4 ms·

> I don't think they're a net gain if you're a skilled senior I'm a skilled senior (I'm 54 and been coding since I was about 8; I've been 100% AI-generated cod

> I don't think they're a net gain if you're a skilled senior I'm a skilled senior (I'm 54 and been coding since I was about 8; I've been 100% AI-generated code for at least 6 months now and have produced a combination of speed and quality that has astonished me; my velocity is apparent at https://github.com/pmarreck/ https://github.com/pmarreck/) and this has been a massive net gain, so your claim is now officially in sheer defiance of reality. In a skilled senior's hands, this is like an expert power tool. In the hands of someone less-skilled, it is likely also... less-skilled. It's a magnifier. > and the hidden cost in terms of technical debt and skill atrophy is just being swept under the rug. Nope, no it's not. It's being reviewed, measured, and controlled against. Because... you WILL need more controls to take full advantage. Look, I even invented a whole new control methodology around it called MFIC: https://gist.github.com/pmarreck/b30aa3ca69cb70a5526f8a63ab8c8d7e https://gist.github.com/pmarreck/b30aa3ca69cb70a5526f8a63ab8...

byzantinegene 3mo ago
you're right, but if skills atrophy so will the efficacy of the tool.
- pmarreck 3mo ago
  Skills atrophying in terms of what? Remembering specific API's that you always had to look up anyway? You don't lose developer intuition, analytical thinking or technical inclination, and those are the things that matter, anyway. I recently did a fleetwide upgrade to Zig 0.16. Do I remember every single change from 0.15? No. Do I have to? Also no. Both because I can look it up if I need to, but also because the LLM already does. If I don't look at a codebase that I myself haven't looked at in a year, I will not recognize some things when I return to it. Is this sense of "atrophy" meaningful when this was a problem long before LLMs came on the scene?
  - wesleywt 3mo ago
    How do you deal with the lack of cognitive engagement? I think it is the primary driver of developing and maintaining skills as well as generating new ideas. Letting an agent do it for you will just get you average but well formatted code. Not something new.
    - bfjvibybd6cuvu6 3mo ago
      I haven't cared about cognitive engagement in over a decade. Neither has my CEO.
dimitrios1 3mo ago
I am another skilled senior, have been coding since I was 7, although you have a few more years of experience on me, and am commenting here just for the goldilocks moment, as I have read and reflected on both of your comments and find my reality is somewhere in the middle. On personal projects, where I am in charge of all the hats (product development, UI, UX, backend, security, server admin, etc) -- absolutely crazy force multiplier. You get a nice suite of backend and e2e tests running, with full business scenario layered on top of that, and constantly running agents to do the coding, another agent on a higher level of reasoning to review that work, and sometimes occasionally poping into another competitors model to review their work just for added comfort -- it feels like wizardry. I am not vibing it, but I wouldn't say I am carefully scrolling through every line. I review whats fundamentally important, especially when it comes to data, overall structure, and large, cross cutting concerns, but I would be lying if I say some code doesn't land that I don't read. But I have the security of the test suites and validations , so I pour more effort into that. It's a nice self reinforceing loop. All of this might sound like I agree with you, and to some extent I do, but I am realizing as the apps I have built out like a cannon shot out of hell with tremendous speed and polish right out of the gate are starting to slow down. Feature adds are getting more complex. My memory is not what it used to be. Each run and pass through the code consumes more of my tokens and limits. I am starting to do less in the same amount of time. Codex did a vertical slice of a feature for me (well defined and well planned). It contained functionality that has historically plagued us developers -- the dreaded time. I used xHigh GPT 5.5. It had obvious bugs, but I wanted the robots to catch it. I popped it in claude (on the new sonnet 5! heyo!) -- Claude caught the bugs. Even said they "immediately stood out" I wondered how this happened. Frontier model from company A was evaluated by workhorse model from company B. All of this again took massive amounts of usage. And time. And this is -- best case scenario, perfect world, everything is in perfect alignment. Now for the work reality. Multiple product and experience owners. Multiple dev teams. Different enterprise teams support services you rely on. You don't have full unfettered access to frontier models. You have to use copilot, or some other enterprise harness, and you run out of credits for the month, you are SOL. It's not as good as your claude, you think to yourself, but hey, its familiar enough, and you have 5k credits left for the month for Opus 4.8, better make the best of it. But now you burned half of them working on that Transactional Bug that was mixing synchronous and asynchronous semantics that the other guy's model should have picked up on. What happened? Maybe he didn't use Opus, maybe he used Haiku, maybe his prompt was bad. Who knows. Gotta fix it. Oh, you gotta reach across the isle and put in a request to get the Enterprise team to look at this caching inconsistency on user data that you need and is really the source of your race conditions. Tick tick tick. Model limits approaching. You start wondering if you just did all this by hand like "in the old days" would you have got it done correctly faster? Or at least, cheaper. You'll never know.
throwaway27448 3mo ago
Have you really found claude to much more more capable than eg deepseek? Anthropic has little to no chance of producing a competitive business model in the long term.
- jeffyaw 3mo ago
  absolutely, for me the tui, ultracode agentic workflows, and streaming logic are far superior. the closest model is minimax 3.0 imo and i ended up adding a custom tui, agentic workflows, streaming logic and implementing skills to that (in typed) in order to get to an acceptable claude fallback. on their own i haven’t found one model comparable to claude, not even chatgpt.
- hhh 3mo ago
  Yeah, using deepseek feels like shit and I spend hours steering deepseek in a direction versus opus-4.7 or 4.8 where I can just kinda let it ball out on some reverse engineering problems.
- n3storm 3mo ago
  I don't. Using claude code, claude.md etc with deepseek v4 is almost undistinguishable.
- boc 3mo ago
  > Anthropic has little to no chance of producing a competitive business model in the long term. Extraordinary thing to say about the fastest growing company in the history of capitalism. They will soon have access to public markets, essentially unlimited capital, and can build insanely large models that they don't have to make public... ever. They can just use those models to run their business, train better models, eat competitors, etc. But maybe it's Anthropic that isn't thinking ahead enough - you clearly think you can see around corners with your proclamation. So why do you think they have "little to no chance" of surviving long term?
  - jurgenburgen 3mo ago
    > Extraordinary thing to say about the fastest growing company in the history of capitalism. They will soon have access to public markets, essentially unlimited capital There is no such thing as unlimited capital. The faster they grow the faster they burn capital. Eventually it will run out.
jimbo808 3mo ago
I think I might have written a comment similar to yours maybe 6 months or a year ago. I'm not quite sure to respond to these sorts of replies. I have used LLMs/Claude Code quite extensively professionally and was a very early adopter, have built tooling around LLM/agentic development, and genuinely embraced it. They aren't useless, but the short term gains you think you're getting come at a very steep price that you may not actually account for consciously for quite some time, if ever.
- aix1 3mo ago
  > a very steep price that you may not actually account for Could you elaborate on this steep price that you have in mind? What does it consist of?
  - mrbungie 3mo ago
    From what I gather from GPs upper post: Technical debt, skill atrophy, delusions of grandeur about one's own abilities / psychosis.
  - shevis 3mo ago
    The cost is skill atrophy. When was the last time you wrote something entirely from scratch by hand without AI assistance? It’s a skill entirely separate from prompting and reviewing. And it atrophies when you stop using it.
    - aix1 3mo ago
      > The cost is skill atrophy I hear what you're saying but I'm not sure I buy it in the context of this thread (a response to someone who is 54 and has been coding since they were eight). I am in a similar boat, having been coding full-time for fourty years. The way I use the current tools is that I own all architectural and design decisions but let Claude Code fill in the blanks. I reckon the quality of the output is about 90% of what it would have been had I done everything myself, but I get a lot more done (easily 3-5X). Will I forget how to write a "for" loop just because I haven't been writing many of them by hand lately? Those skills are so deeply ingrained that I seriously doubt it. I can ride a bike after a multi-year break, or converse in a language I haven't regularly spoken for several decades. Or write using pen & paper even though I hardly ever do it. I don't see why coding would be any different.
kerabatsos 3mo ago
Finally, someone said it. 20+ years in software and my productivity and velocity is wild right now.
integricho 3mo ago
I believe you are miscalculating the effect of skill atrophy, there is benefit and actual experience gained by doing the work yourself. You are an experienced dev and already have a lot of tools and knowledge under your belt so at the moment it is hard to see the actual issue, as this is just a productivity multiplierfor you. But give it a couple of years working under these conditions, your tech savvy nature will be severely diminished.
- alchemism 3mo ago
  In a couple of years he will be 60, too. Then 65, then 70. Seniors will be able to stay in the game much longer than before, mark my words.
  - aix1 3mo ago
    Indeed. I think it's a much bigger issue for juniors, who haven't yet had a chance to build that systems design muscle. When an LLM is making a bad design decision but the engineer doesn't have the experience to spot it AND the consequences don't become apparent until much later (which is often the case) -- it's kinda hard to learn.
Thanemate 3mo ago
The skilled seniors better stop downplaying what actually led them to be skilled in the first place, and realize that the conditions to develop that skill has been gone and almost deemed unproductive in today's workplace. Not disagreeing that LLM's are a force multiplier, but I highly doubt whatever value will end up finding multiplying in the next generation of seniors, at this rate. It's surreal to me that I have to point out that recognition AND recalling are both necessary components of skill acquisition, because humans largely knew this since the dawn of education.
- einichi 3mo ago
  This is something for educators to deal with, not a 50+ senior IC, but yes your point is extremely important.
  - monk_e_boy 3mo ago
    As an educator (UK) it's very hard to find people with experience to join us. The pay is SO crap and the workload is huge. Trying to teach complex, large systems is impossible, because we don't have them. We can't throw 1,000 files and 20,000 lines of code at a student and teach them how the system was engineered. We can show them toy systems.... which is fine if there is a work route that takes them and nutures them for 5 or so years. But without that pipeline, shrug not sure what we do about it
- vincnetas 3mo ago
  i would rephrase "Force multiplier" as "Force power up". If your "force" is above 1 then its ok to have AI power up your force. 2.3 to the power of 3 is 12.169. But if you're a beginner and your "force" is bellow 1 so power upping this makes it worse. 0.2 to power of 3 is 0.008
- chewz 3mo ago
  I have been thinking about it - paid apprenticeship is the answer - just as it is in other professions like medicine. Seniors should be paid to actively introduce juniors to the trade over couple of years. No more bootcamp entry. And it would be significant $ for senior to agree to expend his time and energy on software engineering apprentices. There would be also very limited number of places with good seniors. Exactly like medicine for a long time now. In fact it is already happening in some companies I know about - seniors geting their bonuses tied to juniors being under their wings.
sensanaty 3mo ago
We've just done an official evaluation at work, using extensive statistics on our gigantic monorepo in a company with ~2000 devs over the course of 2 years, everyone from hardware engineers to regular old frontend engineers. It's a highly profitable and mature public company, and has been for going on a decade at this point without missing a beat. We were given infinite access & budgets to basically any and all AI tooling we could imagine, and we have several "AI Native" teams (whatever the fuck that even means). We're doing agentic coding, we have harnesses of all kind, skills, we have many teams doing spec-driven development, designers using all the various things like Figma Make and access to tools like Devin/Factory Droid/Claude Code/Codex/etc. This is all to say, we as a company are using AI a lot in all possible corners, but thankfully our leadership isn't schizophrenic and isn't mandating everyone hit token limits or whatever, it's more of a "Let's see what works and what doesn't" type of thing, and we measure a lot of statistics. Nobody here really cares whether LLMs are the next coming of Christ or not, as a company there are many people (even in SLT) that are indifferent to LLMs, and many who are reasonably hyped. I wish I could link to the actual document we were all shown since it has a beautiful breakdown of the methodology and a fine-grained breakdown of the stats and the categories measured, but in the grand scheme of things, ALL the AI tooling we have implemented (at least on the engineering side of the equation) has contributed to a total of... drum roll please... 7 (seven) Percent overall productivity increase! The most productive teams saw a productivity increase of around 20%, while some teams actually saw drops in productivity into the negative percentage points. My team, none of us really give a shit about AI and we're somewhere in the 3-5% range on certain categories of tasks, which I'd say is a fairly good assessment. Productivity here is measured in many ways, including but not limited to speed of MR review and merge times, feature/ticket/roadmap closure/delivery, rollback/revert incidence rate, how often people interact with the MR review bots and implement their suggestions/fixes, how many times people check back on AI transcriptions/meeting notes (hint: Nobody looks back on any of it, it's all just noise that gets generated and never actually referenced outside a few extremely rare cases) and many more things I'm forgetting. It is an imperfect number of course, because measuring productivity in engineering is a sisyphean task, but in my opinion it is accurate to the reality on the ground and outside of all the hype and marketing bullshit. So, I remain thoroughly unconvinced of these personal anecdotes of people being "massively" more productive, especially once you factor in the fact that we now have a 2000EUR budget/month/dev for all the AI tooling, those productivity numbers start looking pathetic once you factor in the costs (which are only increasing as the AI companies need to start recouping the gazillions they've burned). Some teams have started begging to disable coderabbit and other similar tools in their MRs because they're producing nothing but walls of noise that makes reviewing any MR a nightmare of sludging through endless slop of useless bullshit, ours included.
kakacik 3mo ago
You very conveniently avoided skill atrophy, the biggest issue for existing engineers to deal with (not even going into topic of cancelling whole hiring-junior-and-raise-senior approach which is just shortsighted and retarded to be polite, but general greed has overtaken the field so its not shocking this went out of window). Everybody using llms excessively is measurably doing worse, ie students. I have hard time believing out industry is somehow immune to that and refuse to do the experiment on myself if avoidable, which it sort of is for me. Its like drug that will give you few years of great high, and ruin rest of your life afterwards. Use it by all means, I don't care about your output, nobody here does, you do you. I do care about my long term skills, which aren't about piping some llm outputs. My employer ain't dumb fuck who is pushing for llms at all costs as much as possible. Anyway, most of my day work are processes, discussions, pushing things through - llms can't do a shit here, its personal conversations, connections, often psychical contact to get things done on time. Startup world would be different but I am as far from that unstable environment as I am from say gaming industry, just not worth my time outside SV area. So I just use llms to verify my coding results, they are fine for that, but I do the creativity. Its by far the best part of my software dev work, why the heck would I be automating that away? Its like automating sex away so you can have more time... reading HN or some other way to just waste time, dumb approach from all angles. Of course this changes if one is working on personal projects, self-employed, small startup etc but most folks here are not in that category.
philipwhiuk 3mo ago
> MFIC Getting another agent to validate the first agent is a tower of sand. > my velocity is apparent at https://github.com/pmarreck/ https://github.com/pmarreck/) Forgive me, but the active repos all look like reimplementations of existing good open source code (which of course is ideal training data) - rm_safe has rip for example. Or prototypes. Is there anything that actually has a user base > 1?

byzantinegene 3mo ago

you're right, but if skills atrophy so will the efficacy of the tool.

pmarreck 3mo ago
Skills atrophying in terms of what? Remembering specific API's that you always had to look up anyway? You don't lose developer intuition, analytical thinking or technical inclination, and those are the things that matter, anyway. I recently did a fleetwide upgrade to Zig 0.16. Do I remember every single change from 0.15? No. Do I have to? Also no. Both because I can look it up if I need to, but also because the LLM already does. If I don't look at a codebase that I myself haven't looked at in a year, I will not recognize some things when I return to it. Is this sense of "atrophy" meaningful when this was a problem long before LLMs came on the scene?
- wesleywt 3mo ago
  How do you deal with the lack of cognitive engagement? I think it is the primary driver of developing and maintaining skills as well as generating new ideas. Letting an agent do it for you will just get you average but well formatted code. Not something new.
  - bfjvibybd6cuvu6 3mo ago
    I haven't cared about cognitive engagement in over a decade. Neither has my CEO.

dimitrios1 3mo ago

I am another skilled senior, have been coding since I was 7, although you have a few more years of experience on me, and am commenting here just for the goldilocks moment, as I have read and reflected on both of your comments and find my reality is somewhere in the middle. On personal projects, where I am in charge of all the hats (product development, UI, UX, backend, security, server admin, etc) -- absolutely crazy force multiplier. You get a nice suite of backend and e2e tests running, with full business scenario layered on top of that, and constantly running agents to do the coding, another agent on a higher level of reasoning to review that work, and sometimes occasionally poping into another competitors model to review their work just for added comfort -- it feels like wizardry. I am not vibing it, but I wouldn't say I am carefully scrolling through every line. I review whats fundamentally important, especially when it comes to data, overall structure, and large, cross cutting concerns, but I would be lying if I say some code doesn't land that I don't read. But I have the security of the test suites and validations , so I pour more effort into that. It's a nice self reinforceing loop. All of this might sound like I agree with you, and to some extent I do, but I am realizing as the apps I have built out like a cannon shot out of hell with tremendous speed and polish right out of the gate are starting to slow down. Feature adds are getting more complex. My memory is not what it used to be. Each run and pass through the code consumes more of my tokens and limits. I am starting to do less in the same amount of time. Codex did a vertical slice of a feature for me (well defined and well planned). It contained functionality that has historically plagued us developers -- the dreaded time. I used xHigh GPT 5.5. It had obvious bugs, but I wanted the robots to catch it. I popped it in claude (on the new sonnet 5! heyo!) -- Claude caught the bugs. Even said they "immediately stood out" I wondered how this happened. Frontier model from company A was evaluated by workhorse model from company B. All of this again took massive amounts of usage. And time. And this is -- best case scenario, perfect world, everything is in perfect alignment. Now for the work reality. Multiple product and experience owners. Multiple dev teams. Different enterprise teams support services you rely on. You don't have full unfettered access to frontier models. You have to use copilot, or some other enterprise harness, and you run out of credits for the month, you are SOL. It's not as good as your claude, you think to yourself, but hey, its familiar enough, and you have 5k credits left for the month for Opus 4.8, better make the best of it. But now you burned half of them working on that Transactional Bug that was mixing synchronous and asynchronous semantics that the other guy's model should have picked up on. What happened? Maybe he didn't use Opus, maybe he used Haiku, maybe his prompt was bad. Who knows. Gotta fix it. Oh, you gotta reach across the isle and put in a request to get the Enterprise team to look at this caching inconsistency on user data that you need and is really the source of your race conditions. Tick tick tick. Model limits approaching. You start wondering if you just did all this by hand like "in the old days" would you have got it done correctly faster? Or at least, cheaper. You'll never know.

throwaway27448 3mo ago

Have you really found claude to much more more capable than eg deepseek? Anthropic has little to no chance of producing a competitive business model in the long term.

jeffyaw 3mo ago
absolutely, for me the tui, ultracode agentic workflows, and streaming logic are far superior. the closest model is minimax 3.0 imo and i ended up adding a custom tui, agentic workflows, streaming logic and implementing skills to that (in typed) in order to get to an acceptable claude fallback. on their own i haven’t found one model comparable to claude, not even chatgpt.
hhh 3mo ago
Yeah, using deepseek feels like shit and I spend hours steering deepseek in a direction versus opus-4.7 or 4.8 where I can just kinda let it ball out on some reverse engineering problems.
n3storm 3mo ago
I don't. Using claude code, claude.md etc with deepseek v4 is almost undistinguishable.
boc 3mo ago
> Anthropic has little to no chance of producing a competitive business model in the long term. Extraordinary thing to say about the fastest growing company in the history of capitalism. They will soon have access to public markets, essentially unlimited capital, and can build insanely large models that they don't have to make public... ever. They can just use those models to run their business, train better models, eat competitors, etc. But maybe it's Anthropic that isn't thinking ahead enough - you clearly think you can see around corners with your proclamation. So why do you think they have "little to no chance" of surviving long term?
- jurgenburgen 3mo ago
  > Extraordinary thing to say about the fastest growing company in the history of capitalism. They will soon have access to public markets, essentially unlimited capital There is no such thing as unlimited capital. The faster they grow the faster they burn capital. Eventually it will run out.

jimbo808 3mo ago

I think I might have written a comment similar to yours maybe 6 months or a year ago. I'm not quite sure to respond to these sorts of replies. I have used LLMs/Claude Code quite extensively professionally and was a very early adopter, have built tooling around LLM/agentic development, and genuinely embraced it. They aren't useless, but the short term gains you think you're getting come at a very steep price that you may not actually account for consciously for quite some time, if ever.

aix1 3mo ago
> a very steep price that you may not actually account for Could you elaborate on this steep price that you have in mind? What does it consist of?
- mrbungie 3mo ago
  From what I gather from GPs upper post: Technical debt, skill atrophy, delusions of grandeur about one's own abilities / psychosis.
- shevis 3mo ago
  The cost is skill atrophy. When was the last time you wrote something entirely from scratch by hand without AI assistance? It’s a skill entirely separate from prompting and reviewing. And it atrophies when you stop using it.
  - aix1 3mo ago
    > The cost is skill atrophy I hear what you're saying but I'm not sure I buy it in the context of this thread (a response to someone who is 54 and has been coding since they were eight). I am in a similar boat, having been coding full-time for fourty years. The way I use the current tools is that I own all architectural and design decisions but let Claude Code fill in the blanks. I reckon the quality of the output is about 90% of what it would have been had I done everything myself, but I get a lot more done (easily 3-5X). Will I forget how to write a "for" loop just because I haven't been writing many of them by hand lately? Those skills are so deeply ingrained that I seriously doubt it. I can ride a bike after a multi-year break, or converse in a language I haven't regularly spoken for several decades. Or write using pen & paper even though I hardly ever do it. I don't see why coding would be any different.

kerabatsos 3mo ago

Finally, someone said it. 20+ years in software and my productivity and velocity is wild right now.

integricho 3mo ago

I believe you are miscalculating the effect of skill atrophy, there is benefit and actual experience gained by doing the work yourself. You are an experienced dev and already have a lot of tools and knowledge under your belt so at the moment it is hard to see the actual issue, as this is just a productivity multiplierfor you. But give it a couple of years working under these conditions, your tech savvy nature will be severely diminished.

alchemism 3mo ago
In a couple of years he will be 60, too. Then 65, then 70. Seniors will be able to stay in the game much longer than before, mark my words.
- aix1 3mo ago
  Indeed. I think it's a much bigger issue for juniors, who haven't yet had a chance to build that systems design muscle. When an LLM is making a bad design decision but the engineer doesn't have the experience to spot it AND the consequences don't become apparent until much later (which is often the case) -- it's kinda hard to learn.

Thanemate 3mo ago

The skilled seniors better stop downplaying what actually led them to be skilled in the first place, and realize that the conditions to develop that skill has been gone and almost deemed unproductive in today's workplace. Not disagreeing that LLM's are a force multiplier, but I highly doubt whatever value will end up finding multiplying in the next generation of seniors, at this rate. It's surreal to me that I have to point out that recognition AND recalling are both necessary components of skill acquisition, because humans largely knew this since the dawn of education.

einichi 3mo ago
This is something for educators to deal with, not a 50+ senior IC, but yes your point is extremely important.
- monk_e_boy 3mo ago
  As an educator (UK) it's very hard to find people with experience to join us. The pay is SO crap and the workload is huge. Trying to teach complex, large systems is impossible, because we don't have them. We can't throw 1,000 files and 20,000 lines of code at a student and teach them how the system was engineered. We can show them toy systems.... which is fine if there is a work route that takes them and nutures them for 5 or so years. But without that pipeline, shrug not sure what we do about it
vincnetas 3mo ago
i would rephrase "Force multiplier" as "Force power up". If your "force" is above 1 then its ok to have AI power up your force. 2.3 to the power of 3 is 12.169. But if you're a beginner and your "force" is bellow 1 so power upping this makes it worse. 0.2 to power of 3 is 0.008
chewz 3mo ago
I have been thinking about it - paid apprenticeship is the answer - just as it is in other professions like medicine. Seniors should be paid to actively introduce juniors to the trade over couple of years. No more bootcamp entry. And it would be significant $ for senior to agree to expend his time and energy on software engineering apprentices. There would be also very limited number of places with good seniors. Exactly like medicine for a long time now. In fact it is already happening in some companies I know about - seniors geting their bonuses tied to juniors being under their wings.

sensanaty 3mo ago

We've just done an official evaluation at work, using extensive statistics on our gigantic monorepo in a company with ~2000 devs over the course of 2 years, everyone from hardware engineers to regular old frontend engineers. It's a highly profitable and mature public company, and has been for going on a decade at this point without missing a beat. We were given infinite access & budgets to basically any and all AI tooling we could imagine, and we have several "AI Native" teams (whatever the fuck that even means). We're doing agentic coding, we have harnesses of all kind, skills, we have many teams doing spec-driven development, designers using all the various things like Figma Make and access to tools like Devin/Factory Droid/Claude Code/Codex/etc. This is all to say, we as a company are using AI a lot in all possible corners, but thankfully our leadership isn't schizophrenic and isn't mandating everyone hit token limits or whatever, it's more of a "Let's see what works and what doesn't" type of thing, and we measure a lot of statistics. Nobody here really cares whether LLMs are the next coming of Christ or not, as a company there are many people (even in SLT) that are indifferent to LLMs, and many who are reasonably hyped. I wish I could link to the actual document we were all shown since it has a beautiful breakdown of the methodology and a fine-grained breakdown of the stats and the categories measured, but in the grand scheme of things, ALL the AI tooling we have implemented (at least on the engineering side of the equation) has contributed to a total of... drum roll please... 7 (seven) Percent overall productivity increase! The most productive teams saw a productivity increase of around 20%, while some teams actually saw drops in productivity into the negative percentage points. My team, none of us really give a shit about AI and we're somewhere in the 3-5% range on certain categories of tasks, which I'd say is a fairly good assessment. Productivity here is measured in many ways, including but not limited to speed of MR review and merge times, feature/ticket/roadmap closure/delivery, rollback/revert incidence rate, how often people interact with the MR review bots and implement their suggestions/fixes, how many times people check back on AI transcriptions/meeting notes (hint: Nobody looks back on any of it, it's all just noise that gets generated and never actually referenced outside a few extremely rare cases) and many more things I'm forgetting. It is an imperfect number of course, because measuring productivity in engineering is a sisyphean task, but in my opinion it is accurate to the reality on the ground and outside of all the hype and marketing bullshit. So, I remain thoroughly unconvinced of these personal anecdotes of people being "massively" more productive, especially once you factor in the fact that we now have a 2000EUR budget/month/dev for all the AI tooling, those productivity numbers start looking pathetic once you factor in the costs (which are only increasing as the AI companies need to start recouping the gazillions they've burned). Some teams have started begging to disable coderabbit and other similar tools in their MRs because they're producing nothing but walls of noise that makes reviewing any MR a nightmare of sludging through endless slop of useless bullshit, ours included.

kakacik 3mo ago

You very conveniently avoided skill atrophy, the biggest issue for existing engineers to deal with (not even going into topic of cancelling whole hiring-junior-and-raise-senior approach which is just shortsighted and retarded to be polite, but general greed has overtaken the field so its not shocking this went out of window). Everybody using llms excessively is measurably doing worse, ie students. I have hard time believing out industry is somehow immune to that and refuse to do the experiment on myself if avoidable, which it sort of is for me. Its like drug that will give you few years of great high, and ruin rest of your life afterwards. Use it by all means, I don't care about your output, nobody here does, you do you. I do care about my long term skills, which aren't about piping some llm outputs. My employer ain't dumb fuck who is pushing for llms at all costs as much as possible. Anyway, most of my day work are processes, discussions, pushing things through - llms can't do a shit here, its personal conversations, connections, often psychical contact to get things done on time. Startup world would be different but I am as far from that unstable environment as I am from say gaming industry, just not worth my time outside SV area. So I just use llms to verify my coding results, they are fine for that, but I do the creativity. Its by far the best part of my software dev work, why the heck would I be automating that away? Its like automating sex away so you can have more time... reading HN or some other way to just waste time, dumb approach from all angles. Of course this changes if one is working on personal projects, self-employed, small startup etc but most folks here are not in that category.

philipwhiuk 3mo ago

> MFIC Getting another agent to validate the first agent is a tower of sand. > my velocity is apparent at https://github.com/pmarreck/ https://github.com/pmarreck/) Forgive me, but the active repos all look like reimplementations of existing good open source code (which of course is ideal training data) - rm_safe has rip for example. Or prototypes. Is there anything that actually has a user base > 1?