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What I don't think the HN bubble is fully familiar with is the fact that probably 70% of programming happening today is boring low paid drudgery (or maybe 50-90

What I don't think the HN bubble is fully familiar with is the fact that probably 70% of programming happening today is boring low paid drudgery (or maybe 50-90%). It's creating dashboards in BI tools, it's tweaking Wordpress themes, it's writing custom business processes in ABAP for SAP deployments, or it's 3-10 engineers doing the work of 1 so that a outsourcing company can bulk up its bills. This is the sort of work that AI is coming for. It's low impact, low effort, low paid, and importantly it doesn't get automated (often). This means there is a lot of low hanging fruit for automation, whether that's by regular tooling or LLMs. On the other hand, if you're a highly paid software engineer, it's likely you're already working with highly automated and abstracted systems, so there's much less opportunity for LLMs. If your deployment process is a Word doc specifying the 120 steps you have to run in bash to deploy that takes 1 eng day, that's going to be automated, but if you're git-pushing and having Kubernetes roll it out in your CI/CD flow, automation has already raised the level of abstraction that you need to work at and there are fewer opportunities. Yes there's Copilot/etc which will reduce boilerplate, but the only way a company achieves "70% less coders" is by wholesale automation of large parts of their process that must be horribly basic already.

faeriechangling 2y ago
I'm well aware of this and in those sorts of jobs, most of the work isn't programming, it's sitting in meetings and communicating. While AI might help with this simply by shrinking the amount of people needed to do a job, I'm very dubious about a 70% efficiency gain when you look at the entire scope of what these workers do. The entire concept that if you make coding 70% more efficient that you'll make coders 70% more efficient is simply wrong.
- gexla 2y ago
  Maybe you need to be more specific about which workers you're talking about. Given a full time worker vs a contractor, I'm guessing the contractor has far less knowledge of the system as a whole, and ripe for being replaced. Then with freed up funds, maybe they hire more internal developers. It could be more of a reshuffling than anything else.
wakawaka28 2y ago
>On the other hand, if you're a highly paid software engineer, it's likely you're already working with highly automated and abstracted systems, so there's much less opportunity for LLMs. I think you're wrong about this. There are people today getting paid lots of money for basic jobs, and people with real difficult jobs that don't get paid much. Pay rate is as much a function of location and your particular company or industry as it is the actual nature of what you are doing. >Yes there's Copilot/etc which will reduce boilerplate, but the only way a company achieves "70% less coders" is by wholesale automation of large parts of their process that must be horribly basic already. The basics often only seem basic because we've done them a great deal. When the machines are charged with doing a lot of stuff, will the basics still appear basic? Will you be able to spot the critical yet tricky errors buried inside reams of code for a process that you never have to develop yourself? Furthermore, will you be able to skip all the basics in your career development and work on advanced things? I have my doubts. A lot of "horribly basic" "drudgery" will have to be done manually, because it is too important to leave to the whims of a LLM and people have no other way to develop the necessary skills to sustain the industry.
- danpalmer 2y ago
  Fair points, although I think you may be reading my points as more concrete than intended. When I'm talking about pay I'm thinking location-agnostic, i.e. low to high pay within a comparable region. For every engineer in London earning £100k there's many earning £26k doing more basic work. And when I say "basic" I don't just mean working with low level systems, I mean working with systems that are un-automated. Working with processes where someone has made the judgement call that it's cheaper to throw large numbers of cheap engineers at the problem rather than fewer highly paid engineers to automate it all away. That's not to say that highly paid engineers don't need to get into the basics, they definitely do, but that digging into the depths of an automated deployment system is not the same as running repetitive manual tasks.
- soco 2y ago
  Here is a question worth answering yet often overlooked: if AI helps the newbs generate useful stuff but which they don't properly understand, and also helps experienced find the issues on AI generated stuff based on their experience, WHERE is the middle ground where newbs can gain the experience to bring them to that senior level? I see no path going from there to there, unless the juniors start doing things by hand again, for which nobody will want to pay them (hey why don't you use AI instead). And seniors don't live forever...
Roark66 2y ago
70%... By lines written? Or by time taken? There is a huge difference. Sometimes you spend days trawling old code, even older dependencies to discover adding a line may fix your problem. In the meantime you may've read hundreds of pages of docs, seen dozens of diagrams. Hunted people that moved between departments and "worked on this before" etc. Then after you fix it yours in charge of organising testing and deployment to cert/prod including representing the change in risk assessment meetings. Good luck using AI to replace this work.
- danpalmer 2y ago
  I'm talking about time spent. I completely agree that all the work you've mentioned is stuff that takes time and that AI won't replace any time soon, but I strongly doubt that it's the bulk of the work. I'm talking about the programmers that a friend of mine works with who take several quarters to produce a dashboard, or the entry level PHP jobs that make barely above minimum wage and sell custom websites and hosting to real-estate companies in small towns, or the outsourced programmers that other friends interact with, who spent ~10 eng over 2 years building a "PaaS" style system in shell scripts that no one in their company actually uses because surprise surprise no one ever thought to ask whether it was necessary or had the right feature set or even worked (but management paid for it). These people are spending a significant amount of their time coding, but they're not spending time automating, or improving the process for next time, and so the work they're doing is fairly trivial and is most likely to be impacted by AI.
chipdart 2y ago
> What I don't think the HN bubble is fully familiar with is the fact that probably 70% of programming happening today is boring low paid drudgery (or maybe 50-90%). What I find odd is that AI tools are used to create new code but the bulk of the work is in rewriting and changing existing software,and fixing issues by touching single lines of code spread throughout the project. Perhaps AI tools will improve, but today you need an awful lot of prompting to get a single decent usable starting point. In some applications you end up spending far more time prompting the AI tool than what you would end up doing by simply writing the thing.
- soco 2y ago
  My usual dialogues with ChatGPT now 4o: I need a SQL to do 1, 2, 3, 4, and 5. GPT: sure thing. Me: umm you forgot 4. GPT: oops sorry, here. Me: now you forgot 3. GPT oops sorry, here. Me: you forgot 4 again. Make sure you do both 3 and 4. GPT: oops sorry, here. Me: you forgot 4 again the fuck I'll do it.
gofreddygo 2y ago
> boring low paid drudgery > the sort of work that AI is coming for This is NOT what AI is coming for. Its too far from even barely capable for that sort of work. BI tools, Wordpress themes, layers and layers of internal tools for custom business processes are all incredibly fragile and intricately balanced. It will have to learn systems where extra empty tags in the xml response get accounts flagged for removal, systems where the output must be a zip file archived within a .cab file for the downstream systems to be able to process it. Its an insanely stupid house of cards held together by bottom feeding groups of human intelligence. There's no budget to fix it. No incentive to improve it. It will never change, till its replaced with garbage from an even lower bottom feeding group. AI is hopeless, because of the sheer lack of anything to accurately train itself for this task. It is trying to sell itself to the OEMs and platforms with shiny demos as an even cheaper alternative to the bottom feeding group of outsourced labor. The joke is going to be real when the $$$ are spent on AI and the outcome is outsourced to the bottom feeding group to maintain.
- spaceman_2020 2y ago
  They literally said in the earnings call that they now need fewer third party developers because of AI. And this is one of the biggest legacy companies on the planet. Strange that the people in the trenches are saying that AI is helping them, but people on HN are screaming that AI is useless…
  - moneywoes 2y ago
    70% fewer?
  - rsynnott 2y ago
    > Strange that the people in the trenches are saying that AI is helping them, but people on HN are screaming that AI is useless… I mean, it sounds a lot like a standard management failure mode, which must be about half a century old at this stage: pretend you can get by on X% of staff due to [faddish pretext], then a year later when the cracks start showing quietly hire more people again. The nature of the fad changes, but the basic story is generally about the same. Actually, I’m not sure it’s even that; at this point the claim seems to be that they _can_ get by on 30% of the staff, not that they _are doing so_. There’s a decent chance this is just a case of “oh, shit, earnings call coming up, we have to mention AI because the markets like that”, tbh.
Ekaros 2y ago
I wonder how much of this can be actually automated by LLMs. Isn't substantial amount of time be just lazily spend tracking down what ever variable name or mapping to right thing? Just spend time adding very simple script as cronjob by CI/CD... And everything was copy paste. But it still took time to set up and name things. To get the small inconsequential details right.
- danpalmer 2y ago
  LLMs are fairly good at understanding how a bunch of naming in slightly different forms maps around a system. This is basically the one trick that transformers/attention does! I think a smart copy/paster is what LLMs will be good at. What they won't be good at is when there are deeper semantics, when there are performance requirements, when there's a complex data model, or when you need to come up with the data model and consider how that will work over time.
deleted 2y ago
[deleted]
anonzzzies 2y ago
I seems that the current AI is rather good at stomping together projects made of react saas starters with nano/microservices (workers etc) where everything is one shot and complete replace and some api routes. People who cannot code at all without AI are now making products that work and sell.
- thefz 2y ago
  Good luck when you have to hunt a bug, though.
  - soco 2y ago
    How about you just tell AI to build you a new site? Presumably your prompt will be better now, and AI will be a newer one, so chances are you'll get a site without that particular bug. This approach to debugging would be quite a new paradigm, and even a bit more adapted to consumer society for better or for worse.
    - dns_snek 2y ago
      Maybe you'll get a site without that particular bug, but you're almost guaranteed to get a site where the unspecified semantics are slightly different compared to the previous version, along with new exciting bugs, and at some point you're likely going to get to data corruption issues because some invariant of the system won't be preserved properly. You'll run into memory leaks and race conditions that you won't be able to resolve. At some point your AI will likely generate new exciting vulnerabilities, leak all customer data and get you buried in lawsuits too. All of these issues are nearly impossible to spot and correct unless you're an expert yourself, but then you wouldn't need AI in the first place. That said, I fully expect such an industry to take off and we'll all be worse off for it. Lowering the barrier to entry is empowering for those who couldn't develop software before, which is good, but if it enters mainstream usage then we're all going to suffer even worse products and services.
      - soco 2y ago
ac130kz 2y ago
GPT 4 Turbo can't even write good automations most of the time, these companies absolutely don't care about the quality of their product.

faeriechangling 2y ago

I'm well aware of this and in those sorts of jobs, most of the work isn't programming, it's sitting in meetings and communicating. While AI might help with this simply by shrinking the amount of people needed to do a job, I'm very dubious about a 70% efficiency gain when you look at the entire scope of what these workers do. The entire concept that if you make coding 70% more efficient that you'll make coders 70% more efficient is simply wrong.

gexla 2y ago
Maybe you need to be more specific about which workers you're talking about. Given a full time worker vs a contractor, I'm guessing the contractor has far less knowledge of the system as a whole, and ripe for being replaced. Then with freed up funds, maybe they hire more internal developers. It could be more of a reshuffling than anything else.

wakawaka28 2y ago

>On the other hand, if you're a highly paid software engineer, it's likely you're already working with highly automated and abstracted systems, so there's much less opportunity for LLMs. I think you're wrong about this. There are people today getting paid lots of money for basic jobs, and people with real difficult jobs that don't get paid much. Pay rate is as much a function of location and your particular company or industry as it is the actual nature of what you are doing. >Yes there's Copilot/etc which will reduce boilerplate, but the only way a company achieves "70% less coders" is by wholesale automation of large parts of their process that must be horribly basic already. The basics often only seem basic because we've done them a great deal. When the machines are charged with doing a lot of stuff, will the basics still appear basic? Will you be able to spot the critical yet tricky errors buried inside reams of code for a process that you never have to develop yourself? Furthermore, will you be able to skip all the basics in your career development and work on advanced things? I have my doubts. A lot of "horribly basic" "drudgery" will have to be done manually, because it is too important to leave to the whims of a LLM and people have no other way to develop the necessary skills to sustain the industry.

danpalmer 2y ago
Fair points, although I think you may be reading my points as more concrete than intended. When I'm talking about pay I'm thinking location-agnostic, i.e. low to high pay within a comparable region. For every engineer in London earning £100k there's many earning £26k doing more basic work. And when I say "basic" I don't just mean working with low level systems, I mean working with systems that are un-automated. Working with processes where someone has made the judgement call that it's cheaper to throw large numbers of cheap engineers at the problem rather than fewer highly paid engineers to automate it all away. That's not to say that highly paid engineers don't need to get into the basics, they definitely do, but that digging into the depths of an automated deployment system is not the same as running repetitive manual tasks.
soco 2y ago
Here is a question worth answering yet often overlooked: if AI helps the newbs generate useful stuff but which they don't properly understand, and also helps experienced find the issues on AI generated stuff based on their experience, WHERE is the middle ground where newbs can gain the experience to bring them to that senior level? I see no path going from there to there, unless the juniors start doing things by hand again, for which nobody will want to pay them (hey why don't you use AI instead). And seniors don't live forever...

Roark66 2y ago

70%... By lines written? Or by time taken? There is a huge difference. Sometimes you spend days trawling old code, even older dependencies to discover adding a line may fix your problem. In the meantime you may've read hundreds of pages of docs, seen dozens of diagrams. Hunted people that moved between departments and "worked on this before" etc. Then after you fix it yours in charge of organising testing and deployment to cert/prod including representing the change in risk assessment meetings. Good luck using AI to replace this work.

danpalmer 2y ago
I'm talking about time spent. I completely agree that all the work you've mentioned is stuff that takes time and that AI won't replace any time soon, but I strongly doubt that it's the bulk of the work. I'm talking about the programmers that a friend of mine works with who take several quarters to produce a dashboard, or the entry level PHP jobs that make barely above minimum wage and sell custom websites and hosting to real-estate companies in small towns, or the outsourced programmers that other friends interact with, who spent ~10 eng over 2 years building a "PaaS" style system in shell scripts that no one in their company actually uses because surprise surprise no one ever thought to ask whether it was necessary or had the right feature set or even worked (but management paid for it). These people are spending a significant amount of their time coding, but they're not spending time automating, or improving the process for next time, and so the work they're doing is fairly trivial and is most likely to be impacted by AI.

chipdart 2y ago

> What I don't think the HN bubble is fully familiar with is the fact that probably 70% of programming happening today is boring low paid drudgery (or maybe 50-90%). What I find odd is that AI tools are used to create new code but the bulk of the work is in rewriting and changing existing software,and fixing issues by touching single lines of code spread throughout the project. Perhaps AI tools will improve, but today you need an awful lot of prompting to get a single decent usable starting point. In some applications you end up spending far more time prompting the AI tool than what you would end up doing by simply writing the thing.

soco 2y ago
My usual dialogues with ChatGPT now 4o: I need a SQL to do 1, 2, 3, 4, and 5. GPT: sure thing. Me: umm you forgot 4. GPT: oops sorry, here. Me: now you forgot 3. GPT oops sorry, here. Me: you forgot 4 again. Make sure you do both 3 and 4. GPT: oops sorry, here. Me: you forgot 4 again the fuck I'll do it.

gofreddygo 2y ago

> boring low paid drudgery > the sort of work that AI is coming for This is NOT what AI is coming for. Its too far from even barely capable for that sort of work. BI tools, Wordpress themes, layers and layers of internal tools for custom business processes are all incredibly fragile and intricately balanced. It will have to learn systems where extra empty tags in the xml response get accounts flagged for removal, systems where the output must be a zip file archived within a .cab file for the downstream systems to be able to process it. Its an insanely stupid house of cards held together by bottom feeding groups of human intelligence. There's no budget to fix it. No incentive to improve it. It will never change, till its replaced with garbage from an even lower bottom feeding group. AI is hopeless, because of the sheer lack of anything to accurately train itself for this task. It is trying to sell itself to the OEMs and platforms with shiny demos as an even cheaper alternative to the bottom feeding group of outsourced labor. The joke is going to be real when the $$$ are spent on AI and the outcome is outsourced to the bottom feeding group to maintain.

spaceman_2020 2y ago
They literally said in the earnings call that they now need fewer third party developers because of AI. And this is one of the biggest legacy companies on the planet. Strange that the people in the trenches are saying that AI is helping them, but people on HN are screaming that AI is useless…
- moneywoes 2y ago
  70% fewer?
- rsynnott 2y ago
  > Strange that the people in the trenches are saying that AI is helping them, but people on HN are screaming that AI is useless… I mean, it sounds a lot like a standard management failure mode, which must be about half a century old at this stage: pretend you can get by on X% of staff due to [faddish pretext], then a year later when the cracks start showing quietly hire more people again. The nature of the fad changes, but the basic story is generally about the same. Actually, I’m not sure it’s even that; at this point the claim seems to be that they _can_ get by on 30% of the staff, not that they _are doing so_. There’s a decent chance this is just a case of “oh, shit, earnings call coming up, we have to mention AI because the markets like that”, tbh.

Ekaros 2y ago

I wonder how much of this can be actually automated by LLMs. Isn't substantial amount of time be just lazily spend tracking down what ever variable name or mapping to right thing? Just spend time adding very simple script as cronjob by CI/CD... And everything was copy paste. But it still took time to set up and name things. To get the small inconsequential details right.

danpalmer 2y ago
LLMs are fairly good at understanding how a bunch of naming in slightly different forms maps around a system. This is basically the one trick that transformers/attention does! I think a smart copy/paster is what LLMs will be good at. What they won't be good at is when there are deeper semantics, when there are performance requirements, when there's a complex data model, or when you need to come up with the data model and consider how that will work over time.

deleted 2y ago

[deleted]

anonzzzies 2y ago

I seems that the current AI is rather good at stomping together projects made of react saas starters with nano/microservices (workers etc) where everything is one shot and complete replace and some api routes. People who cannot code at all without AI are now making products that work and sell.

thefz 2y ago
Good luck when you have to hunt a bug, though.
- soco 2y ago
  How about you just tell AI to build you a new site? Presumably your prompt will be better now, and AI will be a newer one, so chances are you'll get a site without that particular bug. This approach to debugging would be quite a new paradigm, and even a bit more adapted to consumer society for better or for worse.
  - dns_snek 2y ago
    Maybe you'll get a site without that particular bug, but you're almost guaranteed to get a site where the unspecified semantics are slightly different compared to the previous version, along with new exciting bugs, and at some point you're likely going to get to data corruption issues because some invariant of the system won't be preserved properly. You'll run into memory leaks and race conditions that you won't be able to resolve. At some point your AI will likely generate new exciting vulnerabilities, leak all customer data and get you buried in lawsuits too. All of these issues are nearly impossible to spot and correct unless you're an expert yourself, but then you wouldn't need AI in the first place. That said, I fully expect such an industry to take off and we'll all be worse off for it. Lowering the barrier to entry is empowering for those who couldn't develop software before, which is good, but if it enters mainstream usage then we're all going to suffer even worse products and services.
    - soco 2y ago

ac130kz 2y ago

GPT 4 Turbo can't even write good automations most of the time, these companies absolutely don't care about the quality of their product.