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Nothing because I’m a senior and LLM’s never provide code that pass my sniff test, and it remains a waste of time. I have a job at a place I love and get more

Nothing because I’m a senior and LLM’s never provide code that pass my sniff test, and it remains a waste of time. I have a job at a place I love and get more people in my direct network and extended contacting me about work than ever before in my 20 year career. And finally I keep myself sharp by always making sure I challenge myself creatively. I’m not afraid to delve into areas to understand them that might look “solved” to others. For example I have a CPU-only custom 2D pixel blitter engine I wrote to make 2D games in styles practically impossible with modern GPU-based texture rendering engines, and I recently did 3D in it from scratch as well. All the while re-evaluating all my assumptions and that of others. If there’s ever a day where there’s an AI that can do these things, then I’ll gladly retire. But I think that’s generations away at best. Honestly this fear that there will soon be no need for human programmers stems from people who either themselves don’t understand how LLM’s work, or from people who do that have a business interest convincing others that it’s more than it is as a technology. I say that with confidence.

planb 2y ago
This is satire, right? The completely off-topic mentioning of your graphics programming skills, the overconfidence, the phrase "delve into"... Let me guess: The prompt was "Write a typical HN response to this post"
- simianparrot 2y ago
  This made me chuckle. But at the same time a bit uneasy because this could mean my own way of expressing myself online might've been impacted by reading too much AI drivel whilst trying to find signal in the noisy internet landscape... The off-topic mentioning of graphics programming was because I tend to type as I think, then make corrections, and as I re-read it now the paragraph isn't great. The intent was to give an example of how I keep myself sharp, and challenging what many consider "settled" knowledge, where graphics programming happens to be my most recent example. For what it's worth, English isn't my native language, and you'll have to take my word for it that no chat bots were used in generating any of the responses I've made in this thread. The fact that people are already uncertain about who's a human and who's not is worrisome.
  - dreamfactored 2y ago
    I'm certain that humans are picking up AI dialect. Very hard to prove though and will become harder.
    - simianparrot 2y ago
      Either that or it's this simple: AI dialect is already the amalgamation of the most popular internet dialects for its training set. I used to read a lot of Reddit years ago now. It's more likely my dialect is influenced by that in subtle ways when typing online in English, and AI is parroting this for obvious reasons.
tigershark 2y ago
Yeah.. generations. I really hope that it doesn’t end like the New York Times article saying that human flight was at best hundred of years away a few weeks before the Wright brothers flight..
shafyy 2y ago
Completely agree. The other day I was trying to find something in the Shopify API docs (an API I'm not familar with), and I decided to try their chat bot assistant thingy. I thought, well, if an LLM is good at something, it's probably at finding information in a very narrow field like this. However, it kept telling me things that were plain wrong, I could compare it to the docs next to it easily. Would have been faster just reading the docs.
- Quarrel 2y ago
  > I thought, well, if an LLM is good at something, it's probably at finding information in a very narrow field like this. I feel like of all the things in this thread, this one is on them. It absolutely is something that LLMs are good at. They have the sample size, examples and docs, all the things. LLMs are particularly good at speaking "their" language, the most surprising thing is that they can do so much more beyond that next token reckoning. So, yeah, I'm a bit surprised that a shop like Shopify is so sloppy, but absolutely I think they should be able to provide you an LLM to answer your questions. Particularly given some of the Shopify alumni I've interviewed. That said, some marketing person might have just oversold the capabilities of an LLM that answers most of their core customer questions, rather than one that knows much at all about their API integrations.
  - shafyy 2y ago
    Another perspective is: Given that Shopify should have the capabilities to be good at this and their AI assistant is still sucking ass, it's not possible to make a better product with the current technology. Maybe it's right 99% of the time and works well for many of their developers. But this is exactly the point. I just can't trust a system that sometimes gives me the wrong answer.
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valval 2y ago
Another post where I get to tell a skeptic that they’re failing at using these products. There will be human programmers in the future as well, they just won’t be ones who can’t use LLMs.
jf22 2y ago
I'd challenge the assertion that LLMs never pass whatever a "sniff test" is to you. The code they produce is looking more and more like working production code.
og2023 2y ago
Seems like nobody noticed the "delve" part, which is a very dark irony here.
dyauspitr 2y ago
This is denial. LLMs already write code at a senior level. Couple that with solid tests and a human code reviewer and we’re already at 5x the story points per sprint at the startup I work at.
- whtsthmttrmn 2y ago
  I'm sure that startup is a great indication of things to come. Bound for long term growth.
  - dyauspitr 2y ago
    It’s solid, efficient, bug free code. What else matters?
  - phist_mcgee 2y ago
    Yap yap yap. Keep living in denial mate.
    - whtsthmttrmn 2y ago
      I'm not living in denial, I think LLMs are extremely useful and have huge potential. But people that are all "omg my startup did this and we reduced our devs by 150% so it must be the end-all tech!" are just as insufferable as the "nope the tech is bad and won't do anything at all" crowd. And before you mention, the hyperbole is for effect, not as an exact representation.
atomsatomsatoms 2y ago
"delve" hmmmmm
throwaway_36924 2y ago
I have been an AI denier for the past 2 years. I genuinely wanted to try it out but the experience I got from Copilot in early 2023 was just terrible. I have been using ChatGPT for some programming questions for all that time, but it was making mistakes and lack of editor integration did not seem like it would make me more productive. Thanks to this thread I have signed up again for Copilot and I am blown away. I think this easily makes me 2x productive when doing implementation work. It does not make silly mistakes anymore and it's just faster to have it write a block of code than doing it myself. And the experience is more of an augmentation than replacement. I don't have to let it run wild. I'm using it locally and refactor its output if needed to match my code quality standards. I am as much concerned (job market) as I am excited (what I will be able to build myself).
jejeyyy77 2y ago
head meet sand lol source: been coding for 15+ years and using LLMs for past year.
goddamnyouryan 2y ago
Tell me more about this 2D pixel blitter engine
rybosworld 2y ago
> Nothing because I’m a senior and LLM’s never provide code that pass my sniff test, and it remains a waste of time. I am constantly surprised how prevalent this attitude is. ChatGPT was only just released in 2022. Is there some expectation that these things won't improve? > LLM’s never provide code that pass my sniff test This is ego speaking.
- palata 2y ago
  > Is there some expectation that these things won't improve? Most of the noise I hear about LLMs is about expectations that things will improve. It's always like that: people extrapolate and get money from VCs for that. The thing is: nobody can know. So when someone extrapolates and says it's likely to happen as they predict, they shouldn't be surprised to get answers that say "I don't have the same beliefs".
- tomcar288 2y ago
  when people's entire livehoods are threatened, you're going to see some defensive reactions.
- eschaton 2y ago
  They shouldn’t be expected to improve in accuracy because of what they are and how they work. Contrary to what the average HackerNews seems to believe, LLMs don’t “think,” they just predict. And there’s nothing in them that will constrain their token prediction in a way that improves accuracy.
  - rybosworld 2y ago
    > Contrary to what the average HackerNews seems to believe, LLMs don’t “think,” they just predict. Anecdotally, I can't recall ever seeing someone on HackerNews accuse LLM's of thinking. This site is probably one of the most educated corners of the internet on the topic. > They shouldn’t be expected to improve in accuracy because of what they are and how they work. > And there’s nothing in them that will constrain their token prediction in a way that improves accuracy. These are both incorrect. LLM's are already quite better today than they were in 2022.
ksdnjweusdnkl21 2y ago
Hard to believe anyone is getting contacted more now than in 2020. But I agree with the general sentiment. I'll do nothing and if I get replaced then I get replaced and switch to woodworking or something. But if LLMs do not pan out then I'll be ahead of all the people who wasted their time with that.
- th0ma5 2y ago
  The sanest comment here.
ricardobeat 2y ago
That’s short term thinking in my opinion. LLMs will not replace developers by writing better code: it’s the systems we work on that will start disappearing. Every SaaS, marketplace is at risk of extinction, superseded by AI agents communicating ad-hoc. Management and business software replaced by custom, one-off programs built by AI. The era of large teams painstakingly building specialized software for niche use cases will end. Consequently we’ll have millions of unemployed developers, except for the ones maintaining the top level orchestration for all of this.
- dimgl 2y ago
  > most of the actual systems we work on will simply start disappearing. What systems do you think are going to start disappearing? I'm unclear how LLMs are contributing to systems becoming redundant.
  - rqtwteye 2y ago
    I think a lot of CRUD apps will disappear. A lot of the infrastructure may also be done by AI instead of some dude writing tons of YAML code.
    - betaby 2y ago
      The infrastructure is not a 'some dude writing tons of YAML code'.
    - munk-a 2y ago
      CRUD apps should already be disappearing. You should be using a framework that auto-generates the boilerplate stuff.
    - iLoveOncall 2y ago
      > I think a lot of CRUD apps will disappear How does that make any sense? How is AI, and especially GenAI, something that is by definition fallible, better in ANY way than current frameworks that allow you to write CRUD applications deterministically with basically one line of code per endpoint (if that)?
idopmstuff 2y ago
> But I think that’s generations away at best. I'm not sure whether you mean human generations or LLM generations, but I think it's the latter. In that case, I agree with you, but also that doesn't seem to put you particularly far off from OP, who didn't provide specific timelines but also seems to be indicating that the elimination of most engineers is still a little ways away. Since we're seeing a new generation of LLMs every 1-2 years, would you agree that in ~10 years at the outside, AI will be able to do the things that would cause you to gladly retire?
- simianparrot 2y ago
  I mean human generations because to do system architecture, design and development well you need something that can at least match an average human brain in reasoning, logic and learning plasticity. I don’t think that’s impossible but I think we’re quite a few human generations away from that. And scaling LLM’s is not the solution to that problem; an LLM is just a small but important part of it.
  - munk-a 2y ago
    I'd be cautious as describing anything in tech as human generations away because we're only about a single human generation into a lot of this industry existing.
    - simianparrot 2y ago
      I understand the hesitancy to do so, but the thing is, what's changed with computers since the inception of the technology is speed and size. The fundamentals are still the same. Programming today is a lot more convenient than programming via punch cards, but it's a matter of abstractions + scale + speed. Given this I'm pretty confident when I say that, but obviously not 100%.
rdrsss 2y ago
+1 to this sentiment for now, I give them a try every 6 months or so to see how they advance. And for pure code generation, for my workflow, I don't find them very useful yet. For parsing large sets of documentation though, not bad. They haven't creeped their way into my usual research loop just yet, but I could see that becoming a thing. I do hear some of my junior colleagues use them now and again, and gain some value there. And if llm's can help get people up to speed faster that'd be a good thing. Assuming we continue to make the effort to understand the output. But yeah, agree, I raise my eyebrow from time to time, but I don't see anything jaw dropping yet. Right now they just feel like surrogate googler's.
modeless 2y ago
> If there’s ever a day where there’s an AI that can do these things, then I’ll gladly retire. But I think that’s generations away at best. People really believe it will be generations before an AI will approach human level coding abilities? I don't know how a person could seriously consider that likely given the pace of progress in the field. This seems like burying your head in the sand. Even the whole package of translating high level ideas into robust deployed systems seems possible to solve within a decade. I believe there will still be jobs for technical people even when AI is good at coding. And I think they will be enjoyable and extremely productive. But they will be different.
- handzhiev 2y ago
  I've heard similar statements about human translation - and look where the translators are now
TZubiri 2y ago
"Nothing because I’m a senior and LLM’s never provide code that pass my sniff test, and it remains a waste of time" That's why the question is future proof. Models get better with time, not worse.
- palata 2y ago
  > Models get better with time, not worse A decade (almost?) ago, people were saying "look at how self-driving cars improved in the last 2 years: in 3-5 years we won't need to learn how to drive anymore". And yet...
- layer8 2y ago
  Models don’t get better just by time passing. The specific reasons for why they’ve been getting better don’t necessarily look like they’ll extend indefinitely into the future.
- latentsea 2y ago
  If the last-mile problems of things like autonomous vehicles have been anything to go by, it seems the last mile problems of entrusting your entire business operations to complete black box software, or software written by a novices talking to complete black box, will be infinitely worse. There's plenty of low-code, no-code solutions around, and yet still lots of software. The slice of the pie will change, but it's very hard to see it being eliminated entirely. Ultimately it's going to come down to "do I feel like I can trust this?" and with little to no way to be certain you can completely trust it, that's going to be a harder and harder sell as risk increases with the size, complexity, and value of the business processes being managed.
  - janalsncm 2y ago
    Even if seniors still do the last mile, that’s a significant reduction from the full commute they were paid for previously. Are you saying seniors should concede this?
    - latentsea 2y ago
luddite2309 2y ago
This is a fascinating comment, because it shows such a mis-reading of the history and point of technology (on a tech forum). Technological progress always leads to loss of skilled labor like your own, usually resulting in lower quality (but higher profits and often lower prices). Of COURSE an LLM won't be able to do work as well as you, just as industrial textile manufacturing could not, and still does not, produce the quality of work of 19th century cottage industry weavers; that was in fact one of their main complaints. As an aside, at the top of the front page right now is a sprawling essay titled "Why is it so hard to buy things that work well?"...
- packetlost 2y ago
  This is a take that shows a completely lack of understanding on what software engineering is actually about.
  - munk-a 2y ago
    The truth is somewhere in the middle. Do you remember the early 2000s boom of web developers that built custom websites for clients ranging from e-commerce sites to pizza restaurants? Those folks have found new work as the pressure from one-size fits all CMS providers (like Squarespace) and much stronger frameworks for simple front-ends (like node) have squeezed that market down to just businesses that actually need complex custom solutions and reduced the number of people required to maintain those. It's likely we'll see LLMs used to build a lot of the cheap stuff that previously existed as arcane excel macros (I've already seen less technical folks use it to analyze spreadsheets) but there will remain hard problems that developers are needed to solve.
- brink 2y ago
  Comparing an LLM to an industrial textile machine is laughable, because one is consistent and reliable while the other is not.
  - palata 2y ago
    It's laughable only if you think that the only reasonable metric is "consistent and reliable". The parent says "it typically doesn't matter that the product is worse if it's cheap enough". And that seems valid to me: the average quality of software today seems to be worse than 10 years ago. We do worse but cheaper.
markerdmann 2y ago
isn't "delve" a classic tell of gpt-generated output? i'm pretty sure simianparrot is just trolling us. :-)
jensensbutton 2y ago
The question isn't about what you'll do when you're replaced by an LLM, it's what you're doing to future proof your job. There is a difference. The risk to hedge against is the productivity boost brought by LLMs resulting in a drop in the needs for new software engineers. This will put pressure on jobs (simply don't need as many as we used to so we're cutting 15%) AND wages (more engineers looking for fewer jobs with a larger part of their utility being commoditized). Regardless of how sharp you keep yourself you're still at subject to the macro environment.
- simianparrot 2y ago
  I'm future proofing my job by ensuring I remain someone whose brain is tuned to solving complex problems, and to do that most effectively I find ways to keep being engaged in both the fundamentals of programming (as already mentioned) and the higher-level aspects: Teaching others (which in turn teaches me new things) and being in leadership roles where I can make real architectural choices in terms of what hardware to run our software on. I'm far more worried about mental degradation due to any number of circumstances -- unlucky genetics, infections, what have you. But "future proofing" myself against some of that has the same answer: Remain curious, remain mentally ambidextrous, and don't let other people (or objects) think for me. My brain is my greatest asset both for my job and my private life. So I do what I can to keep it in good shape, which incidentally also means replacing me with a parrot is unlikely to be a good decision.
  - paulcole 2y ago
    Nobody who's been replaced by a parrot thought they were going to get replaced by a parrot. Where's your espoused intellectual curiosity and mental ambidextrousness when it comes to LLMs? It seems like your mind is pretty firmly made up that they're of no worry to you.
    - simianparrot 2y ago
      In another comment I briefly mention one use case I have been implementing with LLM's: https://news.ycombinator.com/item?id=42434886 https://news.ycombinator.com/item?id=42434886 I'm being vague with the details because this is one of the features in our product that's a big advantage over competitors. To get to that point I experimented with and prototyped a lot using LLM's; I did a deep dive into how they work from the ground up. I understand the tech and its strengths. But likewise the weaknesses -- or perhaps more apt, the use cases which are more "magic show" than actually useful. I never dismissed LLM's as useless, but I am as confident as I can possibly be that LLM's on their own cannot and will not put programmers out of jobs. They're a great tool, but they're not what many people seem to be fooled into believing that they are; they are not "intelligent" nor "agents". Maybe it'll be a bit difficult for juniors to get entry level jobs for a short while due to a misunderstanding of the tech and all the hype, but that'll equalize pretty quickly once reality sets in.
arisAlexis 2y ago
So your argument is: There is some tech that is getting progressively better. I am high on the linear scale Therefore I don't worry about it cathing up to me ever And this is the top voted argument.
- whtsthmttrmn 2y ago
  Considering the entire purpose of the original post is asking people what they're doing, why do you have such a problem with the top voted argument? If the top voted argument was in favour of this tech taking jobs, would you feel better?
- NorthTheRock 2y ago
  > is getting progressively better Is it still getting better? My understanding is that we're already training them on all of the publicly available code in existence, and we're running in to scaling walls with bigger models.
  - arisAlexis 2y ago
    So you think that was it? Amazing comforting thoughts here
swishman 2y ago
The arrogance of comments like this is amazing. I think it's an interesting psychological phenomenon similar to virtue signalling. Here you are signalling to the programmer in-group how good of a programmer you are. The more dismissive you are the better you look. Anyone worried about it reveals themself as a bad coder. It's a luxury belief, and the better LLMs get the better you look by dismissing them.
- rybosworld 2y ago
  This is spot on. It's essentially like saying "What I do in particular, is much too difficult for an AI to ever replicate." It is always in part, humble bragging. I think some developers like to pretend that they are exclusively solving problems that have never been solved before. Which sure, the LLM architecture in particular might never be better than a person for the novel class of problem. But the reality is, an extremely high percentage of all problems (and by reduction, the lines of code that build that solution) are not novel. I would guesstimate that less than 1 out of 10,000 developers are solving truly novel problems with any regularity. And those folks tend to work at places like Google Brain. That's relevant because LLM's can likely scale forever in terms of solving the already solved.
  - whtsthmttrmn 2y ago
    > I would guesstimate that less than 1 out of 10,000 developers are solving truly novel problems with any regularity. And those folks tend to work at places like Google Brain. Looks like the virtue signalling is done on both sides of the AI fence.
    - rybosworld 2y ago
      Not sure how you equate that statement with virtue signaling. This is just a natural consequence of the ever growing repository of solved problems. For example, consider that sorting of lists is agreed upon as a solved problem. Sure you could re-discover quick sort on your own, but that's not novel.
  - raincole 2y ago
sigmarule 2y ago
My perspective is that if you are unable to find ways to improve your own workflows, productivity, output quality, or any other meaningful metric using the current SOTA LLM models, you should consider the possibility that it is a personal failure at least as much as you consider the possibility that it is a failure of the models. A more tangible pitfall I see people falling into is testing LLM code generation using something like ChatGPT and not considering more involved usage of LLMs via interfaces more suited for software development. The best results I've managed to realize on our codebase have not been with ChatGPT or IDEs like Cursor, but a series of processes that iterate over our full codebase multiple times to extract various levels of resuable insights, like general development patterns, error handling patterns, RBAC-related patterns, extracting example tasks for common types of tasks based on git commit histories (i.e. adding a new API endpoint related to XYZ), common bugs or failure patterns (again by looking through git commit histories), which create a sort of library of higher-level context and reusable concepts. Feeding this into o1, and having a pre-defined "call graph" of prompts to validate the output, fix identified issues, consider past errors in similar types of commits and past executions, etc has produced some very good results for us so far. I've also found much more success with ad-hoc questions after writing a small static analyzer to trace imports, variable references->declarations, etc, to isolate the portions of the codebase to use for context rather than RAG-based searching that a lot of LLM-centric development tools seem to use. It's also worth mentioning that performance quality seems to be very much influenced by language; I thankfully primarily work with Python codebases, though I've had success using it against (smaller) Rust codebases as well.
- mplanchard 2y ago
  This sounds nice, but it also sounds like a ton of work to set up we don't have time for. Local models that don't require us to send our codebase to Microsoft or OpenAI would be something I'm sure we'd be willing to try out. I'd love it if more companies were actually considering real engineering needs to provide products in this space. Until then, I have yet to see any compelling evidence that the current chatbot models can consistently produce anything useful for my particular work other than the occasional SQL query.
- j45 2y ago
Const-me 2y ago
> CPU-only custom 2D pixel blitter engine I wrote to make 2D games in styles practically impossible with modern GPU-based texture rendering engines I’m curious what’s so special about that blitting? BTW, pixel shaders in D3D11 can receive screen-space pixel coordinates in SV_Position semantic. The pixel shader can cast .xy slice of that value from float2 to int2 (truncating towards 0), offset the int2 vector to be relative to the top-left of the sprite, then pass the integers into Texture2D.Load method. Unlike the more commonly used Texture2D.Sample, Texture2D.Load method delivers a single texel as stored in the texture i.e. no filtering, sampling or interpolations. The texel is identified by integer coordinates, as opposed to UV floats for the Sample method.
rakkhi 2y ago
Agree with this. SWE don't need to do anything because LLMs will just make expert engineers more productive. More detail on my arguments here: https://rakkhi.substack.com/p/economics-of-large-language-models https://rakkhi.substack.com/p/economics-of-large-language-mo...
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richardw 2y ago
For those less confident: U.S. (and German) automakers were absolutely sure that the Japanese would never be able to touch them. Then Koreans. Now Chinese. Now there are tariffs and more coming to save jobs. Betting against AI (or increasing automation, really) is a bet against not against robots, but against human ingenuity. Humans are the ones making progress, and we can work with toothpicks as levers. LLM's are our current building blocks, and people are doing crazy things with them. I've got almost 30 years experience but I'm a bit rusty in e.g. web. But I've used LLM's to build maybe 10 apps that I had no business building, from one-off kids games to learn math, to building a soccer team generator that uses Google's OR tools to optimise across various axes, to spinning up four different test apps with Replit's agent to try multiple approaches to a task I'm working on. All the while skilling up in React and friends. I don't really have time for those side-quests but LLM's make them possible. Easy, even. The amount of time and energy I'd need pre-LLM's to do this makes this a million miles away from "a waste of time". And even if LLM's get no better, we're good at finding the parts that work well and using that as leverage. I'm using it to build and check datasets, because it's really good at extraction. I can throw a human in the loop, but in a startup setting this is 80/20 and that's enough. When I need enterprise level code, I brainstorm 10 approaches with it and then take the reins. How is this not valuable?
- Timber-6539 2y ago
  This is no different from creating a to-do app with an LLM and proclaiming all developers are up for replacement. Demos are not what makes LLMs good, let alone useful.
- apwell23 2y ago
  > 've got almost 30 years experience but I'm a bit rusty in e.g. web. But I've used LLM's to build maybe 10 apps that I had no business building, from one-off kids games to learn math, Yea i built bunch of apps when RoR blog demo came out like 2 decades ago. So what?
- nidnogg 2y ago
  As a senior-ish programmer who struggled a lot with algorithmic thinking in college, it's really awe-inspiring. Truly hit the nail on the head there. We HAD no business with these side-quests, but now? They're all ripe for the taking, really.
nidnogg 2y ago
LLMs are not necessarily a waste of time like you mention, as their application isn't limited to generating algorithms like you're used to. When you consider LLMs to be building blocks in bigger, more complex systems, their potential increases dramatically. That's where mid/senior engineers would chip in and add value to a company, in my point of view. There's also different infrastructure paradigms involved that have to be considered carefully, so DevOps is potentially necessary for years to come. I see a lot of ego in this comment, and I think this is actually a good example of how to NOT safeguard yourself against LLMs. This kind of skepticism is the most toxic to yourself. Dismiss them as novelty for the masses, as bullshit tech, keep doing your same old things and discard any applications. Textbook footgun.
- NorthTheRock 2y ago
  > When you consider LLMs to be building blocks in bigger, more complex systems, their potential increases dramatically. Do you have any examples of where/how that would work? It has seemed for me like lot of the hype is "they'll be good" with no further explanation.
  - curl-up 2y ago
    I pull messy data from a remote source (think OCR-ed invoices for example), and need to clean it up. Every day I get around 1k new rows. The way in which it's messed up changes frequently, and while I don't care about it being 100% correct, any piece of code (relying on rules, regex, heuristics and other such stuff) would break in a couple of weeks. This means I need at least a part time developer on my team, costing me a couple of thousands per month. Or I can pass each row through an LLM and get structured clean output out for a couple of dollars per month. Sure, it doesn't work 100%, but I don't need that, and neither could the human-written code do it. Effectively, LLM resulted in one less develper hired on our team.
    - defrost 2y ago
      Human or LLM the trick with messy inputs from scanned sources is having robust sanity combs that look for obvious fubar's and a means by which end data users can review the asserted values and the original raw image sources (and flag for review | alteration). At least in my past experience with volumes of transcribed data for applications that are picky about accuracy.
curl-up 2y ago
Could you give an example of an AI capability that would change your mind on this, even slightly? "Sniff test" is rather subjective, and job replacement rarely happens with machines doing something better on the exact same axis of performance as humans. E.g., cars wouldn't have passed the coachman's "sniff test". Or to use a current topic - fast food self-order touchscreens don't pass the customer service people sniff test.
crystal_revenge 2y ago
> never provide code that pass my sniff test Unfortunately it won't be your sniff test that matters. It's going to be an early founder that realizes they don't need to make that extra seed round hire, or the resource limited director that decides they can forgo that one head count and still deliver the product on time, or the in house team that realizes they no longer need a dedicated front end dev because, for their purposes, AI is good enough. Personally, the team I lead is able to ship much faster with AI assistants than without, which means in practice we can out compete much larger teams in the same space. Sure their are things that AI will always struggle with, but those things aren't merely "senior" in nature, they're much closer to the niche expert type of problems. Engineers working on generally cutting edge work will likely be in demand and hard to replace, but many others will very likely be impacted by AI from multiple directions.
- irunmyownemail 2y ago
  "Personally, the team I lead is able to ship much faster with AI assistants than without, which means in practice we can out compete much larger teams in the same space." So, you're giving away your company's IP to AI firms, does your CEO understand this?
  - dreamfactored 2y ago
    IP is a legal construct not a technical one. If it's protected by law it's protected by law.
  - crystal_revenge 2y ago
    Appreciate the snark, but yes my CEO and I did have a good chat about that. My team's work is 100% open source, so if anyone wants to borrow that code I'm more than happy to share! (obviously not from a pseudonymous account, but I don't mind the API sniffing). But there's plenty of fantastic open models now and you can increasingly run this stuff locally so you don't have to send that IP to AI firms if you don't want to.
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planb 2y ago

This is satire, right? The completely off-topic mentioning of your graphics programming skills, the overconfidence, the phrase "delve into"... Let me guess: The prompt was "Write a typical HN response to this post"

simianparrot 2y ago
This made me chuckle. But at the same time a bit uneasy because this could mean my own way of expressing myself online might've been impacted by reading too much AI drivel whilst trying to find signal in the noisy internet landscape... The off-topic mentioning of graphics programming was because I tend to type as I think, then make corrections, and as I re-read it now the paragraph isn't great. The intent was to give an example of how I keep myself sharp, and challenging what many consider "settled" knowledge, where graphics programming happens to be my most recent example. For what it's worth, English isn't my native language, and you'll have to take my word for it that no chat bots were used in generating any of the responses I've made in this thread. The fact that people are already uncertain about who's a human and who's not is worrisome.
- dreamfactored 2y ago
  I'm certain that humans are picking up AI dialect. Very hard to prove though and will become harder.
  - simianparrot 2y ago
    Either that or it's this simple: AI dialect is already the amalgamation of the most popular internet dialects for its training set. I used to read a lot of Reddit years ago now. It's more likely my dialect is influenced by that in subtle ways when typing online in English, and AI is parroting this for obvious reasons.

tigershark 2y ago

Yeah.. generations. I really hope that it doesn’t end like the New York Times article saying that human flight was at best hundred of years away a few weeks before the Wright brothers flight..

shafyy 2y ago

Completely agree. The other day I was trying to find something in the Shopify API docs (an API I'm not familar with), and I decided to try their chat bot assistant thingy. I thought, well, if an LLM is good at something, it's probably at finding information in a very narrow field like this. However, it kept telling me things that were plain wrong, I could compare it to the docs next to it easily. Would have been faster just reading the docs.

Quarrel 2y ago
> I thought, well, if an LLM is good at something, it's probably at finding information in a very narrow field like this. I feel like of all the things in this thread, this one is on them. It absolutely is something that LLMs are good at. They have the sample size, examples and docs, all the things. LLMs are particularly good at speaking "their" language, the most surprising thing is that they can do so much more beyond that next token reckoning. So, yeah, I'm a bit surprised that a shop like Shopify is so sloppy, but absolutely I think they should be able to provide you an LLM to answer your questions. Particularly given some of the Shopify alumni I've interviewed. That said, some marketing person might have just oversold the capabilities of an LLM that answers most of their core customer questions, rather than one that knows much at all about their API integrations.
- shafyy 2y ago
  Another perspective is: Given that Shopify should have the capabilities to be good at this and their AI assistant is still sucking ass, it's not possible to make a better product with the current technology. Maybe it's right 99% of the time and works well for many of their developers. But this is exactly the point. I just can't trust a system that sometimes gives me the wrong answer.

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valval 2y ago

Another post where I get to tell a skeptic that they’re failing at using these products. There will be human programmers in the future as well, they just won’t be ones who can’t use LLMs.

jf22 2y ago

I'd challenge the assertion that LLMs never pass whatever a "sniff test" is to you. The code they produce is looking more and more like working production code.

og2023 2y ago

Seems like nobody noticed the "delve" part, which is a very dark irony here.

dyauspitr 2y ago

This is denial. LLMs already write code at a senior level. Couple that with solid tests and a human code reviewer and we’re already at 5x the story points per sprint at the startup I work at.

whtsthmttrmn 2y ago
I'm sure that startup is a great indication of things to come. Bound for long term growth.
- dyauspitr 2y ago
  It’s solid, efficient, bug free code. What else matters?
- phist_mcgee 2y ago
  Yap yap yap. Keep living in denial mate.
  - whtsthmttrmn 2y ago
    I'm not living in denial, I think LLMs are extremely useful and have huge potential. But people that are all "omg my startup did this and we reduced our devs by 150% so it must be the end-all tech!" are just as insufferable as the "nope the tech is bad and won't do anything at all" crowd. And before you mention, the hyperbole is for effect, not as an exact representation.

atomsatomsatoms 2y ago

"delve" hmmmmm

throwaway_36924 2y ago

I have been an AI denier for the past 2 years. I genuinely wanted to try it out but the experience I got from Copilot in early 2023 was just terrible. I have been using ChatGPT for some programming questions for all that time, but it was making mistakes and lack of editor integration did not seem like it would make me more productive. Thanks to this thread I have signed up again for Copilot and I am blown away. I think this easily makes me 2x productive when doing implementation work. It does not make silly mistakes anymore and it's just faster to have it write a block of code than doing it myself. And the experience is more of an augmentation than replacement. I don't have to let it run wild. I'm using it locally and refactor its output if needed to match my code quality standards. I am as much concerned (job market) as I am excited (what I will be able to build myself).

jejeyyy77 2y ago

head meet sand lol source: been coding for 15+ years and using LLMs for past year.

goddamnyouryan 2y ago

Tell me more about this 2D pixel blitter engine

rybosworld 2y ago

> Nothing because I’m a senior and LLM’s never provide code that pass my sniff test, and it remains a waste of time. I am constantly surprised how prevalent this attitude is. ChatGPT was only just released in 2022. Is there some expectation that these things won't improve? > LLM’s never provide code that pass my sniff test This is ego speaking.

palata 2y ago
> Is there some expectation that these things won't improve? Most of the noise I hear about LLMs is about expectations that things will improve. It's always like that: people extrapolate and get money from VCs for that. The thing is: nobody can know. So when someone extrapolates and says it's likely to happen as they predict, they shouldn't be surprised to get answers that say "I don't have the same beliefs".
tomcar288 2y ago
when people's entire livehoods are threatened, you're going to see some defensive reactions.
eschaton 2y ago
They shouldn’t be expected to improve in accuracy because of what they are and how they work. Contrary to what the average HackerNews seems to believe, LLMs don’t “think,” they just predict. And there’s nothing in them that will constrain their token prediction in a way that improves accuracy.
- rybosworld 2y ago
  > Contrary to what the average HackerNews seems to believe, LLMs don’t “think,” they just predict. Anecdotally, I can't recall ever seeing someone on HackerNews accuse LLM's of thinking. This site is probably one of the most educated corners of the internet on the topic. > They shouldn’t be expected to improve in accuracy because of what they are and how they work. > And there’s nothing in them that will constrain their token prediction in a way that improves accuracy. These are both incorrect. LLM's are already quite better today than they were in 2022.

ksdnjweusdnkl21 2y ago

Hard to believe anyone is getting contacted more now than in 2020. But I agree with the general sentiment. I'll do nothing and if I get replaced then I get replaced and switch to woodworking or something. But if LLMs do not pan out then I'll be ahead of all the people who wasted their time with that.

th0ma5 2y ago
The sanest comment here.

ricardobeat 2y ago

That’s short term thinking in my opinion. LLMs will not replace developers by writing better code: it’s the systems we work on that will start disappearing. Every SaaS, marketplace is at risk of extinction, superseded by AI agents communicating ad-hoc. Management and business software replaced by custom, one-off programs built by AI. The era of large teams painstakingly building specialized software for niche use cases will end. Consequently we’ll have millions of unemployed developers, except for the ones maintaining the top level orchestration for all of this.

dimgl 2y ago
> most of the actual systems we work on will simply start disappearing. What systems do you think are going to start disappearing? I'm unclear how LLMs are contributing to systems becoming redundant.
- rqtwteye 2y ago
  I think a lot of CRUD apps will disappear. A lot of the infrastructure may also be done by AI instead of some dude writing tons of YAML code.
  - betaby 2y ago
    The infrastructure is not a 'some dude writing tons of YAML code'.
  - munk-a 2y ago
    CRUD apps should already be disappearing. You should be using a framework that auto-generates the boilerplate stuff.
  - iLoveOncall 2y ago
    > I think a lot of CRUD apps will disappear How does that make any sense? How is AI, and especially GenAI, something that is by definition fallible, better in ANY way than current frameworks that allow you to write CRUD applications deterministically with basically one line of code per endpoint (if that)?

idopmstuff 2y ago

> But I think that’s generations away at best. I'm not sure whether you mean human generations or LLM generations, but I think it's the latter. In that case, I agree with you, but also that doesn't seem to put you particularly far off from OP, who didn't provide specific timelines but also seems to be indicating that the elimination of most engineers is still a little ways away. Since we're seeing a new generation of LLMs every 1-2 years, would you agree that in ~10 years at the outside, AI will be able to do the things that would cause you to gladly retire?

simianparrot 2y ago
I mean human generations because to do system architecture, design and development well you need something that can at least match an average human brain in reasoning, logic and learning plasticity. I don’t think that’s impossible but I think we’re quite a few human generations away from that. And scaling LLM’s is not the solution to that problem; an LLM is just a small but important part of it.
- munk-a 2y ago
  I'd be cautious as describing anything in tech as human generations away because we're only about a single human generation into a lot of this industry existing.
  - simianparrot 2y ago
    I understand the hesitancy to do so, but the thing is, what's changed with computers since the inception of the technology is speed and size. The fundamentals are still the same. Programming today is a lot more convenient than programming via punch cards, but it's a matter of abstractions + scale + speed. Given this I'm pretty confident when I say that, but obviously not 100%.

rdrsss 2y ago

+1 to this sentiment for now, I give them a try every 6 months or so to see how they advance. And for pure code generation, for my workflow, I don't find them very useful yet. For parsing large sets of documentation though, not bad. They haven't creeped their way into my usual research loop just yet, but I could see that becoming a thing. I do hear some of my junior colleagues use them now and again, and gain some value there. And if llm's can help get people up to speed faster that'd be a good thing. Assuming we continue to make the effort to understand the output. But yeah, agree, I raise my eyebrow from time to time, but I don't see anything jaw dropping yet. Right now they just feel like surrogate googler's.

modeless 2y ago

> If there’s ever a day where there’s an AI that can do these things, then I’ll gladly retire. But I think that’s generations away at best. People really believe it will be generations before an AI will approach human level coding abilities? I don't know how a person could seriously consider that likely given the pace of progress in the field. This seems like burying your head in the sand. Even the whole package of translating high level ideas into robust deployed systems seems possible to solve within a decade. I believe there will still be jobs for technical people even when AI is good at coding. And I think they will be enjoyable and extremely productive. But they will be different.

handzhiev 2y ago
I've heard similar statements about human translation - and look where the translators are now

TZubiri 2y ago

"Nothing because I’m a senior and LLM’s never provide code that pass my sniff test, and it remains a waste of time" That's why the question is future proof. Models get better with time, not worse.

palata 2y ago
> Models get better with time, not worse A decade (almost?) ago, people were saying "look at how self-driving cars improved in the last 2 years: in 3-5 years we won't need to learn how to drive anymore". And yet...
layer8 2y ago
Models don’t get better just by time passing. The specific reasons for why they’ve been getting better don’t necessarily look like they’ll extend indefinitely into the future.
latentsea 2y ago
If the last-mile problems of things like autonomous vehicles have been anything to go by, it seems the last mile problems of entrusting your entire business operations to complete black box software, or software written by a novices talking to complete black box, will be infinitely worse. There's plenty of low-code, no-code solutions around, and yet still lots of software. The slice of the pie will change, but it's very hard to see it being eliminated entirely. Ultimately it's going to come down to "do I feel like I can trust this?" and with little to no way to be certain you can completely trust it, that's going to be a harder and harder sell as risk increases with the size, complexity, and value of the business processes being managed.
- janalsncm 2y ago
  Even if seniors still do the last mile, that’s a significant reduction from the full commute they were paid for previously. Are you saying seniors should concede this?
  - latentsea 2y ago

luddite2309 2y ago

This is a fascinating comment, because it shows such a mis-reading of the history and point of technology (on a tech forum). Technological progress always leads to loss of skilled labor like your own, usually resulting in lower quality (but higher profits and often lower prices). Of COURSE an LLM won't be able to do work as well as you, just as industrial textile manufacturing could not, and still does not, produce the quality of work of 19th century cottage industry weavers; that was in fact one of their main complaints. As an aside, at the top of the front page right now is a sprawling essay titled "Why is it so hard to buy things that work well?"...

packetlost 2y ago
This is a take that shows a completely lack of understanding on what software engineering is actually about.
- munk-a 2y ago
  The truth is somewhere in the middle. Do you remember the early 2000s boom of web developers that built custom websites for clients ranging from e-commerce sites to pizza restaurants? Those folks have found new work as the pressure from one-size fits all CMS providers (like Squarespace) and much stronger frameworks for simple front-ends (like node) have squeezed that market down to just businesses that actually need complex custom solutions and reduced the number of people required to maintain those. It's likely we'll see LLMs used to build a lot of the cheap stuff that previously existed as arcane excel macros (I've already seen less technical folks use it to analyze spreadsheets) but there will remain hard problems that developers are needed to solve.
brink 2y ago
Comparing an LLM to an industrial textile machine is laughable, because one is consistent and reliable while the other is not.
- palata 2y ago
  It's laughable only if you think that the only reasonable metric is "consistent and reliable". The parent says "it typically doesn't matter that the product is worse if it's cheap enough". And that seems valid to me: the average quality of software today seems to be worse than 10 years ago. We do worse but cheaper.

markerdmann 2y ago

isn't "delve" a classic tell of gpt-generated output? i'm pretty sure simianparrot is just trolling us. :-)

jensensbutton 2y ago

The question isn't about what you'll do when you're replaced by an LLM, it's what you're doing to future proof your job. There is a difference. The risk to hedge against is the productivity boost brought by LLMs resulting in a drop in the needs for new software engineers. This will put pressure on jobs (simply don't need as many as we used to so we're cutting 15%) AND wages (more engineers looking for fewer jobs with a larger part of their utility being commoditized). Regardless of how sharp you keep yourself you're still at subject to the macro environment.

simianparrot 2y ago
I'm future proofing my job by ensuring I remain someone whose brain is tuned to solving complex problems, and to do that most effectively I find ways to keep being engaged in both the fundamentals of programming (as already mentioned) and the higher-level aspects: Teaching others (which in turn teaches me new things) and being in leadership roles where I can make real architectural choices in terms of what hardware to run our software on. I'm far more worried about mental degradation due to any number of circumstances -- unlucky genetics, infections, what have you. But "future proofing" myself against some of that has the same answer: Remain curious, remain mentally ambidextrous, and don't let other people (or objects) think for me. My brain is my greatest asset both for my job and my private life. So I do what I can to keep it in good shape, which incidentally also means replacing me with a parrot is unlikely to be a good decision.
- paulcole 2y ago
  Nobody who's been replaced by a parrot thought they were going to get replaced by a parrot. Where's your espoused intellectual curiosity and mental ambidextrousness when it comes to LLMs? It seems like your mind is pretty firmly made up that they're of no worry to you.
  - simianparrot 2y ago
    In another comment I briefly mention one use case I have been implementing with LLM's: https://news.ycombinator.com/item?id=42434886 https://news.ycombinator.com/item?id=42434886 I'm being vague with the details because this is one of the features in our product that's a big advantage over competitors. To get to that point I experimented with and prototyped a lot using LLM's; I did a deep dive into how they work from the ground up. I understand the tech and its strengths. But likewise the weaknesses -- or perhaps more apt, the use cases which are more "magic show" than actually useful. I never dismissed LLM's as useless, but I am as confident as I can possibly be that LLM's on their own cannot and will not put programmers out of jobs. They're a great tool, but they're not what many people seem to be fooled into believing that they are; they are not "intelligent" nor "agents". Maybe it'll be a bit difficult for juniors to get entry level jobs for a short while due to a misunderstanding of the tech and all the hype, but that'll equalize pretty quickly once reality sets in.

arisAlexis 2y ago

So your argument is: There is some tech that is getting progressively better. I am high on the linear scale Therefore I don't worry about it cathing up to me ever And this is the top voted argument.

whtsthmttrmn 2y ago
Considering the entire purpose of the original post is asking people what they're doing, why do you have such a problem with the top voted argument? If the top voted argument was in favour of this tech taking jobs, would you feel better?
NorthTheRock 2y ago
> is getting progressively better Is it still getting better? My understanding is that we're already training them on all of the publicly available code in existence, and we're running in to scaling walls with bigger models.
- arisAlexis 2y ago
  So you think that was it? Amazing comforting thoughts here

swishman 2y ago

The arrogance of comments like this is amazing. I think it's an interesting psychological phenomenon similar to virtue signalling. Here you are signalling to the programmer in-group how good of a programmer you are. The more dismissive you are the better you look. Anyone worried about it reveals themself as a bad coder. It's a luxury belief, and the better LLMs get the better you look by dismissing them.

rybosworld 2y ago
This is spot on. It's essentially like saying "What I do in particular, is much too difficult for an AI to ever replicate." It is always in part, humble bragging. I think some developers like to pretend that they are exclusively solving problems that have never been solved before. Which sure, the LLM architecture in particular might never be better than a person for the novel class of problem. But the reality is, an extremely high percentage of all problems (and by reduction, the lines of code that build that solution) are not novel. I would guesstimate that less than 1 out of 10,000 developers are solving truly novel problems with any regularity. And those folks tend to work at places like Google Brain. That's relevant because LLM's can likely scale forever in terms of solving the already solved.
- whtsthmttrmn 2y ago
  > I would guesstimate that less than 1 out of 10,000 developers are solving truly novel problems with any regularity. And those folks tend to work at places like Google Brain. Looks like the virtue signalling is done on both sides of the AI fence.
  - rybosworld 2y ago
    Not sure how you equate that statement with virtue signaling. This is just a natural consequence of the ever growing repository of solved problems. For example, consider that sorting of lists is agreed upon as a solved problem. Sure you could re-discover quick sort on your own, but that's not novel.
- raincole 2y ago

sigmarule 2y ago

My perspective is that if you are unable to find ways to improve your own workflows, productivity, output quality, or any other meaningful metric using the current SOTA LLM models, you should consider the possibility that it is a personal failure at least as much as you consider the possibility that it is a failure of the models. A more tangible pitfall I see people falling into is testing LLM code generation using something like ChatGPT and not considering more involved usage of LLMs via interfaces more suited for software development. The best results I've managed to realize on our codebase have not been with ChatGPT or IDEs like Cursor, but a series of processes that iterate over our full codebase multiple times to extract various levels of resuable insights, like general development patterns, error handling patterns, RBAC-related patterns, extracting example tasks for common types of tasks based on git commit histories (i.e. adding a new API endpoint related to XYZ), common bugs or failure patterns (again by looking through git commit histories), which create a sort of library of higher-level context and reusable concepts. Feeding this into o1, and having a pre-defined "call graph" of prompts to validate the output, fix identified issues, consider past errors in similar types of commits and past executions, etc has produced some very good results for us so far. I've also found much more success with ad-hoc questions after writing a small static analyzer to trace imports, variable references->declarations, etc, to isolate the portions of the codebase to use for context rather than RAG-based searching that a lot of LLM-centric development tools seem to use. It's also worth mentioning that performance quality seems to be very much influenced by language; I thankfully primarily work with Python codebases, though I've had success using it against (smaller) Rust codebases as well.

mplanchard 2y ago
This sounds nice, but it also sounds like a ton of work to set up we don't have time for. Local models that don't require us to send our codebase to Microsoft or OpenAI would be something I'm sure we'd be willing to try out. I'd love it if more companies were actually considering real engineering needs to provide products in this space. Until then, I have yet to see any compelling evidence that the current chatbot models can consistently produce anything useful for my particular work other than the occasional SQL query.
j45 2y ago

Const-me 2y ago

> CPU-only custom 2D pixel blitter engine I wrote to make 2D games in styles practically impossible with modern GPU-based texture rendering engines I’m curious what’s so special about that blitting? BTW, pixel shaders in D3D11 can receive screen-space pixel coordinates in SV_Position semantic. The pixel shader can cast .xy slice of that value from float2 to int2 (truncating towards 0), offset the int2 vector to be relative to the top-left of the sprite, then pass the integers into Texture2D.Load method. Unlike the more commonly used Texture2D.Sample, Texture2D.Load method delivers a single texel as stored in the texture i.e. no filtering, sampling or interpolations. The texel is identified by integer coordinates, as opposed to UV floats for the Sample method.

rakkhi 2y ago

Agree with this. SWE don't need to do anything because LLMs will just make expert engineers more productive. More detail on my arguments here: https://rakkhi.substack.com/p/economics-of-large-language-models https://rakkhi.substack.com/p/economics-of-large-language-mo...

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richardw 2y ago

For those less confident: U.S. (and German) automakers were absolutely sure that the Japanese would never be able to touch them. Then Koreans. Now Chinese. Now there are tariffs and more coming to save jobs. Betting against AI (or increasing automation, really) is a bet against not against robots, but against human ingenuity. Humans are the ones making progress, and we can work with toothpicks as levers. LLM's are our current building blocks, and people are doing crazy things with them. I've got almost 30 years experience but I'm a bit rusty in e.g. web. But I've used LLM's to build maybe 10 apps that I had no business building, from one-off kids games to learn math, to building a soccer team generator that uses Google's OR tools to optimise across various axes, to spinning up four different test apps with Replit's agent to try multiple approaches to a task I'm working on. All the while skilling up in React and friends. I don't really have time for those side-quests but LLM's make them possible. Easy, even. The amount of time and energy I'd need pre-LLM's to do this makes this a million miles away from "a waste of time". And even if LLM's get no better, we're good at finding the parts that work well and using that as leverage. I'm using it to build and check datasets, because it's really good at extraction. I can throw a human in the loop, but in a startup setting this is 80/20 and that's enough. When I need enterprise level code, I brainstorm 10 approaches with it and then take the reins. How is this not valuable?

Timber-6539 2y ago
This is no different from creating a to-do app with an LLM and proclaiming all developers are up for replacement. Demos are not what makes LLMs good, let alone useful.
apwell23 2y ago
> 've got almost 30 years experience but I'm a bit rusty in e.g. web. But I've used LLM's to build maybe 10 apps that I had no business building, from one-off kids games to learn math, Yea i built bunch of apps when RoR blog demo came out like 2 decades ago. So what?
nidnogg 2y ago
As a senior-ish programmer who struggled a lot with algorithmic thinking in college, it's really awe-inspiring. Truly hit the nail on the head there. We HAD no business with these side-quests, but now? They're all ripe for the taking, really.

nidnogg 2y ago

LLMs are not necessarily a waste of time like you mention, as their application isn't limited to generating algorithms like you're used to. When you consider LLMs to be building blocks in bigger, more complex systems, their potential increases dramatically. That's where mid/senior engineers would chip in and add value to a company, in my point of view. There's also different infrastructure paradigms involved that have to be considered carefully, so DevOps is potentially necessary for years to come. I see a lot of ego in this comment, and I think this is actually a good example of how to NOT safeguard yourself against LLMs. This kind of skepticism is the most toxic to yourself. Dismiss them as novelty for the masses, as bullshit tech, keep doing your same old things and discard any applications. Textbook footgun.

NorthTheRock 2y ago
> When you consider LLMs to be building blocks in bigger, more complex systems, their potential increases dramatically. Do you have any examples of where/how that would work? It has seemed for me like lot of the hype is "they'll be good" with no further explanation.
- curl-up 2y ago
  I pull messy data from a remote source (think OCR-ed invoices for example), and need to clean it up. Every day I get around 1k new rows. The way in which it's messed up changes frequently, and while I don't care about it being 100% correct, any piece of code (relying on rules, regex, heuristics and other such stuff) would break in a couple of weeks. This means I need at least a part time developer on my team, costing me a couple of thousands per month. Or I can pass each row through an LLM and get structured clean output out for a couple of dollars per month. Sure, it doesn't work 100%, but I don't need that, and neither could the human-written code do it. Effectively, LLM resulted in one less develper hired on our team.
  - defrost 2y ago
    Human or LLM the trick with messy inputs from scanned sources is having robust sanity combs that look for obvious fubar's and a means by which end data users can review the asserted values and the original raw image sources (and flag for review | alteration). At least in my past experience with volumes of transcribed data for applications that are picky about accuracy.

curl-up 2y ago

Could you give an example of an AI capability that would change your mind on this, even slightly? "Sniff test" is rather subjective, and job replacement rarely happens with machines doing something better on the exact same axis of performance as humans. E.g., cars wouldn't have passed the coachman's "sniff test". Or to use a current topic - fast food self-order touchscreens don't pass the customer service people sniff test.

crystal_revenge 2y ago

> never provide code that pass my sniff test Unfortunately it won't be your sniff test that matters. It's going to be an early founder that realizes they don't need to make that extra seed round hire, or the resource limited director that decides they can forgo that one head count and still deliver the product on time, or the in house team that realizes they no longer need a dedicated front end dev because, for their purposes, AI is good enough. Personally, the team I lead is able to ship much faster with AI assistants than without, which means in practice we can out compete much larger teams in the same space. Sure their are things that AI will always struggle with, but those things aren't merely "senior" in nature, they're much closer to the niche expert type of problems. Engineers working on generally cutting edge work will likely be in demand and hard to replace, but many others will very likely be impacted by AI from multiple directions.

irunmyownemail 2y ago
"Personally, the team I lead is able to ship much faster with AI assistants than without, which means in practice we can out compete much larger teams in the same space." So, you're giving away your company's IP to AI firms, does your CEO understand this?
- dreamfactored 2y ago
  IP is a legal construct not a technical one. If it's protected by law it's protected by law.
- crystal_revenge 2y ago
  Appreciate the snark, but yes my CEO and I did have a good chat about that. My team's work is 100% open source, so if anyone wants to borrow that code I'm more than happy to share! (obviously not from a pseudonymous account, but I don't mind the API sniffing). But there's plenty of fantastic open models now and you can increasingly run this stuff locally so you don't have to send that IP to AI firms if you don't want to.

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