for buying IBM". Basically, as long as you follow what everyone else is doing at the time, even catastrophic losses won't result in consequences. Just look at the recent AWS outages and issues - if you're a CTO and you'd have your webshop running on-prem, you'd get axed for a multi hour downtime. But since your webshop runs on AWS, you're following "industry best practice".
• shevy-java 4mo ago
  I don't see it as negatively, in that there are specific trade-offs. For one: LLMs make a lot of mistakes. We all see that when they hallucinate search results and what not. But, possibly even more important than that, you ultimately become dependent on some big company via LLMs. Perhaps that trade-off is worth it for some companies, but I personally don't want to become dependent on these companies. I actually consider it a hostile attack from the USA, and under Trump this is even more obvious. Another thing that sucks by LLMs is documentation. They generate a lot of crap that is useless. So that's another area where humans could be better. Admittedly a lot of vibe-coded AI slop is also useful in some ways, but it has started to make me rather angry in general - youtube already spoiled me here. I no longer want to see ANY AI videos at all whatsoever. It just wastes my time. I am not here to empower skynet version 20.2.
  • emodendroket 4mo ago
    OK, but that same argument applied to getting on one of like four cloud providers and essentially everyone did that.
• 5701652400 4mo ago
  don't worry, soon there will be no "software engineering" careers anymore.
• steveBK123 4mo ago
  > when I step outside my area of deep knowledge I can no longer call BS on the agents It's still funny that 4 years into this mania the models can hallucinate basic ground truths, humans are increasingly not reviewing the output, and misusing LLMs where simple automation would suffice. My wife does project management and works with a lot of tech leads. They came to her with a project plan deck, and she started questioning some weird dates. The LLM was able to pull artifacts out of their issuer tracker, but it just.. hallucinated some of the dates in the process of creating a project plan deck out of the underlying data. These guys didn't care to review and notice, and who knows what else it hallucinated content wise. They were happy to send this project plan multiple levels up the food chain with hallucinated unreviewed dates. 5 years ago they would have just written a script and had none of this mess.
  • juleiie 4mo ago
    That’s why I use AI more like: Write a tool for me that does this. Instead of directly: do this. Preferably I would interweave code and AI queries where some function waits on prompt result too I think?? To avoid too big context hallucinations I mean that would work for my use cases. At least what I learned is that the less AI itself does in the context is the better so to say as critical LLM mistakes are approaching 100% of probability over time.
    • steveBK123 4mo ago
      The crazy thing is how many people who can write code (with or without uAI) are in fact using the LLMs in the latter "go do this" mode. There are a lot of non-tech people using these products in this manner. Along these lines my friend is CTO at a non-tech firm and theres vibe coding happening in one department on a project that is going to churn $1M of tokens. Head of that department told him it's OK because instead of paying a SWE annual salary, they'll just pay $1M of tokens once forever. People don't know what they don't know about software, SDLC, support, maintenance, etc. If code was something you write once and never think about again, most tech orgs could be 75% smaller.
• goodrun 4mo ago
  I read all the posts in this thread - but no one has a good idea to avoid software developer obsolescence. My guess is this profession has 5 more years. It was a good run while it lasted. All the other white collar workers are in the same boat. A pillar of the economy is going to be destroyed with no obvious replacement in sight.
  • xyzal 4mo ago
    Which other profession has the same amount of training data freely available for the taking?
    • goodrun 4mo ago
      Don't need much training data for bank/insurance/retail analyst work - it's just basic reasoning and data retrieval. If AI could crack the programming nut - one of the most intellectually challenging professions - it can handle the rest with ease. The only human role will be high level monitoring - and even this will be largely automated so fewer will be required.
      • goodrun 4mo ago
        Sorry to reply to myself but I just recalled the recent Apple ad that ran last year about a corporate goofball who got his Apple device to fire off well crafted email slop to his manager who looked surprised/impressed. That trick will only last for a short time. The joke is that people like him and his manager will be the first to be fired.
      • mschuster91 4mo ago
        > Don't need much training data for bank/insurance/retail analyst work - it's just basic reasoning and data retrieval. For insurances... there's a reason why the three bullets of the plumber's brother were labelled "delay, deny and depose". You don't need a grunt to compose a denial order. Just let AI default-deny everything, most people won't have the energy left to battle the system or they'll die anyway before the claim finally sees an independent judge. And as long as insurances aren't severely punished for denying claims that are found out to be valid later on, this dynamic will just continue as-is.
• threethirtytwo 4mo ago
  There is an element of human nature that is known as self delusion and it is extremely common. Almost everyone on HN is suffering from a form of self delusion. Usually when a human self deludes they do it when they're identity is under threat. People would rather hold on to identity then face the truth at the cost of their identity. That is what is going on in almost every HN thread that has to do with this topic. A good example is religion. Someone who is intelligent, but born into a religion, will have a hard time giving up that religion EVEN when presented with logical/rational/realistic arguments for why that religion is false. They will rationalize the most convenient reasoning to maintain their own identity. I mean think about it. Even the concept of religion is obviously false. It's not science, it talks about phantasmic beings that OBVIOUSLY don't exist. It's inconsistent among different groups as in there's thousands of religions in the world and nobody thinks the obvious of the fact that if only religion can be correct, then most of the world is fundamentally believing a total lie. Anyway, the same thing is happening with AI. AI is eroding our identity as software engineers. So you'll see rationalizations in this thread in attempt to protect that identity. The biggest excuse is LLMs are hallucinate and are often wrong and fortunately for humans... this rationalization still works because it's still very true. However what people are not mentioning is the obvious. People are avoiding it because they are delusional. The topic of this thread is "erosion" of "software engineering career" AND that is utterly true. ADDITIONALLY the error rate of LLMs have been going down. AI in general is improving. The erosion is real and obvious. But you will see here on this thread that people are not talking about the erosion. They are holding on to the one last rationalization that is a differentiator without ever thinking about how that differentiator is "eroding" even though "erosion" is the LITERAL topic of the conversation.
  • ralferoo 4mo ago
    At the risk of being voted down for stating an unpopular opinion, the problem is that faith is neither provably true nor provably false. That's what makes it faith, not science. Even though you clearly believe very strongly that religion is wrong, that's not a scientific viewpoint because science doesn't and cannot disprove the fundamentals of religion. Taking it further, you can't actually prove anything is true with science, because fundamentally it is about making hypotheses and attempting to disprove them, and those that remain and can't be disproved you accept as "scientific truth". But many "laws of science", we have already disproved but we still use them as approximations because they are useful. One final thought is that people frequently have conflicting internal world views. Some people cannot tolerate that, and require a consistent set of rules that govern their idea of the world, but the majority of people are comfortable with some degree of ambiguity in that. In general, the more rigid and coherent your worldview, the less likely you are to accept that it might be wrong, which is why many scientists devote their efforts to disproving other ideas they disagree with, rather than trying to disprove the things they believe themselves.
• skeledrew 4mo ago
  Yeah the writing is on the wall. Not just for knowledge work, but for jobs in general, as I've been saying in other comments. The era of wage labour, and this dominant economic system, is coming to an end. There's no way it can coexist with AI, but it also needs to continuously push for better AI, which means there's no stopping it. The only thing to do really is brace for the disruption - which will likely be pretty rough - and hope governments play their role properly to ease the transition.
  • weatherlite 4mo ago
    I agree but I think it would take awhile. Some of us here seem to believe 2026-2027 is the end of programming jobs. At least that's Amodei seemed to be saying but then changed his mind later on?
    • jplusequalt 4mo ago
      Amodei has a track record of saying blatantly false shit in order to drive hype. At this rate, I see him as a snake oils salesman.
    • skeledrew 4mo ago
      Well given the pace of improvement so far, it's possible - though not given, IMO - that before 2028 we'll have models that make programming jobs fully obsolete. But that doesn't mean jobs will suddenly disappear; many places, especially in 3rd world countries, will continue to have humans programming for a while yet. Just that the available positions will slowly taper out over several more years, until only the most critical systems are maintained by a few humans, and programming - and other knowledge work - becomes purely hobby. Manual work will follow the same trajectory as AI also accelerates innovation in robotics.
      • weatherlite 4mo ago
        It's possible , yes. For now I'm betting against it, we'll see.
  • bluefirebrand 4mo ago
• dk970 4mo ago
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• ef2k 4mo ago
  > All my finance and payment domain expertise, all the debugging intuition and distributed system knowledge earned through hours of sweat and tears, is now promptable. I think the author downplays how much of that knowledge is used on knowing what to zoom in on, what to prompt, or what to look for.
• internet2000 4mo ago
  This is good. We want less barrier to entry and more competition in software.
• hypfer 4mo ago
  This feels fake/engineered but regardless of that also redundant. It's the exact same story that we've heard countless times by now. Hosted on a blog with just a single post. Named in a way that suggests that said blog was created for this very single post. What is there to learn from this other than LLMs seem to be bad for some people's psyches and that AI companies need these very stories to not get their funding shut down?
  • gamegod 4mo ago
    It's 100% fake, and half the comments here are from 20 year olds working at AI companies.
    • hypfer 4mo ago
      I mean I kinda get that it sucks being a junior now, but otoh, it might also not? It might be easier to adapt to this new tech when you're 19 compared to when you're 59. But honestly, this discussion _also_ has happened ad-nauseam by now. Everything that was worth saying has been said. And then some. People don't actually want to talk about LLMs. They want a hug. And that's fine, human and all. But could you please just start asking for hugs instead of encoding that into vaguely profound sounding takes on AI? I'm tired of this play pretend.
  • Havoc 4mo ago
    >Hosted on a blog with just a single post Would you put a "Hey i'm feeling a little useless" post on your main blog / linkedin?
• throwatdem12311 4mo ago
  My job as a staff engineer has turned into just reviewing slop farm vomit from offshore devs in Pakistan making pennies on the dollar given a slop code subscription and going wild. I’ve lately just turned to having Claude do a quick /review, spot checking it, doing my own review and the. firing up some web agents to make the needed changes and just ignoring the back and forth because they don’t give a fuck anyway. Just waiting for someone to notice and ask the obvious question at this point.
  • rootusrootus 4mo ago
    I will be happy if Claude lets me eliminate my offshore Genpact team. I don’t need slop from slop.
    • throwatdem12311 4mo ago
      I’m the one that needs to support it in production and fix the bugs anyway. Offshore is pointless.
• jordemort 4mo ago
  Reads like “AI is inevitable” propaganda to me
• amelius 4mo ago
  It's not just our careers. In the hunks versus nerds wars, it is now clear who has won. The nerds have made themselves obsolete and put the continued evolution of homo sapiens to an abrupt halt.
  • trumpdong 4mo ago
    No software developers == no humans?
    • amelius 4mo ago
      No, homo sapiens degenerating into homo stupidus.
• sergiotapia 4mo ago
  I can't write what I really think because my name is attached to my account. Let me just say AI is not nearly as good as the billions of dollars in marketing spend say. We are months away from catastrophic bed shitting and the tech industry will pay the piper.
• theptip 4mo ago
  > I have no domain expertise that another Sr. engineer steering an LLM cannot match. All my finance and payment domain expertise, all the debugging intuition and distributed system knowledge earned through hours of sweat and tears, is now promptable. Don’t sell yourself short! Taste is not promptable, I suspect good taste is AGI-complete. Especially in domains like fintech, there is a lot of accumulated wisdom, and that is what you’ll be handsomely paid for (for at least the next couple years :/ ) For example, architectural patterns, when you need bitemporality, immutable logs, CQRS, all these good patterns that can only be learned by owning years of system architecture - none of these feedback loops are in the training set. And from a product design side, agents will just miss key concepts and you need a few words to prompt a fix - but that might represent a massive tree search optimization, or the agent on many cases would just fail to identify the requirement. These small steers feel small, but by evaporation our work has distilled down to just the extremely high value insights. METR task time is still at weeks, doubling every 7 months; it’s years (assuming we keep riding this crazy exponential) until you hit multi-year tasks. I don’t see wisdom / Métis being solved in 2027. All this said - I think it’s important to extrapolate forwards, if the trend continues, this will may all be true in 3-5 years. Now is the time to pre-register what metrics would make you worried, so that you can define your red lines. There will be a rapid consolidation of power and wealth if these tools continue on their existing growth trajectory.
• myfonj 4mo ago
  I think that the domain knowledge still matters: if for nothing else, then at least it can make the communication both with savvy AI tools and savvy humans more effective compared to "outsiders": acquired vocabulary, truly grokked concepts in the field of target expertise etc… -- that all seem like a huge competitive advantage over folks having to learn all that "on the go", constantly struggling to pick the right nomenclature or using wrong or vague terms. It's mostly that domain knowledge what makes experts understand problems faster or at all, even.
• dfilppi 4mo ago
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• r2ob 4mo ago
  I'm thinking about taking a plumbing course.
• snowe2010 4mo ago
  Am I the only one that has noticed the massive increase in buggy software across almost every domain? Like, EVERYTHING has so many more bugs now. Things just break constantly. AI isn’t one shotting fixing bugs, it’s one shotting making hundreds of new ones every time it writes anything.
• aogaili 4mo ago
  Software engineers with low self-esteem who built their entire identity as mechanical cognitive workers are having an identity crisis and spreading FUD. Currently, LLMs are nothing more than amplification tools that require significant steering. If you think your job is mainly to take input from POs or managers, translate it into if/else statements and loops, and review PRs, then you never really understood your role. Software engineering—for those who went to university and studied it—is fundamentally about complexity management and cognitive automation. People in the field, or at least those with some math background who studied software engineering properly, understand that it's all about managing complexity; current tools are nowhere near replacing a software engineer. What they call "taste" is imagination, creativity, embodiment, a more intuitive understanding of context, and yes, superior intelligence compared to current AI. However, AI and LLMs are excellent at mechanical work and mimicking human intelligence, so use them for what they are, and stop whining. Going forward, the world is ever-growing in complexity, and automation will become widespread everywhere. LLMs just unlocked another level. So basically, cognitive work will be automated—perhaps up to 90%—until the next breakthrough (if ever). You can sit and cry, or you can learn the tools and help shape the future. Software engineers can automate the entire economy now, including the executives, yet they just sit there whining and crying. This is a self-esteem, confidence, and identity issue more than anything else.
  • jplusequalt 4mo ago
    >You can sit and cry, or you can learn the tools and help shape the future. What exactly are you helping shape? The volume of your employers bank account?
    • aogaili 4mo ago
      Chinese Gen Zers are starting companies before graduating, people are generating music and starting their own studios, others are improving models and building harnesses, and the rest are on a mission to automate the entire knowledge economy—from healthcare to governance. Regarding your employer's bank account: if that is all you were doing before, then that is all you will be doing after. You are just complaining about capitalism now. The irony, is that the means of production is now in the hands of millions. Those who are crying are those who paid their mortgages with for loops..well, I think they will continue doing so, with less hubris that's all. LLMs are nowhere near replacing full engineer. So get a grip fellow engineers.
• deleted 4mo ago
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• xiaosong001 4mo ago
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• rahulshah2002 4mo ago
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• dwh452 4mo ago
  There are lots of positives that have resulted from using AI in software engineering. (1) No more long repetitive text editing sessions. I.e. changing namespaces or replacing deprecated APIs with the "correct" ones. AI will make nearly perfect text modifications with ease. (2) No more bike-shedding code reviewers nitpicking over every tiny coding decision. I.e, "you should use std::format instead of std::stringstream". AI will match the existing set of nitpicks so you don't have to. (3) Average Joe's and Jane's can craft applications by just talking to the computer. This might inject a freshness to the current state of software. Currently, we are all forced to use the same bloated applications like Word, Excel, Jira, and Photoshop. We are currently forced to deal with the same set of monopolistic SW companies. Now average folk can solve problems and avoid dealing with Microsoft for a spreadsheet program.
  • manishsharan 4mo ago
    Average folks like their Excel and Word. Most families have MS subscriptions like they have Netflix subscriptions. Monopolies will continue as Token prices continue to rise.
  • neta1337 4mo ago
    Re. 1) Ai will often hallucinate new APIs therefore creating more text editing.
  • jesterson 4mo ago
    > Now average folk can solve problems and avoid dealing with Microsoft for a spreadsheet program. You seriously believe some vibecoder can write anything remotely similar to MS Excel, which took probably thousands man-hours to create?
    • NichoPaolucci 4mo ago
      I'm also a little hesitant to accept that this is the future. Why build excel with someone in house? It'll probably take at least a few weeks to build it, and now they need to maintain a spreadsheet platform in house??? Google sheets is free - Excel subscription is pretty much standard in many businesses and is not super expensive... Feels like the ROI just doesn't exist for most scenarios. Microsoft already DID all of the hard work, why redo it.
• tantalor 4mo ago
  Even if the model can replace a domain expert on the software side, you still need a human who can decide if the technical solution actually meets the business needs and that would require a human with domain expertise.
• EGreg 4mo ago
  Think of it like this You’ve already faced this the entire time with… libraries on github. If employers knew how much you can just use a new standard library, or ask you to “use React”, that’s a lot like asking you to use an LLM to speed things up. You also benefit from the collective wisdom of a lot of people. Do you write assembly or pixel shaders by hand?
• hmokiguess 4mo ago
  I always remember of the infamous Steve Jobs quote "Ideas are cheap". If execution is everything, and frontier LLMs solve execution, then ideas are the gateway to abundance now, but abundance alone does not guarantee "stickiness". What I think is often overlooked is the human "Willingness" and "Care" of staying with the thing for the lack of a better term. What I mean by that is that a lot of people just don't care enough, or don't want to, build, maintain, and own things. Sure you can ship V1 faster, but will you remain on the grind? I think a great example of what probably will happen is found in Suno, the AI Music thing. I don't know if y'all have tried it, but it now produces really good stuff. What's happening there? A lot of people play with their own little universe and get tired quickly, move away from it, and only a few prolific creators stay and turn it into a "job like" environment. We may have shifted the scale and the economics of "delegation" and "execution" but I think there are still a lot of other factors to consider.
  • onlyrealcuzzo 4mo ago
    > If execution is everything, and frontier LLMs solve execution, then ideas are the gateway to abundance now, but abundance alone does not guarantee "stickiness". They don't "solve" execution. If you're willing to push them enough, and put in place the system that they can actually get working code, they can solve execution - but that IS engineering!! They are far from doing that by default now (replacing engineering). Maybe in 3 years. They're moving fast. But you can't ask them to build you a better Rust compiler, sit back and watch, and get a result today.
    • hmokiguess 4mo ago
      Totally, I meant that more in the lenses of how folks are perceiving it. They solve the execution part of the "one shot" aspect mentioned in the post. You still need to do a lot of plumbing, orchestration, supervision, etc. I think it will get cheaper and cheaper over time, though not magical enough to one shot a Rust compiler from "write a Rust compiler make no mistakes" haha.
    • tiahura 4mo ago
      Today is when ground needs to be broke on the data centers to run it in 3 years.
• kamranjon 4mo ago
  “even though you're delivering code at a good pace, you're taking too long to deliver those Design Docs. Are you using AI? You should use more AI.” This here is the crux of it I think… it’s often promoted that AI will give us the time to do the “real” engineering work of designing systems and really serving the user, but in practice all I’ve seen is further attempts at optimizing every last process with AI - just homogenizing every product and feature into slop. It feels like every leader has been to some talking points boot camp where they’re incentivized to apply pressure to every part of their process - sort of a desperate attempt to justify the costs they’re incurring. I think we will look back at this and see how obviously short sighted it was.
• kypro 4mo ago
  This was a good summary. I feel similar. At this point I think 95% of the skills I've developed over the 2 decades are basically useless. Prior to 2023 I felt like every new skill only made me more employable, but now I don't really see any software skills that are safe from AI today. Even the ones that are very likely won't be in a year or two so there's no point in learning. I've said this in other threads, but it concerns me how little the average person is preparing for what's coming right now... It seems people are making decisions as if their jobs and income are safe when in reality their entire profession could be gone in less than a decade. People in this comment thread saying crap like "yea, but the code LLMs write still isn't that good by my standards" are totally missing the trend. The fact LLMs are even one-shotting extremely technically difficult problems was something almost no one thought they'd be able to do by now a couple of years ago. Even I as someone who pushed back against this and thought they would become extremely competent within years am genuinely amazed at just how good they are. Trust me, regardless of your opinions, your job and career is at risk. Another thing to understand is that if AI replaces workers in a variety of fields from SWE, accounting, customer support, graphic design, etc. Then it's likely going to be hard to fine other jobs to pivot into because when unemployment increases that significantly everyone will competing for the same limited number of jobs. Some will fine something, but most will struggle to find anything. I hear a lot of people talking about how they'll just go into 'x' field if AI comes for their job, but realistically you'll need years of reskilling and you're assuming that in a world where other people are also losing their jobs, and where AI is touching ever more forms of work, that you'll easily be able to get a job in that other field. And I'm not saying that won't happen, just that this isn't as realistic or as safe of a bet as some people seem to think it is. You're also likely deluded about how hard it is to find work because you've been in software for the last decade. Please, please, please, start preparing for what's coming. The economy is going to get extremely rough over the next 10 years. You need to be prepared to be without income for years, if not indefinitely.
  • dfffsdfdsfds 4mo ago
    The fact the whole world is going down with me is of some help actually. I can't stop the world. There is no preparing for that. We'll figure something out and if not, then not. My non-tech friends will not suddenly be able to run servers or oversee AI systems. They will come to me with their ideas and I will turn the crank. My role will probably be named differently, something like "Intent Manager" or "Architecture Developer" or whatever but I have a strong feeling much of it will basically remain the same. The politics, the egos, the personality differences, AI has changed nothing in that regard. The jocks will not suddenly sit in front of laptops prompting Claude to debug their MQTT setups. You can say AI will do that and sure it will, prompted by me. If AI will do it autonomously then we're all fucked and I don't care about my "career" by that point. It'll be survival of the species time. Much of accounting could have been automated. A good friend of mine has been manually entering paper receipts and whatever for well over 20 years now and his work load has actually increased. It's all automatable, but there are so. much. more. levers. Possible != will happen. I do agree it's not the time to empty your savings account. Get ready for some rough times.
• NoGravitas 4mo ago
  This person was hired, from the beginning, to be a meat shield. To be responsible for decisions they won't be allowed to make.
  • incognito124 4mo ago
    I like the term "human crumple zone"
• zkmon 4mo ago
  > I don't know what to do. Ride the wave. You rode it when websites/webapps were the wave. I came into software industry before internet, kept changing my horse. You are never too old to learn new tricks. The new wave create new kind of work and workers. Be one of them. Ride the beast, master the tools. It's the same game again.
  • Verdex 4mo ago
    This here. Overall society feels more turbulent, but this is otherwise all the same song and dance all over again. The 90s and 00s had this wave of "object oriented programming changes everything". Hey we're doing this thing that's been done successfully 100s of times before, but now it's OO. Writing some code in involving an airplane? Just purchase this omni-airplane object that does everything for airplanes (an actual thing I was told in college). That's weird OO isn't the be all end all? Code gen, get this Ruby on rails running. Look at me building this website in two seconds. Code gen everywhere. Huh, that's going to a funny place... TDD. If you aren't TDDing then you're such a bad engineer that you should be locked in prison (real conversation I observed). Oh wait, not TDD, BDD. That fixes it. Lean, no Agile, no agile like with a small a ... but it was first, no scrum, no xml wait that was last decade, json, and finally SAFe. Hey, have you seen this chat bot thingy? Every iteration brings good stuff if you're paying attention. But it also brings a lot of hype and anxiety. Experiment and learn. The one thing that's remained constant for me is that nearly everyone would rather die than to think carefully about the consequences of their dreams coming true. And as long as that remains true they'll continue to pay for someone else to ride the hype dragon on their behalf.
    • mschuster91 4mo ago
      > Overall society feels more turbulent, but this is otherwise all the same song and dance all over again. The thing is... everything you mentioned had only brought the need to retrain. This new hotness AI? It's bringing actual layoffs, and not just of the boom bust cycle kind, but permanent, industrial-revolution kind that lasts for decades.
      • 4mo ago
• lovlar 4mo ago
  I’m excited about the genAI future. I’m a software engineer interested in product, user experience, architecture, and entrepreneurship. After 4 years in the industry, mostly within fintech, I have gotten tired of slow organizations, company politics, nontechnical managers doing the decisions etc. I’ve saved up a couple of months of salary, have a couple of bootstrap ideas that I believe are within reach for me equipped with a coding agent to build. Hosting can be done almost for free. What used to take entire teams and hence millions of dollars to build can now be done a lot cheaper. If I’m lucky one of those ideas can pay my bills soon. If not I’ll go back to consulting for a couple of months.
• SoftTalker 4mo ago
  > I spent 10 years (even more when you account for non-profession experience) getting good at things that are becoming less and less valuable. This is just how it is, and has always been in this industry. And it takes about 10 years to realize it. When I started my career in software, businesses were still writing new code in COBOL. 10 years later those skills were pretty much useless, except for dwindling maintenance roles. Then there was the client/server era. Then the web era. Then mobile. Then cloud, etc. All the same functionality, written and re-written time and time again, using the latest popular stacks and methodologies. I hope to be retiring in a few years and pretty much everything I have learned over nearly 40 years is no longer applicable or is at best losing relevancy to the way sofware is built today. And that's how it's always been.
  • matwood 4mo ago
    This is a good point. I started with Turbo Pascal in school and my first job was writing VB 5 Windows apps for local businesses. SQL (and C, but I haven't written it in ages) is probably the only thing I learned in the late 90s that has been a constant my entire career. Languages and frameworks seemed to change so frequently that I never thought too much about them. I was always focused on the end goal of solving some business problem.
  • rdbl27 4mo ago
    Sure, but those are cherrypicked cases where a technology became obsolete. There are many counterexamples of decades-old technologies that are still actively chosen for greenfield work today, in 2026. SQL was first released in 1973. More new SQL is being written today than ever. C++ (1985) is the de facto standard implementation language for web browsers, JavaScript engines, networking stacks, telecommunications, video games, high speed trading, CAD/CAM, video rendering and editing, audio processing, filesystems, databases, hardware drivers, automotive, aerospace, and robotics, among others. Is Rust making inroads? Sure, and it's a tiny fraction of C++ still. It's a long ways from being the standard. Likewise, Python is often cited as the "AI language," but that's on the surface -- CUDA, tensor libraries, inference languages, GPU kernels, compiler stacks, and so on are usually C++. Then there's C -- introduced in 1972. Still widely used for greenfield in kernels, device drivers, embedded systems and microcontrollers, filesystems, firmware, network stacks, cryptography, databases, compilers. LaTeX, MATLAB, Erlang, Verilog, PostScript, Lisp (including Scheme and Clojure), shell scripting (and the UNIX paradigm itself)... the list of old tech that still sees new projects in 2026 goes on.
• pieceofcake 4mo ago
  Agents may have made 80% of your experience go to $0, but the other 20% is exponentially more valuable now. This outweighs your other losses. The ability to orchestrate intelligence is a magnificent power that few have, and while barriers to entry will be eroded, it will take time and they won't be eroded fully. This is your edge.
• dasil003 4mo ago
  It's odd to me how quickly the author devalues their own experience just because AI can do certain things well. There's a huge chasm between what AI can do when prompted by an expert software engineer vs a non-technical person. Sure the models and the tooling will get better, but it still needs to be driven by someone with an intuition for how software works and able to dig in when necessary to unpack and correct the hallucinations, misplaced assumptions, or straight up borked code that will come from the gap between what a human wants and what they can express in words. I have no idea how things will play out, but so far I am not worried because the amount of software continues to increase, and AI only accelerates that trend. This will require the same mental modeling, first principles thinking, and relentless curiosity that already formed the foundation of the software engineer skillset.
  • mariopt 4mo ago
    I think the core issue is not AI itself, it's people. Right now non-tech people just think AI will do anything they want and are the one in charge of hiring/firing, managing, etc. It's horrible to be a software dev right now, you've to deal with AI and lunatics. Of course Domain Knowledge is important but, right now it's very hard to have reasonable conversation because... you know... AI this, AI that. I had a customer showing me a Claude vibe coded atrocity trying to convince me it's was a great app, now ask yourself: How are devs even supposed to collaborate with this without going insane? Simple, you can't.
    • dasil003 4mo ago
      There's no point debating people who are in a blind mania. Sometimes it's better to just keep your head down and focus on what you can control while "mistakes are made". You will be infinitely more appreciated once they acknowledge that help is needed.
      • fzeroracer 4mo ago
        Sadly while I agree with this attitude, from experience they will ever get to the point of acknowledging help is needed. Eventually they'll find a way to blame the workers again to justify laying them off and double downing on doing things the stupid way.
• mannanj 4mo ago
  Isn't the solution to learn business skills? My challenge is seeking good resources for the business skills. I'm doing sales for a passion project for the first time, and it's teaching me a lot. I'm just confused still on why it feels so hard and why I can't find an easier way.
  • mschuster91 4mo ago
    > My challenge is seeking good resources for the business skills. I'm doing sales for a passion project for the first time, and it's teaching me a lot. I'm just confused still on why it feels so hard and why I can't find an easier way. Sales are going to be drowned by AI soon enough. The low end is already getting yeeted by webshops, dropshippers and AI powered bots and a lot of B2C and B2B sales are shifting off of the classic representative sales model as well (towards self-service) because everyone that does not is cheaper. Basically if I have the choice between a SaaS that says "contact for a quote" and "X users => Y $/month", I'll always go with the latter option. And on top of that comes offshoring, that has gotten surprisingly good with ever increasing voice call quality.
    • mannanj 4mo ago
      Ah. My strategy has been going in to in-person shops, as I'm targeting service businesses with my project. I don't think you can ever beat that in person trust and chemistry. Though, also, I think it helps still when I am comparing products as you said "X users => Y $/month" and I have a vibe that I trust one product more than the other I'd go for the one I trust more. And that level of proximity, humanity, empathy maybe? That isn't being approached very well by these AI or offshore services and probably never will. Thoughts?
• pfdietz 4mo ago
  It feels like it's time to start turning the screws on regulation of software engineering. If productivity is really getting better, regulation can force that productivity to go into increasing software quality.
• punkbit 4mo ago
  The company is hiring; the author mentioned they are talented and unemployed for the past 8 months. Why not remind the company to re-hire them?
• hmokiguess 4mo ago
  One other thing I find it is bound to happen is that this domain knowledge you speak of is just going to shift towards LLM domain knowledge. Look at prompt engineering, and how quickly it became a hot thing. Does everyone know to steer their AI well? There's only so much a harness can do for you once you start attempting to one shot with a single sentence of 4 words. As others said, "write a Rust compiler make no mistakes" can only work if you overfit a harness to that single prompt. Nobody is going to do that. So the part you mentioned about the knowledge you accumulated around how to know that "trade-offs between implementations" and "idempotency to prevent double-charges" is just moving to the domain of the english language and tokenizers. One could argue here that this is far more interesting as it requires you to explore deeper into how we communicate and describe the world around us. Reminds me of physics and math. I think there's an optimism lenses to it if you can grasp it as an opportunity rather than an inevitable doomsday apocalypse.
• dkarl 4mo ago
  Coding taste and good architecture are the final pillars because AIs are trained on a ton of bad examples that are presented as good examples. That pillar will stand until AIs are able to reconsider and re-evaluate the material they've been trained on.
  • m0llusk 4mo ago
    That should help, but there is a fundamental problem. A conscious entity exercising good judgement can say they don't know a good answer or method for getting one, but an LLM will always compose a response for a given prompt.
• ralferoo 4mo ago
  Interesting that this dev sees domain knowledge as the most important part of his job. Over my nearly 30 year history, I consider domain knowledge as the least important aspect, and in fact have experience of many varied domains. 3 years web development, 2 years systems administration, 5 years point-of-sale / payment systems, 3 years performance management software, 16 years games development, 2 years GPU development tools, etc. In every case when I've shifted domains, the skills that have got me the job were demonstrable solid programming experience on a wide variety of systems, with only a tangential link to the new company's business. In each case, I've gone in knowing almost none of the domain knowledge, but it's never been a problem because the business analysts know that stuff and tell me what they want me to do, or it's been stuff I've been able to pick up in the first few months. For example, when I switched to games development it was the combo of systems admin and web backend development that the company wanted, I actually used none of those skills in the first year doing what they hired me for, and pretty quickly I'd transitioned from that to become a rendering engineer, and I've now spent the majority of my career optimising shaders and game engines. So for me, it's certainly the case that I value my adaptability across domains, and I'm not worried about having to shift to another business domain because I know I'll be able to produce whatever it is they want if there's a reasonable spec in place. Sure, when hiring if you have 2 candidates - 1 with the exact domain knowledge you want, and 1 without, the one with domain knowledge has a head start, but in the case where nobody has that domain knowledge (or in the case of the article, it doesn't matter because AI levels the field), then I don't think it matters much. Personally, I'd rather be the person with the broadest skills and able to pick up what I need than to have been stuck doing the same thing my entire career.
  • 59nadir 4mo ago
    Most people don't really want to acknowledge this because most people have optimized only for learning domains and are still terrible at the job of actually putting together solutions, writing software, etc., even after 8+ years of work ostensibly doing exactly that. Constantly falling standards agree with them, though; no one really cares to have good software that is well put together, it's more important to have surface level knowledge about frameworks and domain knowledge that can be taught in less than a month (though most people think their particular domain is oh-so-complex and difficult to deal with).
• awill88 4mo ago
  I think we are all vulnerable and need to reassess what it is we bring. Agents merely accelerate and equalize the playing field. And they cost money. We might be a dying breed, but we are the best operators of this technology. And if we want it, this is our moment. Yes, get into wood working.
• havkom 4mo ago
  I am mostly worried about the current AI use in management. I’ve met a few with ”AI hubris” making poor managerial decisions that stem from their poor usage of ChatGPT (not understanding the importance of context, model sycophancy, etc).
• holyknight 4mo ago
  People are missing the long-term horizon on this. Yes, definitely, you can automate most of your workflows as a software engineer with today's LLM frontier capabilities fully E2E. But many things are still super open: -First, cost is not a settled topic yet. We have no indication that automating everything E2E will be a cost-effective way of doing stuff. So the bare minimum is that you will need some expert designing the workflows in a token-efficient way. Worst-case scenario, tokens become super expensive and only certain parts of the job can be efficiently automated and many companies are not even able to afford tokens. -Second, the system you just "created" is just a static snapshot of today. Yeah it may work fully automated for 6 months, maybe a year. What then? Breaking changes? Updates? Re-designs? What if the quality slowly degrades until nothing ever works again? Who will fix that? There are so many unknowns that it is borderline irresponsible to make guesses on what can be automated sustainably long-term or not. Unless you are OpenAI's Codex team wasting a billion tokens a day on automating and self-improving everything, there is a high chance that everything you set up today is completely useless in a year. -Third, the core engineering workflow hasn't changed a single bit. People like stakeholders, product owners, PMs, etc. can come up with ideas and things to build but someone needs to take decisions on what gets built and what doesn't, balance out paying down technical debt vs. feature development, incorporate new domain knowledge into the system (Or would you expect your PM to be tweaking the prompts about a new regulation regarding GDPR or a completely new legal framework that changes the whole thing?) -Fourth, probably the most important one. If you think AI will soon get good enough to get self-improving and self-sustaining enough to replace full engineering departments E2E with no supervision then nothing else matters because we will all end up without a job and living on UBI (not only tech people). So why do you even care? If it happens it doesn't matter, and if it doesn't happen we just continue doing what we were doing until now. Why do you care?
• a4hast 4mo ago
  Advertisement piece for the IPOs. We get this multiple times daily to pump the stocks and demoralize programmers.
• serge_blanc 4mo ago
  Well, not a single 20th-century science fiction novel features programmers; instead, there are platonologists, biologists, and linguists. Humanity is twenty years behind in development because the previous twenty years were spent solely on e-commerce.
  • pcthrowaway 4mo ago
    Not sure if you're being sarcastic, but lots of 20th-century novels featured programmers. Snow Crash being the first to come to my mind.
• jgilias 4mo ago
  > And we all know the demand is drying up. I don’t think the data really supports this? Last I checked at least.
• hnuser 4mo ago
  This post is sad. Hacker news is turning into /cscareerquestions as someone who's watched this for last 15 years it's going downhill.
• catigula 4mo ago
  Just want to point out that code quality and architecture is actually eroded by codes 5.5. It’s over for this job I think.
  • bigstrat2003 4mo ago
    Just want to point out that such claims have been made, falsely, for every model to come out in the past three years. It's almost certainly not true this time either.
    • catigula 4mo ago
      I am truly sorry, but it is true this time.
• mschuster91 4mo ago
  > Maybe I should consider transforming my woodworking hobby into a profession... Yeah. There is no future in IT any more, let's be real. Enough CEOs have drunk so much AI kool-aid that they'll lay off so many people it will become outright impossible to get re-hired again when the incompetent CEOs have gotten fired - too much competition. The only industry that's going to give reliable employment in the future is the trades, especially the regulated/licensed ones. Gas, water, electricity, structural engineers - basically everything where there is actual human lives on the line when things go south.
• pegasus 4mo ago
  I don't believe agents care less about architecture than us. Badly architected code has the same effect on them as on us, namely to slow them down and degrade the quality of their output. Which translates to the same thing as well, loss of revenue. Coding agents are driving up the value of architectural skills to the detriment of more specialized/technical skills.
• Aperocky 4mo ago
  > And then I started realizing: all the knowledge I have accumulated over the years: the trade-offs between implementations, how acquiring works, how to structure idempotency to prevent double-charges, everything, was becoming useless. How is that true? I've been using Opus on an industry scale over last 6 months and this is just not real. It has consistently with a certain percentage of chance each time (and no claude.md and skills do not stop it fully): * Suggested to remove tests to allow for things to pass * Suggested remove an error so that things can be "unblocked" * Suggested to use a second path when the original path ran into problem instead of making the original path accomodate for that possibility. * Suggested or silently added "features" or "guardrail" that I don't want. * Can be left unsupervised only if given a goal that it can verify against itself. Without such clear goal (e.g. this test in the integration environment must be fixed), it flounders. I'm not using just the native harness (e.g. CC) either, with additional, customized harness, the behavior improves somewhat but are still fundamentally constrained and cannot really be trusted without verification. See my methodology (100% handwritten): https://aperocky.com/blog/post.html?slug=agentic-development-philosophy https://aperocky.com/blog/post.html?slug=agentic-development.... Being a heavy user I think I've ran into every single hallucination that the model can do over development release and operations. I am still a heavy user but there are a lot of value in recognizing where exactly LLM's limit is and work around that.
  • causal 4mo ago
    To me the greatest monument to Claude's poor software quality is Claude Code itself.
    • Aperocky 4mo ago
      Yes, let's build a 40K line main loop! I wonder if they thought claude code need to be more like an LLM to work lmao.
• yoyohello13 4mo ago
  I’m just continuing to get paid as long as I can, while also going back to school part time to train in a role that’s insulated from AI. Having a backup plan at least makes me feel better day to day.
  • causal 4mo ago
    > to train in a role that’s insulated from AI Would love to know more about that role
    • Havoc 4mo ago
      >Would love to know more about that role Anything that can't be done with a screen and internet connection is a good start
    • yoyohello13 4mo ago
      Paramedic
• gxs 4mo ago
  > And then I started realizing: all the knowledge I have accumulated over the years: the trade-offs between implementations, how acquiring works, how to structure idempotency to prevent double-charges, everything, was becoming useless. It’s not useless, at least not yet. And the fact that you recognize this puts you way ahead of the typical HN user constantly crying about how AI could never What’s going to make you a good AI-augmented engineer is going to be treating AI like a good partner Not like a genius, not like an idiot - these are extremes where all the memes on LinkedIn are generated Like any partnership you will see it comes with bad ideas and good ideas - that it will challenge your own ideas and be sometimes wrong and sometimes right Approaching it this way, I think my learnings only accelerated - the conversation is of much higher value because it’s a fast back and forth where I can take a moment to learn on those occasions where its ideas beat mine You are feeling a little insecure, paranoid is not the word, and that’s a good thing Tackle the problem for what it is: I have this sidekick now that can help me bang shit out in a fraction of the time it used to Use the the brain that got you here to figure that out - don’t waste your time on these debating whether ai is good or not or listening to stories about how it’s stupid because one time it suggested something that wrong You’re going to be fine, put AI to work for you Ask me again in a few months but for now you’re fine
• docheinestages 4mo ago
  LLMs can synthesize the domain knowledge so long as it's within their training data. At some point, blindly trusting the decisions they make becomes gambling.
  • tossandthrow 4mo ago
    There is this over indexing in training data that I find quite problematic. I have really good results getting LLMs to read documentation and work of these. This is in domains probably sparsely represented in the training data.
    • docheinestages 4mo ago
      In my experience, even the best frontier LLMs are very likely to make critical but subtle mistakes and false assumptions the more they're trying to one-shot the solution. One-shotting could be thought of as a broad term and varies depending on the use case. You have great results with LLMs because you did the job of finding the right documentation, and more importantly, those who wrote the documentation both had a deep understanding of the domain, and effectively compiled them into a coherent document. In other words, the more vetting, supervision, and research you do, the better the results. Of coruse, this doesn't mean doing the heavy lifting yourself. But the signal is key.
• godlabs 4mo ago
  I code myself now and have given up on LLMs, no matter what, they eventually make a codebase unmaintainable. The uncertainity of LLM generated code has been screwing up with my peace and guarantee I have when I wrote code myself. LLMs are not AI they are Jack. Jack of all trades, Master of None.
• alexpotato 4mo ago
  I've posted this before but worth posting again: I work in DevOps at a firm that has been very enthusiastic about using LLMs (in the good sense). The phases were basically: - try out having the LLM do "a lot" - now even more - now run multiple agents - back to single agents but have the agents build tools - tools that are deterministic AND usable by both the humans (EDIT: and the LLMs) The reasons: 1. Deterministic tools (for both deployments and testing) get you a binary answer and it's repeatable 2. In the event of an outage, you can always fall back to the tool that a human can run 3. It's faster. A quick script can run in <30 seconds but "confabulating" always seemed to take 2-3 minutes. Really, we are back to this article: https://spawn-queue.acm.org/doi/10.1145/3194653.3197520 https://spawn-queue.acm.org/doi/10.1145/3194653.3197520 aka "make a list of tasks, write scripts for each task, combine the scripts into functions, functions become a system" -- END of original post -- What I would add: if you let LLMs do whatever they want, they will happily make code. You can add tests to confirm that the tests work (which you used to do with human code, right?). You can also read the code. When you read the code, you'll find that they sometimes do totally bananas things that still produce working code (I've seen humans do this too but that's another story). In other words, you still need to make sure the system being built makes sense. More succinctly: Coding may be dead but software engineering is alive and kicking.
  • theshrike79 4mo ago
    This is the way to do it. You can have the Big Boy LLM do _everything_. It can and it will do it. It will also cost fucktons of money and take a long time. But if you build tools (with AI) that do as many tasks in the process deterministically as possible and let the AI use those, it'll be a lot faster and cheaper to run it. As a bonus you can eventually drop the expensive cloud AI and run a small/medium sized local model instead.
    • chasd00 4mo ago
      You know, i think harnesses and tools are the next "webapps" for the industry. Everyone is going to be making their own. Some will be great some will be meh but i think that's where things are headed.
• PeterStuer 4mo ago
  I think the one thing the author is underestimating, especially in his "first pillar" is that he is able to coach the models into great results because he already knows the lay of the land. I often make the same mistake. I see people struggle with GenAI, and feel flabbergasted how they succeed to fail, but then if you observe how they work the tool, it is clear they have no idea what to ask or how to evaluate and iterate on the responses.
• eranation 4mo ago
  My prediction is that the review / human in the loop part will become much bigger and more discussed. Current transformer technology will either plateau or eventually we will get to that singularity bracket. (I was a skeptic once but all signs point there) And this means models will eventually get better. The main human value will be - intent (we call the shots of why and what, AI will take care of the how) - taste (everyone now immediately identifies Claude designed landing pages, they all look the same, taste changes with time, and can’t be predicted) - supervision, both before and after AGI, to ensure no accidental damage, no misaligned decision drift, or in the unlikely but still statistically possible case of AI going rouge Anything else (if we don’t plateau) can be eventually achieved. Having that said, the fact AI can do it, doesn’t mean we’ll want AI to do it. If there will be enough demand for handmade creations (with the current anti AI sentiment I can see it having an impact at least as similar to organic food) then we have some hope.
• PunchyHamster 4mo ago
  I think the author missed the forest for the trees - the domain knowledge is what allowed him to successfully use the AI because he instantly knew what was correct or not. Constant use of AI will probably erode that knowledge over time just because of not practising it, but successful use in complex domain needs the domain knowledge to steer it away from icebergs or hallucination or model flaws.
• fithisux 4mo ago
  If the majority of the people have selected a direction you either opt in or opt out. That's the hard truth. Governments do dot care on our future, only on who pays them. This is the tragedy.
• emodendroket 4mo ago
  Do any of us? But I think it's kind of backwards the way it's presented in this article; the raw code part it has down more so than the design sense. I also would point out that, while this thought has occurred to me about the skills being commoditized, in practice I don't see that everyone's getting the same results from the tools. Not sure what's going on but that's interesting.
• deleted 4mo ago
  [deleted]
• dalton_zk 4mo ago
  Use the LLMs to improve your career as software engineer
• canadaduane 4mo ago
  I posted this elsewhere, but I think it still has a valuable insight to bring to the table: https://halecraft.org/software-engineering-is-the-new-manufacturing-engineering/ https://halecraft.org/software-engineering-is-the-new-manufa... > LLMs are regression-to-the-mean machines--they pull junior developers up, and drag senior developers down. Taming them requires trading the romance of 'code as craft' for the physics of manufacturing. The thing I don't know is: how do we decide which direction is most valuable? I can see arguments in both directions--quality vs quantity, essentially. I think there's a strong argument for the value of both: - we need more quantity of software: for a long time, the ability to write software has been locked up, confined to a closed cabal of specialists - we need more quality in software: we depend more and more on software in every aspect of our lives, mistakes are intolerable and should be avoided
  • epolanski 4mo ago
    I have not seen evidence that they are regression to the mean machines. I'm lucky to work with great engineers and their productivity and code quality has become even higher. Wish that wasn't the case, but it is, and that puts also lots of pressure on myself to work more and better all the time. It's exhausting. There are cons too, system's understanding sometimes is not as intimate, which in turn produces less "gotcha" moments that may lead to better design. There's less time to review PRs and make it a choral work. On the other hand way more refactors and experiments can be run, so again, code quality has improved just because if you have a hunch that something could be done better, you can test it for cheap.
    • canadaduane 4mo ago
      I'm curious what you think of as "the mean"? I consider the input training set for an LLM to contain its mean. My hypothesis would be: an LLM alone cannot consistently produce code above the mean of the quality it was trained on.
      • epolanski 4mo ago
        The input training doesn't matter much, besides, the input training is already skewed for code that has been submitted after much trial and error by a dev locally and possibly reviewed. And input has an over bias over open source projects, not crap internal tools no llm has ever seen. There's more to the quality of the output, like prompts, the quality of the codebase (from which the llms learn), the documentation/harnessing, the feedback an engineer provides while reviewing multiple times (in the chat, in the diff, in the pr) etc, etc.
• lordmoma 4mo ago
  looks like you just need a bit of harness for your AI: https://leestack.dev/writing/nasa-rules-for-code-that-cant-fail https://leestack.dev/writing/nasa-rules-for-code-that-cant-f...
• monegator 4mo ago
  Hear me out: what about just refusing to use them? why would i ever want to use a tool that remove the part of my job that brings me joy? Fuck productivity, we were already doing good, when we were able to actually do our job, i.e.: not wasting hours in useless meetings, or doing customer care to idiots who could not be bothered to follow instructions, which i shouldn't be doing in the first place. let the LLM do that, or let the human assisted by the LLM do that. Not my job.
  • dragontamer 4mo ago
    My boss came up to me and said a coworker using LLM tools has shipped more customer solutions in a week than basically what I've done in 3 months. The bosses are out to force people like you to use AI. And have been for months. Maybe not your boss yet, but it swept through my office dramatically. Maybe two or three months from limited tests to now today FORCED usage of AI (people going around the office asking constantly if there's any AI that can help today). ---------- This has a few toxic effects. 1. You are not allowed to complain about code quality issues anymore. Any complaints are met with okay, we will get the AI to fix it. No discussion, no elaboration. No one in the office is even interested anymore. AI solves everything. 2. You are basically in a position where you are forced to use AI, whether you want it or not. 3. I expect code quality at my office to drop dramatically as fewer and fewer office mates give a shit
    • monegator 4mo ago
      Ah, if (2) happens i will just walk out. No more brain. I refuse to work on those conditions. And if that's the situation everywhere, i'll just go back being a tradesman, i love working with my hands, and there's been abundance of work for any skilled individual in any trade for more than a decade. Now, my attitude may change when we get back to decent prices for hardware capable of running local models. I can be fine with local models, but not the current corpo owned shitshow. See what's happening with anthropic. They reserve the right to keep the chats for security concerns if you use bad words in the prompt, even if they are breaking contracts. Gee, who would have fucking guessed? Their most valuable asset is their training data and OF COURSE they're going to suck up new brain activity from everywhere they can. (like who was really surprised when it came out that microsoft was training copilot on private repos?)
• amirathi 4mo ago
  Author says Claude now one-shots distributed systems bugs that used to take him two days but most top comments here are still playing down frontier model capabilities. Are we collectively in denial? It's understandable as the craft as we knew it is being disrupted by tools that have improved at an astonishing pace.
• dalton_zk 4mo ago
  The title should be: LLMs are changing my software engineering career and I know what I should do
• lanstin 4mo ago
  Like all my C skills that I spent ten years mastering aren’t that useful either. But being a hard worker, smart, able and eager to learn new things, and able to judge accurately if I am helping people out (boss, coworkers, customers), these are and always have been the keys to my being a good hire. It’s a great world for smart, kind and hard working people. No idea where the LLMs are going but it will be interesting and I will be able to use and explain them in useful ways for people.
• dpcan 4mo ago
  The problem with “code quality” and LLM’s taking over your first 3 “pillars” is basically that LLM’s don’t care. I recently had Cursor evaluate a huge code base that we took over. All public stuff, nothing scary security wise, but it was so convoluted that it was taking me forever to find the bugs. It was written by a person, I should add. I did this in cursor and after one prompt using Plan, it found all the bugs, created a plan to fix them, it looked good, and I had the agent create the fix. It took 30 minutes. The client had this project in the hands of another company without ai tools and they couldn’t fix the bugs she told them about. So my point is, if we are holding on to our jobs for dear life on the basis that “code quality” matters, you might as well kick down the 4th pillar. Like I said, the LLM does not care.
• ilaksh 4mo ago
  Jobs have always been a bad deal, especially for most people. Very unfair. Less unfair is entrepreneurship. LLMs (VLMs) etc. should make that more feasible for a broader range of people.
  • philipallstar 4mo ago
    > Jobs have always been a bad deal, especially for most people. Very unfair. Less unfair is entrepreneurship. LLMs (VLMs) etc. should make that more feasible for a broader range of people. They can't be a bad deal and also the best possible option for the majority of people (as most people choose employment). Entrepreneurship increases risk, which is the tradeoff for more upside.
• eqiq 4mo ago
  [flagged]
• dwa3592 4mo ago
  I don't know how else to say this but LLMs are just word calculators. They are becoming better for sure but at this point even Claude 4.8 is absolute shit at any complex task in a not so common field. I have been working on terrain contour matching algorithms for the last few days and, oh boy are the predictions about AI taking over the world wrong. Its the highest level of bullshit I have ever come across in my life. I ended up writing 100% of the actual algorithm myself. It's a productivity mess.
  • ThrowawayR2 4mo ago
    > "terrain contour matching algorithms" That's an extremely niche specialty though. 99% of software development jobs are web frontend/backend or mobile/desktop apps and they are more at risk from LLMs.
    • dwa3592 4mo ago
      It's only good at churning out reliable boilerplate. If you want a genuinely good frontend - human creativity still beats AI any day today. Sure it's helpful but I think frontend devs will land just fine on their feet. At least, I hope.
• medhir 4mo ago
  [dead]
• nsxwolf 4mo ago
  I started feeling like a factory worker well before LLMs. My reputation and network stopped mattering and it all came down to take this assessment and do this Leetcode to prove you are a good enough replaceable cog. I have about 15 more years before retirement and I doubt there is anything left to look forward to in my career.
  • stuxnet79 4mo ago
    I echo this. Software development stopped being a dignified profession a long time ago once we fully coopted the metrics / performance theatre that the MBAs brought in. I'm talking agile / SAFe / leetcode / mandatory "side projects" as a filtering mechanism etc. Now that clankers are generating full end-to-end products with an easy to understand dollar per token cost outlay the MBAs have finally gotten what they've always wanted. Good for them! But it also gives us ICs an opportunity to switch to (hopefully) more fulfilling career paths. For me personally working with computers was always more of a hobby anyway. Ideally I'd like for it to stay that way but we will have to see how the next 5-10 years shake out.
  • pjmlp 4mo ago
    That came to me a few years ago when cloud, SaaS and iPaaS products took off. We were still coding, however most of the work was reduced to serverless, or configuration of said cloud products. Now even coding serverless is going away with AI based orchestrations.
• greenbeans12 4mo ago
  From someone who thinks there's too much AI doom right now and is a glass half full optimist: If you are a software engineer reading this and panicking, don't. The author only mentions his codified, stable knowledge like you'd get from a distributed systems O'Reilly book. There's no mention of the functional elements of a software engineering role - incident response, working with auditors to define and maintain controls for internal services, handling escalated account support & fraud, working on DevEx, selling shovels (MCPing your consumer-facing APIs/services), getting on customer calls to help sell your company's X feature, managing people downwards and upwards. The piece kinda reads like remorse over sunken costs and attachment of knowledge to personality. If you twiddle your thumbs and stay static in your role, you will be replaced. It's the differentiation that sets employees apart. And attaching yourself to functions instead of knowledge is the only way to stay afloat.
• bilater 4mo ago
  The bitter lesson is that there is no domain that will be left which AI won't get good at eventually. So really you have two options: if you actually believe the timeline is long you can keep retreating to the sectors that will be taken over last (emotional support nurse etc) or you can just say if you can't beat me join em and try to supercharge your career/project/life with AI now so it improving helps you rather than hurts you.
  • DrewADesign 4mo ago
    The supercharge bit missed an important fact: that strategy is very temporary. Getting expertise in software development takes a long time. Getting expertise in these LLM tools takes a lot less time— the combination of LLM expertise and dev expertise is the useful part. If LLMs make working developers, say, 35% more efficient, that’s going to be many thousands of people out of work, many of them being the most experienced and expensive we have. It’s not like those people are all going to give up immediately and become DoorDash drivers — they’re going to fight tooth and nail to get a job that uses their existing hard-won expertise. That means they’re going to level up their LLM knowledge, be willing to work for a LOT less money, and bring down everybody’s wages in the process. Companies don’t pay people based on the amount they bring to the company — they pay people based on the going market rate. That’s about to be a whole lot lower. So no matter how much you supercharge, you’re only buying yourself a little while until the labor market catches up. Nobody in development is safe. The entire field was so busy seeing how fast they could saw branches off of a tree that they didn’t realize they were standing on the wrong side of the cut, and the business side of the industry could not be happier about it. You’re basically working as a manufacturing engineer in the 90s US specializing in moving processes to offshore facilities. Probably felt pretty clever for a few years until they got the pink slip. Honestly, the only hope that the dev field has is this all being so economically inefficient that the industry as we know it collapses after the VC subsidies run out, and we’re going to pivot towards much more reasonable interventions with local models and such.
    • bilater 4mo ago
      you're being a doomer and only looking at how AI will take your job or suppress your wage. try to flip it around and see how you can do more. layoffs are coming and I have said as much in other posts but the top AI engineers will make a lot more money. ultimately they will get replaced to but in that scenario we should have reached AGI abundance.
• deleted 4mo ago
  [deleted]
• jppope 4mo ago
  Yes, Code Monkey jobs are gone... I can assure you though that there are plenty of hard problems that reduce human suffering which still need humans to solve them.
• lcb13 4mo ago
  “We were taught that generalists and specialists will always have their roles. But now the market is shaping everyone into becoming a generalist.” I see this as a negative, the whole once everyone has everything than everyone has nothing type of argument. The company I work for believes strongly in keeping humans in control and in the loop which is something I’m grateful for but at the same time who knows how long that will last. Companies are starting to get their AI bills and realizing how much this AI usage actually costs so only time will tell but I hope, for the sake of everyone, that those with the knowledge described in this article make effort to keep their brains in shape.
• _pdp_ 4mo ago
  10 years of software development is still young and inexperienced.
• aplomb1026 4mo ago
  [flagged]
• anupshinde 4mo ago
  Domain knowledge and architectural skills are not gone. I can say even Opus 4.7 and GPT 5.5 get domain-specific stuff wrong. I use both, because when I am not sure I ask both and also check with Gemini. But these days, I ask those even when I am sure - its like I get something confirmed from a peer. And yes, you have to be the gate keeper - the speed breaker in a way - LLMs still lack a lot of context. And even if they get more context, they will end up costing a lot and still have no accountability. In accounting, one wrong entry and the whole system can be seen as "unreliable" - thats why you are needed. The interesting part is "who takes over" - accountants who become coders, or coders who become accountants. And the latter looks more likely, in any profession. And when that happens - the bar will be raised in these other white-collar professions too, just like what happening in tech. Opus is getting good at architecture - I need lesser "pushbacks" either because I have learnt to say the right thing or it has learnt to do the right thing - I do not know which one.
• strangescript 4mo ago
  Agents are getting good but professing they are surpassing you in domain and architectural knowledge with no special prompting is basically self reporting at this point. That could be your job wasn't that complicated or your personal knowledge wasn't that strong, either way, same result. Don't get me wrong, I am sure we will get to all three of these pillars, probably by next year. I am not naive.
• ChicagoDave 4mo ago
  The OPs domain/subject matter expertise is the part that should elevate their career. Understanding how large applications are constructed should also remain a pillar. The coding and debugging part will be GenAI and possibly guardrails (harness engineering) tuned specifically for fintech, which they are also well-suited to implement.
• z33zain 4mo ago
  [flagged]
• AJRF 4mo ago
  We have all the AI tools you could bare to mention, but we still don't have anyone but programmers shipping things. Why aren't the designers and PMs shipping things if these tools are so good?
  • hyperadvanced 4mo ago
    I don’t know about your co but at my job we very much have non SWE shipping their own (mostly garbage) apps
• system2 4mo ago
  This reads like a self thought ecommerce/small company employee finding its place in the tech world. These people were erased first, understandably. I am meeting more and more of the same type of people. I had a friend in LA who was sure that CSS and HTML were enough for her to be a "Senior frontend developer". This year she moved to Tennessee and is trying to find a rich husband because she can't find a single job.
• wcfrobert 4mo ago
  > "Now I have CLIs that one-shots bugs across distributed systems for me. Bugs that I couldn't solve in the past. Bugs that would take 2 days of full-time debugging. Bugs across distributed systems that lack distributed observability. 90% of the bugs are one-shotted now, including bizarre race conditions, unexpected corner-cases, third-party integration issues, undocumented API edge cases, everything. I hardly have to intervene." The fact that the author can articulate _why_ the AI is getting so good is kind of a moat for specialist, right? Imagine a layman prompting without domain expertise: "There is likely a race condition here + [long-winded explanation and analysis carefully guiding the AI]" Degenerates to: "This button is not working, please fix. I don't care about code. Decide yourself" Degenerates to: "Claude make me money"
• grokcodec 4mo ago
  Maybe denial is a river in Egypt, but I (most of the time) believe that the glass is half full and we will need MORE humans as LLMs gain in ability. My thesis: 1. most jobs are created by small to medium size enterprise 2. the throttle for new SMEs has been people, money and ideas, in that order 3. with LLMs being a force multiplier, fewer technical people are needed but some people still ARE needed 4. with less throttling, MORE SMEs will be created with more jobs - they will be able to do more, faster, but still need some human oversight. Also, what is the point of software if it is not to serve human needs? Also, in open source, community building and tending is a very human enterprise that will not be replaced by bots any time soon. So, as coding becomes commoditised, perhaps the soft skills backed by technical knowledge will be the complementary skill that increases in value. Or, maybe it's time for me to become an itinerant folk musician.
  • oytis 4mo ago
    Software boom due to SMEs looks very unnatural to me, because what makes software so special is its ability to scale, so it naturally tends to monopolization
    • jgilias 4mo ago
      That was in the world where making software was _prohibitively_ expensive.
      • oytis 4mo ago
        Well, alright, scalability + expensiveness create ideal conditions for monopolization. Assuming it's cheap now, scalability still doesn't go away. So it's a) cheap b) easily reusable, you make it once cheaply and quickly and it stays with you forever, and can be used by others too - I don't see a condition for lots of job creation in software engineering here.
        • jgilias 4mo ago
          One could argue that scalability matters more when software is expensive to make, as you need to reuse it to make the cost worthwhile. So, for context, two data points I have that make me want to argue for the opposite side. First, some time ago I worked for a startup that had a B2B offering that in most cases involved integration costs to align with whatever the client was already using. We tried to eat this as much as possible, but we still had to have some “integration price” we asked. More than once we had a potential client who just couldn’t lift it. They needed the software but just didn’t have the cash buffer for the initial cost (us neither). With how things are now, we’d have onboarded all of them. And much faster than it normally took. And yes, they still would have bought our solution instead of rolling their own (see the next point). The next point that kind of ties into the previous one if you squint. I’m in a position now where I see non-technical people building stuff with AI. _Most_ can’t. As an example, the AI says they need a database. But they don’t really know what that is, and deploying one sounds scary, so they ask the AI if they can build it without a database. And the AI happily complies and makes a “CRUD” API that “persists” data in RAM. And the AI is not being dumb here. The best, most perfect model is still an LLM at the end of the day, so it completes the context window. Sure, you could make a mod that “sticks to its guns” more, but that comes across as the model being “non-compliant” and “difficult”. Now, I’ve also seen non-technical people who have succeeded. But then they have the kind of a mindset that they could’ve been engineers in the first place in different circumstances. But also, even they build fragile monstrosities that they don’t understand. So, going back to the first point. Our clients were deeply nontechnical for the most part. Most of them wouldn’t even have attempted to build their own. But also, getting the system up and working involved more than just code - relationships with suppliers, some legal stuff, etc. So, I can totally see how the amount of software produced might grow exponentially leading to “pre-AI” engineers being worth their weight in gold due to that. That doesn’t exclude a painful transition though.
• mg794613 4mo ago
  Every 3 lines coming out of Claude has got a bug in it. There is going to be a lot of demand for people to clean it up.
• titaniumrain 4mo ago
  find another job but software engineering :) simple
• notepad0x90 4mo ago
  LLMs mean less devs are needed, not no devs. even after serveral more decades, they'll need steering. I've seen agents stuck chasing one issue, when to me the issue was obvious, but I can see how the model would rule out the obvious easily and move on, but my instinct/experience tells me that's where I need to focus time on. This translates into costly token-waste. Secondly, it isn't simply "quality", the LLM might generate something that's good quality from its perspective, but it simply won't consider things unless it's explicitly told to in excruciating detail, and even then! understanding things from a simian point of view can't be perfected without that simian experience as part of its training. It can come very close but not quite. Think of it this way, who needs engineering managers, project managers, scrum masters,etc.. if they're employable then surely actual devs that can tell what good architecture is vs bad, good code vs potentially bug code is are also employable. But the number of devs needed, that demand will obviously decline dramatically. At the same time though, there are other careers that require programming and software dev as part of your skill set. Simply integrating LLM-enabled solutions into real world workflows is a new area that's very young and immature. Let's not act like we're suddenly in some sort of post-scarcity utopia where all problems are solved by LLMs, where tech can solve problems, there is demand for those who can use technology to do so. However, I see a lot of people attacking the technology and resisting change a lot, and to those I suggest they look up every single technological revolution and see about the fate of such people.
• rglover 4mo ago
  Based on what I've been seeing/reading online the past ~6 months or so, I think there's a self-fulfilling prophecy going on here. Developers are concerned about jobs going away, but how often are they pushing back in their orgs about how AI works? In response to "are you using AI to move faster," how many are responding with "yes, but there are some things you should know..."? If there's no pushback and just pure acceptance of stuff like tokenmaxxing, then what does anybody expect when the broader narrative around AI is that it can help a novice to grind out miracles (i.e., "holy crap, if this is what a novice can do, what can an expert do?!")? Of course leadership is confused because (it seems) few are asserting expertise, saying "no," and stating a clear case as to why they're doing that. The default excuse is "I don't want to lose my job" (which is a fair reaction to all of this, especially these days), but it's worth considering when/how that choice is actually just shooting future you in the foot later. It seems there's a broader trend toward compliance more than there is "you hired me to do this job properly, did you not?"
  • rybosworld 4mo ago
    For most companies that I've worked for, pushback is normal and expected as long as you've built some trust/rapport with your management chain. However with AI, it feels different. I have seen both technical and non-technical managers tell engineers something to the effect of "you aren't prompting correctly" if they aren't able to get the task done within some preferred time frame. We are seeing the industry revive metrics like lines of code, number of tickets closed, bug's found (looking at you Mythos), and now even "tokenmaxxing". It's exhausting to push back on. These are all things that we know will be gamed. But the individual that brings this up might be viewed as "anti-ai" or something. If you're an IC, I do think the best thing to do is just go along with it. Sooner or later we will see more shocked-pikachu-faced executives when they realize that engineers are spending tokens just for the sake of it.
    • bluefirebrand 4mo ago
      > If you're an IC, I do think the best thing to do is just go along with it I personally think the best thing to do is start retraining now so you aren't screwed by the time this all topples
• hintymad 4mo ago
  There's no doubt that LLM increases our efficiency, be it producing prototypes, generating production code, debugging our systems, or more. So, if there's no more demand or reduced work hours, some of us will lose our jobs. I certainly hope the Jevon's Paradox kicks in faster, as in months instead of years, let alone decades. If we don't consider the potential loss of our jobs, on the other hand, isn't it great that we don't have to repeatedly do what we already know how to do? I mean, how many times can we feel the thrill by writing the same CRUD applications? How many times do we have to design the same idempotent APIs? It's also a relief that we could spend way less time figuring out mitigations or root causes when there is a production incident. This reminds me of the scribes before Gutenberg's moveable-type printing press. They spent their life in scriptoriums copying the manuscripts by hand. They earned three times of the average income of their times. They were highly skilled labor. It required years of training, deep literacy, and a high level of domain expertise. Yet, history showed that even highly specialized expertise can be mechanically reproduced. That appears to be exactly what LLMs are doing for us: automating the digital equivalent of manual transcription, such as setting up the repetitive boilerplate, sketching out the standard APIs, finding predictable bug fixes. I'm not sure about others, but I have to face the same existential question today: as software engineers, where does our true value lie? Is it merely in learning, memorizing, and, reproducing patterns that others have already built. More often than not, patterns that an LLM can now piece together better and faster? Or is it in taking everything we’ve learned and applying it to solve entirely new, messy, and uniquely human problems? If our worth is tied to how well we copy the past, we are already obsolete. Our value has to shift from being human repositories of known solutions to being creators who venture into the unknown. It is, of course, easier said than done. Hence I have likely the same level of stress as other software engineers.
  • prerok 4mo ago
    But... software engineering was never about the boiler plate. Or adding the extra parameter. It was about knowing how to fit the new use case into an existing code base, respecting the architecture, and sometimes rearchiteting the solution. How easy the latter was is really dependent on whether the code/arcitecture respected the low coupling, high cohesion principle. Now, some of this can be coerced into LLMs but it takes work and careful study of the changes. Sometimes they get it right, many times they do not. So, you have to go back and forth with them. If you know what they should have produced. SWE is far from dead. We just let too much slop into the codebase because we're overwhelmed by it and not incentivized by leadership to care. Code quality will likely drop to the point where even the leadership will notice and it will normalize again. There's nothing like a high profile customer calling out a problem that was vibe coded. It has started already and will be happening more and more. Don't worry, the hype will be over in some time.
• Melatonic 4mo ago
  Software engineers really need to unionise. ASAP.
• d1553636d 4mo ago
  [flagged]
• Reason077 4mo ago
  > ”If you don't steer them, they'll hit a circular dependency issue sooner than you think. Will duplicate code. Add unnecessary comments. Mix up pure functions and side-effects. Disregard the principles of SOLID.” This is one thing I worry about with AI-driven development on large projects. Every time someone comes along to add a feature it’s likely to lead to wheel-reinvention: dropping in a new bunch of AI-generated code rather than specialising, refining, and reusing some existing code. As the years go by this is going to lead to complex, hugely bloated code bases that are only maintainable by AI tools…
• george_max 4mo ago
  I see many comments saying, "AI can't do X with 80-100% accuracy; therefore our professions are in good hands." While I don't want to sound overly pessimistic, the models are improving at a rapid rate. If asked ~3 years ago where the state of the models are today, it would sound like sci-fi if answered, "the models are creating full MVP apps in ~30 minutes with one prompt". The hurdles the models are facing now, like reducing hallucination rates, ensuring compliance, and keeping a clean codebase, do not seem far away from being resolved IMO. Fetching specific information is already partially done with various MCP servers / RAG. I am, of course, a bit worried about the future of software engineers. If these quirks are resolved, where do their professions fit in the industry? Delegating tasks to the AI model? Unfortunately, this does not require years of expertise, which is a double-edged sword. Reviewing AI's output? Ask it to explain each line not understood. I think we will see more waves of larger layoffs, similar to how human computers were replaced by digital computers. To some, doing complex mathematical calculations mentally is a fun task / challenge, but it is ultimately significantly slower and more error-prone than calculating with a computer. In the same way, I think hand-crafting code will be seen as a fun "challenge" and AI will be seen as the "modern-day calculator".
  • rsalus 4mo ago
    I don't know, even if AI allows two engineers to do the work of six, companies will likely just use that efficiency to expand their scope. I think we'll see short-term layoffs and a more stratified engineering field during the transition, but the fundamental need for deep technical expertise isn't going away.
    • coldtea 4mo ago
      >I don't know, even if AI allows two engineers to do the work of six, companies will likely just use that efficiency to expand their scope. Not really. It will be a cuttthroat landscape, and the scope wont matter as much anymore. First because everyone else will equally be able to throw LLMs at the scope, but also because the scope has natural limits: your market fit, customer expectations, and (for software/hw products) physical world/manufacturing limitations. They'll want to reduce their margins.
• oldnewthing 4mo ago
  Hey, I agree with you. I and my team have the same existential worries. This was one reason why I bought my own subscriptions to Claude and Codex to learn and skill up. I have been using that to intensively do side projects, curating prompts and workflows to see how these new tools fit in my toolbox. I have been bringing back the learnings to my team so that they can upskill as well. For context, I use Claude and Codex (side projects, Max and Pro plans respectively) and Gemini at work. The key takeaway I have is: These tools have let me climb up the value chain ladder. Even with Claude (Max plan, Opus 4.8, High Effort), it makes tons of mistakes, assumes a lot, misses nuance and doesn't really think through every aspect of the problem from every angle. Limited memory, lack of full context and a lack of experience with real world distributed systems means that the initial solutions they offer need a lot of iteration and refinement. Just like any junior engineer would need to do. So, you might feel that with a LLM, "this should just be an hour" but it usually becomes a 2-week exercise for me. Which brings me to what I tell my team repeatedly: "the only person with the big picture is you." I ask them to focus on thinking, ideating, refining. Do quick PoCs, talk to customers, discern what they are trying to achive, and what you can do to solve those problems. Work with Gemini (we can only use Gemini at work) to iterate until you are comfortable with the full solution end to end with all the nuances. Then let the agent code. This moves you up the value chain from being a programmer to a problem solver. That's what software engineering has always been about: solving problems. Don't be discouraged. In fact, I am having more fun, am more energized and loving my craft even more now with LLMs. I am able to write down my thoughts, iterate on them and create a one-pager for ideas fast and get them to my team for them to think about. Sure, probably half of them we discard because it's usually not a "now" problem but we put that in our backlog to dust off when the first customer asks for it.
  • jval43 4mo ago
    Problem-solving is not the same as engineering or computer science though. Problem-solving can be done by an "analyst" or whatever these types of jobs are usually called.
    • oldnewthing 4mo ago
      Not sure what value your comment added. Software engineering is also problem solving. Are you arguing it is not?
• PLenz 4mo ago
  Start advocating for a wealth tax
• visarga 4mo ago
  > All my finance and payment domain expertise, all the debugging intuition and distributed system knowledge earned through hours of sweat and tears, is now promptable. In ML it was even worse, we had to throw away a decade of experience, made irrelevant by the new approaches. Even the most revered activity - designing new architectures - became too expensive to do in real life. Fine-tuning models is what we do now, prompting and evals. Like 90% of what we used to learn is no longer needed. And yes, LLMs can do most new ML activities too, they just need light supervision. I am sometimes ashamed to admit I have stopped coding 12 months ago and never wrote one more line, that after 35 years of coding manually. But I also think we will never be without LLMs again, so no point in preparing for 2016 in 2026
• mrandish 4mo ago
  Of the posts I've seen by senior devs who assess recent events and end up roughly here: > I'm still employed and I see myself employed for a foreseeable future. But I don't know what to think about the long-term ... Maybe I should consider transforming my woodworking hobby into a profession. This one is notable for having all the clues pointing to why that's not the end-state this is headed toward, and yet... still not quite see it. > I have no domain expertise that another Sr. engineer steering an LLM cannot match. It's clear he's developed a significant competence in "steering an LLM" but the depth and value of that aren't apparent yet. After ~70 years, software development is now in the early stages of its first tectonic disruption. In the moment, these kinds of tech disruptions mostly appear to be displacing jobs but, historically, we understand the displacement is one part of a larger shift that's vertically compressing roles, functions and labor value. One steam shovel doesn't just displace dozens of pick-axe swinging diggers, it changes the roles, functions and competencies required across the entire supervision and management stack of "make tunnel through mountain" from the crew bosses and site managers to the tunnel engineers and business owners. The author seems to be successfully navigating this shift but is still mid-disruption, so he and his management aren't yet able to see all the new competencies required or appreciate their value because it's all so new and still evolving. The rapid shock of agentic coding LLMs is especially disorienting because it's the first dramatic disruption in the field. > review the code and steer the robot. Historically, it's not surprising those few words are bearing so much weight and unappreciated value. Steam power was a similar shock to every field which relied on earth-moving and shaping. The big machines were quickly deployed, but it took quite a while for all the disruptions to both new and existing roles, functions and necessary competencies to be understood and appropriately valued. I imagine some top pick-axe swingers who'd graduated to being crew bosses and site foremen ended up driving or directing early steam shovels. In the first months they probably had little appreciation for the tremendous amounts of tacit new knowledge and practical expertise they accrued while keeping the steel beasts working. They were too busy being both amazed at the sheer power and frustrated by the constant scalding burns, tip-overs, blown boilers, landslides (too much weight, too little support) and cave-ins (dug too much tunnel, too fast with too little scaffolding), etc. A big difference in the analogy is the first 100,000 steam shovels weren't sold at ~1/10th their actual cost and simultaneously delivered to job sites worldwide in six months. Software engineering is also unlike earth-moving and tunnel digging, in that the full costs and consequences aren't as visible or immediate as cave-ins and avalanches. The prices of 'steel beasts' are already going vertical with no end in sight and, over the next 18 months, I suspect "management" is about to gain a more viscerally accurate appreciation of the catastrophic costs of digging 'too much tunnel, too fast' absent the close supervision of highly skilled experts in directing all that newfound power constructively and not destructively. Between the skyrocketing full cost of operation and the consequences of poorly managed, non-expert execution - we'll start to see the broad outlines of the new equilibrium take shape. In the steam era it over a decade for the ecosystem to understand how to even draw a new org chart accurately, label the boxes and appropriately value proven competency where it mattered. The faster the disruption, the longer it can take for all the pieces to rebalance and stabilize around a new equilibrium. Today, the author doesn't know all that he already knows and doesn't yet have the visibility to see how the new domain competencies he's rapidly accruing are creating a different kind of role that could be even higher value.
• wolfgangbabad 4mo ago
  In my opinion the LLMs in the "cloud" reached plateau. Still the same probabilistic hallucinations. No idea what they gobbled up. It's a non-reliable circus type of thing. In fact I more and more go directly to Wikipedia or Grokipedia (if you want to know about Odin etc). There is more and more guardrails and talkbacks. They try to make it more human which makes it even more unusable. My guess, more and more marketing people get involved and things turn to unusable shit. I am more optimistic about local llms in a few years where there won't be any guardrails and you will be able to tweak the model how you like and not some marketing specialist at OpenAI or Anthropic.
• samdonovan 4mo ago
  [flagged]
• WhyNotHugo 4mo ago
  Woodworking sounds like a solid way to steer a career. Un-impacted by LLMs, or any trend/hyper or that matter. Great for keeping the body active after decades of sitting all day. Your produce (literally) tangible products. And above all: there's always a need for more skilled carpenters.
  • tartoran 4mo ago
    Most of us would not be able to become woodworkers or carpenters for a living. If white collar jobs get so affected by AI probably the competition in blue collar jobs would produce the worst race to the bottom.
• sathyayoshi 4mo ago
  [flagged]
• giancarlostoro 4mo ago
  I say this every time: if the LLM is saving you on time, its time to rethink how you spend that time which includes reading the code, reviewing documentation of your preferred stack / programming language, re-learning concepts you feel like you've gotten stale on, and just keep your mind growing on these things. Some of the best devs I ever knew before LLMs were always reading official documentation and reviewing existing code.
• dyauspitr 4mo ago
  We are finally getting past the denial phase
• 3vo-ai 4mo ago
  [flagged]
• customguy 4mo ago
  > Nobody needs A or B-grade codebases anymore because they're being made for LLMs, not for humans to read. But however effective LLM may be now, shouldn't they be even better if trained on and working in really, really good codebases?
• elzbardico 4mo ago
  I don't get those depressing articles. If anything I've been working way more with LLMs and working harder. I love that Codex added "Steer" to the chat, because I fucking pay attention to the conversation traces on coding agents and I was tired of the PANIC ESC - "No, that's not what you should do! We use a visitor to calculate all that stuff, I just need you to implement another visit method for this new Stuff according to the rules". Nothing says you shouldn't write any code, in fact, I think that starting from a n interface and a few clients is superior to simply describing things only in natural language. Lots of refactors like extracting method, extracting interface, renaming symbol are way faster, cheaper (no tokens) and less error prone using the IDE. When I am not sure about the concrete design to implement something, I talk to the coding agent, we discuss types, i suggest patterns, I wrote a small stub here and there, maybe a couple unit tests, but I like to activelly engage with the coding agent as if I was pair programming. Yeah, I am not a fan of fire and forget, I see no point in being able to control agents remotelly, but nobody is complaining I am not fast enough. It is perfectly possible to have the huge productivity gains coding agents give you without entering vegetative programmer mode. You just need to engage yourself in the process. You can describe the different categories of something, or you can go ahead and create an enum in rust, you can create a pydantic validator, a few tests here and there. The agent now has something more concrete than a natural language description, it has the compiler to check his code, it has the unit test. The flow becomes faster. You can mention in your prompt that the agent should use AWS SDK v2 in your Go service, or you can go ahead and add the imports and the initialization somewhere in your code, the second option is a far stronger nudge towards the right direction. The time you used to waste trying to shoehorn some stack overflow answer to your problem, now you can use to actually read the documentation of whatever you're trying to use. Go ahead, read it fully, you now have time to understand it deeply. The grunt work, the toil will be taken care of by the agent in a few minutes when you're finally feel yourself ready to move to implementation, because now you have the deep knowledge to take the best possible decisions. There are plenty of places for you to apply your knowledge: the agent may write a correct function, but then this function does a remote HTTP call in the context of a database transaction, so, what happens when the remote http endpoint has a spike on latency? And what if the tables involved on this transaction are a hotspot in your application? You can't add all those small details in your context all the time, you can't add all single corner case and potential pitfall to your AGENTS.md. Of course, you have to up your game. If all you ever did was completing JIRA tickets without thinking much about it, yes, there's no much you can add to the process beyond what your coding agent can do. But this is a choice. We can either create a humongous era of slop and technical debt with coding agents, or we can use its hability to free ourselves from toil so we can finally improve our code in correctness, performance, efficiency, efficacy, security and compliance all the while keeping the business happy. We can either use LLMs to have tens, hundreds, thousands of THERAC-25, or we can use them to liberate our time so we can do the deep work that ensures that you can't possibly deploy a THERAC-25 in production.
• matheusmoreira 4mo ago
  I think this is our one chance to build a post-scarcity society. If we fail at this now, things are likely to get pretty bad, economically speaking. For everyone, not just software engineering.
• aos_architect 4mo ago
  [flagged]
• roncesvalles 4mo ago
  AI slop. Prompter probably prompted "don't make it sound like AI slop". But one can still make it out.
• elitehacker1337 4mo ago
  I was pretty worried until my company started letting designers and PMs contribute code. They can barely get Codex to do anything. The few who are actually contributing meaningful changes have a SWE background, and they are still doing a pretty bad job at it overall
• MarkSamuels12 4mo ago
  Yea, I don't know if I fully agree with this. You are not going to be able to have a vibe coder design, develop and implement a system of moderate complexity without blowing everything up. A big part of using applications like Claude and others is having the conceptual understanding and experience with Computer Science concepts. These are things that vibe coders will never have, if they did, they wouldn't be vibe coders.
• deleted 4mo ago
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• link89 4mo ago
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• MetaWhirledPeas 4mo ago
  I'm probably a good candidate to direct a platoon of agents. I'm a generalist and I think in terms of business requirements. But I'm not sure I want to. Coding captures my imagination, and directing agents just plain doesn't. Or maybe it's more than that: maybe I'm off-put by people who have no need to be in the immediate AI race spending a lot of money to get ahead without asking what near-term problem they are trying to solve. It's depressing and makes the whole field more depressing. My advice for them (if they cared) would be that soon all this will be even more batteries-included, to where any dunce can dial up a production-ready app with a sentence. There's no need to rush; when it happens you'll be better off not having wasted millions trying to be on the bleeding edge.
• gitaarik 4mo ago
  I don't know, I've been interviewing a lot lately, for jobs that are specifically looking for engineers keen with AI. But they still drill me on the technical stuff, whether I really have the years of experience I claim. I guess they don't want just any script kiddie. And that seems very logical to me. So I don't really see the big issue. They still want experts. You just shouldn't do the same stuff you did last 10 years.
• istvan0 4mo ago
  > Sure, humans should steer the agent to prevent spaghetti codebases with circular dependency graphs. We don't want F-rated codebases that are impossible to touch without breaking something. But a C or D? It's now fine. Nobody needs A or B-grade codebases anymore because they're being made for LLMs, not for humans to read. Your job is now to get the LLMs to write good code the same way you would do it if instead of AI agents, you would be leading a team of humans.
• jacobjjacob 4mo ago
  I don’t think that my career has been eroded by even 1%. The areas of erosion listed by the author feel like reverse order to me. The domain is knowing what questions to ask. That’s the last thing to be replaced. I think that if you are a skilled software engineer and can adapt, you will be amplified in all aspects. If you just like writing artisanal code, you might have a bad time.
• altern8 4mo ago
  There is no way that LLMs can replace human engineers. They're often wrong, dumb, and would turn any code into an unmaintainable mess in days if left unchecked. I use LLMs every day because I can do less work at my job, but they suck and I would never use them for a personal project besides for very isolated and self-contained components. It's a lot of marketing and hype.
• ixeption 4mo ago
  I really think that this blog is part of the IPO story from Anthropic or OpenAI. Because the reality is: A generalist can simply not guide the LLMs through the system nor can he/she verify the output. LLMs are force-multipliers and if there is nothing to multiply, it won't work. As long we don't have AGI, humans will guide AI and if we get AGI, that's not something to even think of anymore. Software engineering was always about automation, if you want to be an artist, you better look for something else.
  • fuck_google 4mo ago
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• kolesnikov-arch 4mo ago
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• do_anh_tu 4mo ago
  Yeah my 10 years experience with Python and Django just flushed down the toilet with the advance of AI, struggling to find a job for a few months now sadly :(
• ProxCoques 4mo ago
  "they can do that because there's plenty of articles on the web on how that shit works along with all the technical documentation, and we have blog posts explaining how to apply the technical tools to the domain." Does this imply the future of LLMs is either that they acquire reasoning, or that they (or even engineering itself?) reach a plateau if humans are no longer writing about how to do things because the humans are using AI?
• entropyneur 4mo ago
  I don't care as much about LLMs deprecating my accumulated knowledge. After a quarter of a century in the industry I have plenty of stuff in my head of purely sentimental value. But for me, the real catastrophe is that they took away all my motivation to learn which was the main work driver for me. Anything I can learn now, the models probably already know or will learn soon enough. Steering LLMs isn't anywhere near being a "deep" skill I'm used to having and it too is being eaten by the agentic tools faster than we learn it. The "make it good" button is coming. And I hate it.
  • tartoran 4mo ago
    Do stuff with your knowledge, apply it wherever you can. AI does not have have any agency to do ... anything.
• HeartStrings 4mo ago
  Become a soldier
• thatsadude 4mo ago
  So are my DSP/Audio ML career, I spent decades acquiring the expertise. Now at 40, I don't know what to do if I lost my current job. Very sad, but from economic POV, I also don't need junior engineers in my team anymore.
• kykeonaut 4mo ago
  > I have no domain expertise that another Sr. engineer steering an LLM cannot match. Sounds like the Dunning-Kruger effect to me. "I can do this with LLMs, therefore any Sr. engineer can do this with LLMs"
• teleforce 4mo ago
  I sense FUD in the OP article towards AI, and we have similar article every week on HN now it's starting to become repetitive and tiresome. As of now this OP article is close to 1000 points and 1000 replies. Apparently this FUD seems to resonate with most people at HN, naturally so. Ironically the entire blog title is the "human in the loop", is probably the biggest counter argument for this FUD. The AI will never ever be concious and responsible, and to function and govern properly in the universe you need to be concious. AI I repeat will never ever becomes one. Not even in the popular fictional Star Wars movie franchises where you can have cute robots but they all devoid of the conciousness for the ever powerful force. Heck even the clones cannot control and balance the force, the Star Wars ultimate conscience. >Of course, this is good for brilliant engineers that never had the chance to get deep into the domain and now have better chances at getting a job, but it's also sad to think that other brilliant engineers that spent their lives collecting domain knowledge are now competing on the same lane. Actually overall it's definitely a very good thing for humanities. For example, currently it's very difficult to become a medical specialist and most medical students just stop at GP. But globally there are severe shortages of medical specialists for example typical cardiologists to patients ratio in developing countries is about 100,000:1, and for neurologists it's even worst. Let's say with AI enabled tools and LLM now these GP can upgrade themselves to become cardiologists easier than before. Let's say due to AI/LLM suddenly there's a big jump of the ratio to 10,000:1 or 10x incraese and improvement in the number of cardiologists without degrading much of the quality of services. Imagine if the typical waiting time for important and necessary procedures like angiography now is reduced to merely days or weeks rather than several months or up to a year. Thus naturally the salary of cardiologists will be not be as high as now, but they still will be compensated handsomely. But as humanity do we really care the cardiologists family just live in semi-D landed houses instead of bungalows, not much me think.
• marekful 4mo ago
  I think LLMs are the great filter of software engineers. They can do a lot reasonable well, but they lack the ability to be an overarching architect of complex projects (and it's my conviction that they can never achieve that). Only the best humans with insight, intuition and pattern recognition and application in non trivial scenarios can fill that gap.
• sankaritan 4mo ago
  This can surely feel painful, and I feel occasional sense of dread too, but then realize than not a lot have changed for folks working in medium+ size companies. Domain knowledge and tech expertise were never the sole differentiators for me when it comes to working with or even hiring capable software engineers. There's so much more to software engineer's job and ability to produce code / designs was barely 30% of our jobs. There is this interdisciplinary skillset we had to hone, how to work with others, how to understand what they actually want, how to ship things safely and learn from our mistakes and data to understand what to build next. You said you maintain candid relationship with PMs and stakeholders so you're likely underselling the whole scope of work you do day to day beyond immediate technical delivery. The time ahead may be rough given the transition period we're in but Software Engineering role (or whatever we will call it in 1-2 years) should not go away. LLMs surely will be able to do most of the individual work Software Engineer needs to do, but blending them all together is a lot harder task. And once we have AI doing that too, well, I believe at that point vast majority of knowledge work can be replaced by AI too and this is not a Software Engineering problem anymore.
• alkonaut 4mo ago
  I spent most of the last two years making a rather large hobby project. A 3D renderer for cad/visualization. It's pretty hard and slow work because getting anything wrong is usually hard to debug. Get a sign wrong and you have a black image suddenly, with painstaking debugging following. I worked on it for evenings and weekends, probably totaling a man-month of work or so. As a fun experiment, yesterday I asked a model to create this for me. It almost one shotted it. After a couple of iterations and 30 minutes I had made what I made over two years. The total AI cost (deepseek api, so entirely usage based) was $0.5. Now, I didn't enjoy making this AI guided version. And I didn't learn anything. But terrifyingly it has removed the drive to make another 2 year project "by hand". The end result (the runnihg demo) was never the goal. But still I can't now make myself hand-craft what an AI can spit out in an hour for $1! This is what bothers me the most. I'm old and senior enough that I don't fear for my job. But the AI thing just swallowed my hobby.
  • port11 4mo ago
    You shouldn’t be bothered that someone else does your hobby better. It’s a hobby, it’s meant to be for you, for no purpose other than fun, experimentation, entertainment, what have you. The outcome isn’t as important as the process. That’s my take on this, at least. I’ll never be very good at Scythe, or the most creative role-player, certainly never managed to do anything beautiful in pottery class (although the glazing is pretty). That’s fine. I achieve enough in other areas ._.
    • __alias 4mo ago
      > you shouldn't be bothered that someone else does your hobby better I don't know, I'd feel this way a little. if it's something that's not obvious how much effort goes into the underlying process, it can feel pretty deflating if the craft behind it has felt like it's eliminated. I can't really think of a good example, but if my hobby was glueing precision glueing little 3d models, then suddenly the hobby has exploded because 3d printers have made it easy, it suddenly feels like it's devalued my collection of manually crafted plastic models
      • 4mo ago
• lo_fye 4mo ago
  I have 25 years of experience with a single programming language that’s still in broad modern use. My employer recently moved me to a project that doesn’t use that language. The new language is completely foreign and hard for me to read. BUT we are supposed to maximize our AI usage. I made a few agents and skills to automate workflows, and now I can just say “$do-ticket ABC-1234”, and it gets done using TDD and hands me a report on what changes it made and why, along with an open Pull Request that automatically gets reviewed (again) by Codex. And the code works the first time 98% of the time. I don’t know the language, and it seems like people would prefer that I not know it, because then my AI use is necessarily maximal, but what am I even doing? Just telling AI to do a ticket? I see developer salaries trending toward minimum wage in the near future, and it’s scary, so I’m learning and leveraging LLM stuff, but even that will only help for so long. It’s a crazy time in our industry.
  • Schiendelman 4mo ago
    Product and program manager salaries aren't trending toward minimum wage. That's what you're becoming. Get good at it.
• robeym 4mo ago
  That woodworking idea is great. It's just a hobby for me as well but after long days of desk work where moving fast is rewarded, it's great to work slowly on a wood project with my hands. I tried listing a couple things on Facebook marketplace but I had never used it before so they just removed my posts.
• magenta_qin 4mo ago
  Even without LLMs, it was already getting tougher. There are just way more developers than before. To me, the game has shifted from just “knowing how to code” to being really good at something specific. General software work is becoming cheaper, while deep knowledge in a niche is still hard to replace. LLMs are speeding this up, but I don’t think they started it.
• bitwize 4mo ago
  You know how we say "adapt or get left behind"? This is what getting left behind looks like. Get your thumb out of your ass and learn the damn tools.
• sspoisk 4mo ago
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• acureau 4mo ago
  I cannot understand the overwhelmingly negative sentiment in this thread. I've used LLMs every day at work for several years now, I am a firm believer they're useful. Never once have I felt that an LLM could do my job without me steering it. I know the project goals, how to structure the code, the right and wrong paths to explore, how to evaluate and test its changes, how to make good engineering decisions, and much more. LLMs do not think. Someone has to be in the driver's seat. You're fooling yourself if you think that 99% of the population can use an LLM to write software. Or that they even have the desire to. I can cook, but I often go out to eat. I could repair a leaky sink, but a plumber will always do a better job. The specifics of our jobs are constantly changing, but our role in society will remain the same. One-off scripts can be written with non-technical prompts, but this work was already cheap. To do anything meaningful you need to be able to reason about a hard problem as a whole and at the implementation level simultaneously. Specifying context, tasks, structure and style, data representation and control flow, these things are software engineering. You are simply writing software in natural language. It has never been about the syntax.
• treebuscartruck 4mo ago
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• animanoir 4mo ago
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• nop_slide 4mo ago
  Anyone have a copy? Author seems to have deleted it
• casey2 4mo ago
  A famous AI company valued at over $1 Trillion cannot build a terminal app without screen flicker. They are simply unable, you can borrow money from the future but you can't borrow skill. If your software engineering career had any care for software quality it's impervious to erosion.
• lacoolj 4mo ago
  Contrary to other comments, and this post, I am actually seeing even that third pillar torn down. I have an architect who is very good at what he does, who wrote specs for the AI to follow, and other than a couple awkward placements, all the file structure is very sane and maintainable. We are in trouble. Not from a "no more devs" side, but from a "we only need one of you 7 to remain .." side
• gherlein 4mo ago
  My public blog response to this - and others saying the same thing - https://blog.herlein.com/post/domain-plus-software-superpower/ https://blog.herlein.com/post/domain-plus-software-superpowe... - Stop mourning the moat you thought you had. You have a much better one. You just need to pick up the new tool and start using it like it belongs in your hand.
  • jval43 4mo ago
    Thank you, that's a good response and I agree with many of your points.
• taffydavid 4mo ago
  > We were taught that generalists and specialists will always have their roles. But now the market is shaping everyone into becoming a generalist. That's not a bad thing per se, until you look under the economics of supply and demand: if everyone is a generalist, the price of a generalist falls if there's no demand to match. And we all know the demand is drying up. I see many posts like this every month, and have many conversations with friends and colleagues who think the same, and I see two trends - like this author, they all joke about becoming carpenters, or electricians. Overwhelmingly, electricians. These two professions seem to be held in special regard by software engineers craving the simple life. I hate to burst yet another bubble, but supply and demand economics apply here too folks. We can't all become electricians and carpenters. The work isn't there. In fact there's gonna be less work there than there is now of the economy tanks and nobody can afford to build or even renovate a house anymore
• jackson281 4mo ago
  The real shift might be that the value is moving from knowing the answers to knowing which questions to ask. The domain expert who steers the AI well will still have a job, just a different one.
• brianmartin039 4mo ago
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• deleted 4mo ago
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• oscarcooper257 4mo ago
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• crsa 4mo ago
  I think there are a few important factors to consider (I did not go through all the comments btw so apologies in case, there are too many). Historically lower development costs have also expanded the scope and ambition of what gets built. With LLMs acting as assistants and humans focusing more on architecture and decision-making, teams can explore multiple solutions in parallel and tackle projects that were previously too expensive or complex. That may increase, rather than decrease, the need for people who can manage complex domainy. There are also practical constraints that could slow or reshape this trend: the growing cost of AI infrastructure and data centers, environmental impact, regulation around copyright and training data, and a likely shift toward specialized domain-specific models instead of a few generic ones. On top of that, if LLMs become the new search engine, advertising and commercial incentives may erode their neutrality. Finally, LLMs depend on a constant supply of high-quality human-generated data, but they are also reducing the production of that data (e.g., the collapse in Stack Overflow activity). We are also in a very unusual market phase, with a handful of companies heavily investing in and cross-subsidizing each other. It is not obvious that the current pace of scaling can continue indefinitely, or that today's AI landscape represents a stable long-term equilibrium. There are other factors, like adoption of frontiers LLM in the market that is anyway slow, also the impact of AI in the economy that is anyway based on humans that must be controlled (because it has consequences when it comes pensions, consumptions of goods, etc.. ) Sorry: I used LLM to summarise my points to avoid long wall of text :D
• sermakarevich 4mo ago
  Not only SE career. Many careers which rely on static knowledge accumulated over years. We have a senior guy who is like a walking cybersecurity library - knowing all the protocols, standards, vendors, threats. He is quite desperate atm. There is nothing he can add to what LLM already knows or can research in 30 seconds. He was building his profile for 30+ years. I am on the side that AI will change everything. The reason why it has not yet is the lack of skills on the market - no AI transformation leaders. My strategy is to be closer to AI - number of nano startups with few people on board building smth AI related is exploding and they need expertise with AI engineering.
• brianmartin039 4mo ago
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