13 ms·

One thing I find frustrating is that management where I work has heard of 10x productivity gains. Some of those claims even come from early adopters at my work.

One thing I find frustrating is that management where I work has heard of 10x productivity gains. Some of those claims even come from early adopters at my work. But that sets expectation way too high. Partly it is due to Amdahl's law: I spend only a portion of my time coding, and far more time thinking and communicating with others that are customers of my code. Even if does make the coding 10x faster (and it doesn't most of the time) overall my productivity is 10-15% better. That is nothing to sneeze at, but it isn't 10x.

louthy 1y ago
> overall my productivity is 10-15% better. That is nothing to sneeze at, but it isn't 10x. It is something to sneeze at if you are 10-15% more expensive to employ due to the cost of the LLM tools. The total cost of production should always be considered, not just throughput.
- bravesoul2 1y ago
  That's a good insight be because with perfect competition it means you need to share your old salary with an LLM!
- votepaunchy 1y ago
  > if you are 10-15% more expensive to employ due to the cost of the LLM tools How is one spending anywhere close to 10% of total compensation on LLMs?
- CharlesW 1y ago
  > It is something to sneeze at if you are 10-15% more expensive to employ due to the cost of the LLM tools. Claude Max is $200/month, or ~2% of the salary of an average software engineer.
  - m4rtink 1y ago
    Does anyone actually know what the real cost for the customers will be once the free AI money no longer floods those companies?
    - wubrr 1y ago
      I'm no LLM evangelist, far from it, but I expect models of similar quality to the current bleeding-edge, will be freely runnable on consumer hardware within 3 years. Future bleeding-edge models may well be more expensive than current ones, who knows.
      - ls612 1y ago
        How do the best models that can run on say a single 4090 today compare to GPT 3.5?
        electroglyph 1y ago
        Qwen 2.5 32B which is an older model at this point clearly outperforms it: https://llm-stats.com/models/compare/gpt-3.5-turbo-0125-vs-qwen-2.5-32b-instruct https://llm-stats.com/models/compare/gpt-3.5-turbo-0125-vs-q...
        ls612 1y ago
        Even when quantized down to 4 bits to fit on a 4090?
        FuckButtons 1y ago
        Not in my experience, running qwen3:32b is good, but it’s not as coherent or useful as 3.5 at a 4bit quant. But the gap is a lot narrower than llama 70b.
      - TeMPOraL 1y ago
        For the purpose of keeping the costs of LLM-dependent services down, you don't need to run bleeding-edge models on single consumer GPUs. Even if it takes a hundred GPUs, it still means people can start businesses around hosting those models, and compete with the large vendors.
    - jppope 1y ago
      yeah there was an analysis that came out on hackernews the other day. between low demand side economics, virtually no impact to GDP, and corporate/vc subsidies going away soon we're close to finding out. Sam Altman did convince Softbank to do a 40B round though so it might be another year or two. Current estimates are that its cheaper than search to run so its probabilistic that there will be more search features swapped. OpenAi hasn't dropped their ad platform yet though, so interested to see how that goes
  - selfhoster11 1y ago
    In the US, maybe. Several times that by percentage in other places around the world.
  - GeoAtreides 1y ago
    the average software engineer makes $10000 a month after taxes?!
wubrr 1y ago
> One thing I find frustrating is that management where I work has heard of 10x productivity gains. Some of those claims even come from early adopters at my work. Similar situation at my work, but all of the productivity claims from internal early adopters I've seen so far are based on very narrow ways of measuring productivity, and very sketchy math, to put it mildly.
jppope 1y ago
The reports from analysis of open source projects are that its something in the range of 10%-15% productivity gains... so it sounds like you're spot on
- smcleod 1y ago
  That's about right for copilots. It's much higher for agentic coding.
  - estomagordo 1y ago
    [citation needed]
    - swader999 1y ago
      Agentic coding had really only taken off in the last few weeks due to better pricing.
datpuz 1y ago
It's just another tech hype wave. Reality will be somewhere between total doom and boundless utopia. But probably neither of those. The AI thing kind of reminds me of the big push to outsource software engineers in the early 2000's. There was a ton of hype among executives about it, and it all seemed plausible on paper. But most of those initiatives ended up being huge failures, and nearly all of those jobs came back to the US. People tend to ignore a lot of the little things that glue it all together that software engineers do. AI lacks a lot of this. Foreigners don't necessarily lack it, but language barriers, time zone differences, cultural differences, and all sorts of other things led to similar issues. Code quality and maintainability took a nosedive and a lot of the stuff produced by those outsourced shops had to be thrown in the trash. I can already see the AI slop accumulating in the codebases I work in. It's super hard to spot a lot of these things that manage to slip through code review, because they tend to look reasonable when you're looking at a diff. The problem is all the redundant code that you're not seeing, and the weird abstractions that make no sense at all when you look at it from a higher level.
- 2muchcoffeeman 1y ago
  This was what I was saying to a friend the other day. I think anyone vaguely competent that is using LLMs will make the technology look far better than it is. Management thinks the LLM is doing most of the work. Work is off shored. Oh, the quality sucks when someone without a clue is driving. We need to hire again.
mlinsey 1y ago
I don't disagree with your assessment of the world today, but just 12 months ago (before the current crop of base models and coding agents like Claude Code), even that 10X improvement of writing some-of-the-code wouldn't have been true.
- __loam 1y ago
  It still isn't.
- timr 1y ago
  > I don't disagree with your assessment of the world today, but just 12 months ago (before the current crop of base models and coding agents like Claude Code), even that 10X improvement of writing some-of-the-code wouldn't have been true. So? It sounds like you're prodding us to make an extrapolation fallacy (I don't even grant the "10x in 12 months" point, but let's just accept the premise for the sake of argument). Honestly, 12 months ago the base models weren't substantially worse than they are right now. Some people will argue with me endlessly on this point, and maybe they're a bit better on the margin, but I think it's pretty much true. When I look at the improvements of the last year with a cold, rational eye, they've been in two major areas: * cost & efficiency * UI & integration So how do we improve from here? Cost & efficiency are the obvious lever with historical precedent: GPUs kinda suck for inference, and costs are (currently) rapidly dropping. But, maybe this won't continue -- algorithmic complexity is what it is, and barring some revolutionary change in the architecture, LLMs are exponential algorithms. UI and integration is where most of the rest of the recent improvement has come from, and honestly, this is pretty close to saturation. All of the various AI products already look the same, and I'm certain that they'll continue to converge to a well-accepted local maxima. After that, huge gains in productivity from UX alone will not be possible. This will happen quickly -- probably in the next year or two. Basically, unless we see a Moore's law of GPUs, I wouldn't bet on indefinite exponential improvement in AI. My bet is that, from here out, this looks like the adoption curve of any prior technology shift (e.g. mainframe -> PC, PC -> laptop, mobile, etc.) where there's a big boom, then a long, slow adoption for the masses.
  - ssk42 1y ago
deadbabe 1y ago
Wait till they hear about the productivity gains from using vim/neovim. Your developers still push a mouse around to get work done? Fire them.
ghuntley 1y ago
Canva has seen a 30% productivity uplift - https://fortune.com/2025/06/25/canva-cto-encourages-all-5000-employees-to-find-the-ai-tools-that-work-best-for-them/ https://fortune.com/2025/06/25/canva-cto-encourages-all-5000... AI is the new uplift. Embrace and adapt, as a rift is forming (see my talk at https://ghuntley.com/six-month-recap/ https://ghuntley.com/six-month-recap/), in what employers seek in terms of skills from employees. I'm happy to answer any questions folks may have. Currently AFK [2] vibecoding a brand new programming language [1]. [1] https://x.com/GeoffreyHuntley/status/1940964118565212606 https://x.com/GeoffreyHuntley/status/1940964118565212606 [2] https://youtu.be/e7i4JEi_8sk?t=29722 https://youtu.be/e7i4JEi_8sk?t=29722
- CuriouslyC 1y ago
  And that's with 50% adoption and probably a broad distribution of tool use skill.
- ofjcihen 1y ago
  There’s something hilariously Portlandia about making outlandish claims with complete confidence and then plugging your own talk.
  - ghuntley 1y ago
    There’s citations to the facts in the links.
- eviks 1y ago
  > The productivity for software engineers is at around 30% That would be a 70% descent?
coolKid721 1y ago
On my personal projects it's easily 10x faster if not more in some circumstances. At work where things are planned out months in advanced and I'm working with 5 different teams to figure out the right way to do things for requirements that change 8 times during development? Even just stuff with PR review and making sure other people understand it and can access it. idk sometimes it's probably break even or that 10-15%. It just doesn't work well in some environments and what really makes it flourish (having super high quality architectural planning/designs/standardized patterns etc.) is basically just not viable at anything but the smallest startups and solo projects. Frankly even just getting engineers to agree upon those super specificized standardized patterns is asking a ton, especially since lots of the things that help AI out are not what they are used to. As soon as you have stuff that starts deviating it can confuse the AI and makes that 10x no longer accessible. Also no one would want to review the PRs I'd make for the changes I do on my "10x" local project... Especially maintaining those standards is already hard enough on my side projects AI will naturally deviate and create noise and the challenge is constructing systems to guide that to make sure nothing deviates (since noise would lead to more noise). I think it's mostly a rebalancing thing, if you have 1 or a couple like minded engineers who intend to do it they can get that 10x. I do not see that EVER existing in any actual corporate environment or even once you get more then like 4 people tbh. Ai for middle management and project planning on the other hand...
abletonlive 1y ago
I’m a tech lead and I have maybe 5X output now compared to everybody else under me. Quantified by scoring tickets at a team level. I also have more responsibilities outside of IC work compared to the people under me. At this point I’m asking my manager to fire people that still think llms are just toys because I’m tired of working with people with this poor mindset. A pragmatic engineer continually reevaluates what they think they know. We are at a tipping point now. I’m done arguing with people that have a poor model of reality. The rest of us are trying to compete and get shit done. This isn’t an opinion or a game. It’s business with real life consequences if you fall behind. I’ve offered to share my workflows, prompts, setup. Guess how many of these engineers have taken me up on my offer. 1-2 and the juniors or ones that are very far behind have not.
- gabrieledarrigo 1y ago
  Dude, if you are a tech lead, and you measure productivity by scoring tickets, you are doing it pretty badly. I would fire you instead.
- dgfitz 1y ago
  I will thank God every day I don’t work with you or for you. How toxic.
  - abletonlive 1y ago
    im glad I don’t have to work with you too lol. It’s not toxic for me to expect someone to get their work done in a reasonable amount of time with the tools available to them. If you’re an accountant and you take 5X the time to do something because you have beef with excel you’re the problem. It’s not toxicity to tell you that you are a bad accountant
    - flextheruler 1y ago
      You believe the cost of firing and rehiring to be cheaper than simple empirical persuasion? You don't sound like a great lead to me, but I suppose you could be working with absolutely incompetent individuals, or perhaps your soft skills need work. My apologies but I see only two possibilities for others not to take the time to follow your example given such strong evidence. They either actively dislike you or are totally incompetent. I find the former more often true than the latter.
TeMPOraL 1y ago
Maybe it's due to a more R&D-ish nature of my current work, but for me, LLMs are delivering just as much gains in the "thinking" part as in "coding" part (I handle the "communicating" thing myself just fine for now). Using LLMs for "thinking" tasks feels similar to how mastering web search 2+ decades ago felt. Search engines enabled access to information provided you know what you're looking for; now LLMs boost that by helping you figure out what you're looking for in the first place (and then conveniently searching it for you, too). This makes trivial some tasks I previously classified as hard due to effort and uncertainty involved. At this point I'd say about 1/3 of my web searches are done through ChatGPT o3, and I can't imagine giving it up now. (There's also a whole psychological angle in how having LLM help sort and rubber-duck your half-baked thought makes many task seem much less daunting, and that alone makes a big difference.)
- jorl17 1y ago
  This, and if you add in a voice mode (e.g. ChatGPT's Advanced Mode), it is perfect for brainstorming. Once I decide I want to "think a problem through with an LLM", I often start with just the voice mode. This forces me to say things out loud — which is remarkably effective (hear hear rubber duck debugging) — and it also gives me a fundamentally different way of consuming the information the LLM provides me. Instead of being delivered a massive amount of text, where some information could be wrong, I instead get a sequential system where I can stop/pause the LLM/redirect it as soon as something gets me curious or as I find problems with it said. You would think that having this way of interacting would be limiting, as having a fast LLM output large chunks of information would let you skim through it and commit it to memory faster. Yet, for me, the combination of hearing things and, most of all, not having to consume so much potentially wrong info (what good is it to skim pointless stuff), ensures that ChatGPT's Advanced Voice mode is a great way to initially approach a problem. After the first round with the voice mode is done, I often move to written-form brainstorming.
  - adi_kurian 1y ago
    This 100%. Though think there is a personality component to this. At least I think when I speak.
doug_durham 1y ago
How much of the communication and meetings are because traditionally code was very expensive and slow to create? How many of those meetings might be streamlined or entirely disappear in the future? In my experience there is are a lot of process around making sure that software on schedule track and that it's doing what it is supposed to do. I think that the software lifecycle is about to be reinvented.
thunky 1y ago
> One thing I find frustrating is that management where I work has heard of 10x productivity gains. That may also be in part because llms are not as big of an accelerant for junior devs as they are for seniors (juniors don't know what is good and bad as well). So if you give 1 senior dev a souped up llm workflow I wouldn't be too surprised if they are as productive as 10 pre-llm juniors. Maybe even more, because a bad dev can actually produce negative productivity (stealing from the senior), in which case it's infinityx. Even a decent junior is mostly limited to doing the low level grunt work, which llms can already do better. Point is, I can see how jobs could be lost, legitimately.
- Loughla 1y ago
  The item lost is pipeline of talent in all of this though. Precision machining is going through an absolute nightmare where the journeymen or master machinists are aging out of the work force. These were people who originally learned on manual machines, and upgraded to CNC over the years. The pipeline collapsed about 1997. Now there are no apprentice machinists to replace the skills of the retiring workforce. This will happen to software developers. Probably faster because they tend to be financially independent WAY sooner than machinists.
  - thunky 1y ago
    > The item lost is pipeline of talent in all of this though. Totally agree. However, I think this pipeline has been taking a hit for a while already because juniors as a whole have been devaluing themselves: if we expect them to leave after one year, what's the point of hiring and training them? Only helping their next employer at that point.
    - deleted 1y ago
      [deleted]
    - hobs 1y ago
      That old canard? If you pay people in a way that incentivizes them to stay, they will. If you train people and treat them right and pay them right, they wont leave. If they are, try to fix one of those things, stop blaming the juniors for their massive collusion in a market where they literally are struggling to get jobs.
ericmcer 1y ago
Its great when they use AI to write a small app “without coding at all” over the weekend and then come in on Monday to brag about it and act baffled that tasks take engineers any time at all.
tom_m 1y ago
Expectations are absolutely way too high. It's going to lead to a lot of toxicity and people being fired. It's really going to suck.

louthy 1y ago

> overall my productivity is 10-15% better. That is nothing to sneeze at, but it isn't 10x. It is something to sneeze at if you are 10-15% more expensive to employ due to the cost of the LLM tools. The total cost of production should always be considered, not just throughput.

bravesoul2 1y ago
That's a good insight be because with perfect competition it means you need to share your old salary with an LLM!
votepaunchy 1y ago
> if you are 10-15% more expensive to employ due to the cost of the LLM tools How is one spending anywhere close to 10% of total compensation on LLMs?
CharlesW 1y ago
> It is something to sneeze at if you are 10-15% more expensive to employ due to the cost of the LLM tools. Claude Max is $200/month, or ~2% of the salary of an average software engineer.
- m4rtink 1y ago
  Does anyone actually know what the real cost for the customers will be once the free AI money no longer floods those companies?
  - wubrr 1y ago
    I'm no LLM evangelist, far from it, but I expect models of similar quality to the current bleeding-edge, will be freely runnable on consumer hardware within 3 years. Future bleeding-edge models may well be more expensive than current ones, who knows.
    - ls612 1y ago
      How do the best models that can run on say a single 4090 today compare to GPT 3.5?
      - electroglyph 1y ago
        Qwen 2.5 32B which is an older model at this point clearly outperforms it: https://llm-stats.com/models/compare/gpt-3.5-turbo-0125-vs-qwen-2.5-32b-instruct https://llm-stats.com/models/compare/gpt-3.5-turbo-0125-vs-q...
        ls612 1y ago
        Even when quantized down to 4 bits to fit on a 4090?
        FuckButtons 1y ago
        Not in my experience, running qwen3:32b is good, but it’s not as coherent or useful as 3.5 at a 4bit quant. But the gap is a lot narrower than llama 70b.
    - TeMPOraL 1y ago
      For the purpose of keeping the costs of LLM-dependent services down, you don't need to run bleeding-edge models on single consumer GPUs. Even if it takes a hundred GPUs, it still means people can start businesses around hosting those models, and compete with the large vendors.
  - jppope 1y ago
    yeah there was an analysis that came out on hackernews the other day. between low demand side economics, virtually no impact to GDP, and corporate/vc subsidies going away soon we're close to finding out. Sam Altman did convince Softbank to do a 40B round though so it might be another year or two. Current estimates are that its cheaper than search to run so its probabilistic that there will be more search features swapped. OpenAi hasn't dropped their ad platform yet though, so interested to see how that goes
- selfhoster11 1y ago
  In the US, maybe. Several times that by percentage in other places around the world.
- GeoAtreides 1y ago
  the average software engineer makes $10000 a month after taxes?!

wubrr 1y ago

> One thing I find frustrating is that management where I work has heard of 10x productivity gains. Some of those claims even come from early adopters at my work. Similar situation at my work, but all of the productivity claims from internal early adopters I've seen so far are based on very narrow ways of measuring productivity, and very sketchy math, to put it mildly.

jppope 1y ago

The reports from analysis of open source projects are that its something in the range of 10%-15% productivity gains... so it sounds like you're spot on

smcleod 1y ago
That's about right for copilots. It's much higher for agentic coding.
- estomagordo 1y ago
  [citation needed]
  - swader999 1y ago
    Agentic coding had really only taken off in the last few weeks due to better pricing.

datpuz 1y ago

It's just another tech hype wave. Reality will be somewhere between total doom and boundless utopia. But probably neither of those. The AI thing kind of reminds me of the big push to outsource software engineers in the early 2000's. There was a ton of hype among executives about it, and it all seemed plausible on paper. But most of those initiatives ended up being huge failures, and nearly all of those jobs came back to the US. People tend to ignore a lot of the little things that glue it all together that software engineers do. AI lacks a lot of this. Foreigners don't necessarily lack it, but language barriers, time zone differences, cultural differences, and all sorts of other things led to similar issues. Code quality and maintainability took a nosedive and a lot of the stuff produced by those outsourced shops had to be thrown in the trash. I can already see the AI slop accumulating in the codebases I work in. It's super hard to spot a lot of these things that manage to slip through code review, because they tend to look reasonable when you're looking at a diff. The problem is all the redundant code that you're not seeing, and the weird abstractions that make no sense at all when you look at it from a higher level.

2muchcoffeeman 1y ago
This was what I was saying to a friend the other day. I think anyone vaguely competent that is using LLMs will make the technology look far better than it is. Management thinks the LLM is doing most of the work. Work is off shored. Oh, the quality sucks when someone without a clue is driving. We need to hire again.

mlinsey 1y ago

I don't disagree with your assessment of the world today, but just 12 months ago (before the current crop of base models and coding agents like Claude Code), even that 10X improvement of writing some-of-the-code wouldn't have been true.

__loam 1y ago
It still isn't.
timr 1y ago
> I don't disagree with your assessment of the world today, but just 12 months ago (before the current crop of base models and coding agents like Claude Code), even that 10X improvement of writing some-of-the-code wouldn't have been true. So? It sounds like you're prodding us to make an extrapolation fallacy (I don't even grant the "10x in 12 months" point, but let's just accept the premise for the sake of argument). Honestly, 12 months ago the base models weren't substantially worse than they are right now. Some people will argue with me endlessly on this point, and maybe they're a bit better on the margin, but I think it's pretty much true. When I look at the improvements of the last year with a cold, rational eye, they've been in two major areas: * cost & efficiency * UI & integration So how do we improve from here? Cost & efficiency are the obvious lever with historical precedent: GPUs kinda suck for inference, and costs are (currently) rapidly dropping. But, maybe this won't continue -- algorithmic complexity is what it is, and barring some revolutionary change in the architecture, LLMs are exponential algorithms. UI and integration is where most of the rest of the recent improvement has come from, and honestly, this is pretty close to saturation. All of the various AI products already look the same, and I'm certain that they'll continue to converge to a well-accepted local maxima. After that, huge gains in productivity from UX alone will not be possible. This will happen quickly -- probably in the next year or two. Basically, unless we see a Moore's law of GPUs, I wouldn't bet on indefinite exponential improvement in AI. My bet is that, from here out, this looks like the adoption curve of any prior technology shift (e.g. mainframe -> PC, PC -> laptop, mobile, etc.) where there's a big boom, then a long, slow adoption for the masses.
- ssk42 1y ago

deadbabe 1y ago

Wait till they hear about the productivity gains from using vim/neovim. Your developers still push a mouse around to get work done? Fire them.

ghuntley 1y ago

Canva has seen a 30% productivity uplift - https://fortune.com/2025/06/25/canva-cto-encourages-all-5000-employees-to-find-the-ai-tools-that-work-best-for-them/ https://fortune.com/2025/06/25/canva-cto-encourages-all-5000... AI is the new uplift. Embrace and adapt, as a rift is forming (see my talk at https://ghuntley.com/six-month-recap/ https://ghuntley.com/six-month-recap/), in what employers seek in terms of skills from employees. I'm happy to answer any questions folks may have. Currently AFK [2] vibecoding a brand new programming language [1]. [1] https://x.com/GeoffreyHuntley/status/1940964118565212606 https://x.com/GeoffreyHuntley/status/1940964118565212606 [2] https://youtu.be/e7i4JEi_8sk?t=29722 https://youtu.be/e7i4JEi_8sk?t=29722

CuriouslyC 1y ago
And that's with 50% adoption and probably a broad distribution of tool use skill.
ofjcihen 1y ago
There’s something hilariously Portlandia about making outlandish claims with complete confidence and then plugging your own talk.
- ghuntley 1y ago
  There’s citations to the facts in the links.
eviks 1y ago
> The productivity for software engineers is at around 30% That would be a 70% descent?

coolKid721 1y ago

On my personal projects it's easily 10x faster if not more in some circumstances. At work where things are planned out months in advanced and I'm working with 5 different teams to figure out the right way to do things for requirements that change 8 times during development? Even just stuff with PR review and making sure other people understand it and can access it. idk sometimes it's probably break even or that 10-15%. It just doesn't work well in some environments and what really makes it flourish (having super high quality architectural planning/designs/standardized patterns etc.) is basically just not viable at anything but the smallest startups and solo projects. Frankly even just getting engineers to agree upon those super specificized standardized patterns is asking a ton, especially since lots of the things that help AI out are not what they are used to. As soon as you have stuff that starts deviating it can confuse the AI and makes that 10x no longer accessible. Also no one would want to review the PRs I'd make for the changes I do on my "10x" local project... Especially maintaining those standards is already hard enough on my side projects AI will naturally deviate and create noise and the challenge is constructing systems to guide that to make sure nothing deviates (since noise would lead to more noise). I think it's mostly a rebalancing thing, if you have 1 or a couple like minded engineers who intend to do it they can get that 10x. I do not see that EVER existing in any actual corporate environment or even once you get more then like 4 people tbh. Ai for middle management and project planning on the other hand...

abletonlive 1y ago

I’m a tech lead and I have maybe 5X output now compared to everybody else under me. Quantified by scoring tickets at a team level. I also have more responsibilities outside of IC work compared to the people under me. At this point I’m asking my manager to fire people that still think llms are just toys because I’m tired of working with people with this poor mindset. A pragmatic engineer continually reevaluates what they think they know. We are at a tipping point now. I’m done arguing with people that have a poor model of reality. The rest of us are trying to compete and get shit done. This isn’t an opinion or a game. It’s business with real life consequences if you fall behind. I’ve offered to share my workflows, prompts, setup. Guess how many of these engineers have taken me up on my offer. 1-2 and the juniors or ones that are very far behind have not.

gabrieledarrigo 1y ago
Dude, if you are a tech lead, and you measure productivity by scoring tickets, you are doing it pretty badly. I would fire you instead.
dgfitz 1y ago
I will thank God every day I don’t work with you or for you. How toxic.
- abletonlive 1y ago
  im glad I don’t have to work with you too lol. It’s not toxic for me to expect someone to get their work done in a reasonable amount of time with the tools available to them. If you’re an accountant and you take 5X the time to do something because you have beef with excel you’re the problem. It’s not toxicity to tell you that you are a bad accountant
  - flextheruler 1y ago
    You believe the cost of firing and rehiring to be cheaper than simple empirical persuasion? You don't sound like a great lead to me, but I suppose you could be working with absolutely incompetent individuals, or perhaps your soft skills need work. My apologies but I see only two possibilities for others not to take the time to follow your example given such strong evidence. They either actively dislike you or are totally incompetent. I find the former more often true than the latter.

TeMPOraL 1y ago

Maybe it's due to a more R&D-ish nature of my current work, but for me, LLMs are delivering just as much gains in the "thinking" part as in "coding" part (I handle the "communicating" thing myself just fine for now). Using LLMs for "thinking" tasks feels similar to how mastering web search 2+ decades ago felt. Search engines enabled access to information provided you know what you're looking for; now LLMs boost that by helping you figure out what you're looking for in the first place (and then conveniently searching it for you, too). This makes trivial some tasks I previously classified as hard due to effort and uncertainty involved. At this point I'd say about 1/3 of my web searches are done through ChatGPT o3, and I can't imagine giving it up now. (There's also a whole psychological angle in how having LLM help sort and rubber-duck your half-baked thought makes many task seem much less daunting, and that alone makes a big difference.)

jorl17 1y ago
This, and if you add in a voice mode (e.g. ChatGPT's Advanced Mode), it is perfect for brainstorming. Once I decide I want to "think a problem through with an LLM", I often start with just the voice mode. This forces me to say things out loud — which is remarkably effective (hear hear rubber duck debugging) — and it also gives me a fundamentally different way of consuming the information the LLM provides me. Instead of being delivered a massive amount of text, where some information could be wrong, I instead get a sequential system where I can stop/pause the LLM/redirect it as soon as something gets me curious or as I find problems with it said. You would think that having this way of interacting would be limiting, as having a fast LLM output large chunks of information would let you skim through it and commit it to memory faster. Yet, for me, the combination of hearing things and, most of all, not having to consume so much potentially wrong info (what good is it to skim pointless stuff), ensures that ChatGPT's Advanced Voice mode is a great way to initially approach a problem. After the first round with the voice mode is done, I often move to written-form brainstorming.
- adi_kurian 1y ago
  This 100%. Though think there is a personality component to this. At least I think when I speak.

doug_durham 1y ago

How much of the communication and meetings are because traditionally code was very expensive and slow to create? How many of those meetings might be streamlined or entirely disappear in the future? In my experience there is are a lot of process around making sure that software on schedule track and that it's doing what it is supposed to do. I think that the software lifecycle is about to be reinvented.

thunky 1y ago

> One thing I find frustrating is that management where I work has heard of 10x productivity gains. That may also be in part because llms are not as big of an accelerant for junior devs as they are for seniors (juniors don't know what is good and bad as well). So if you give 1 senior dev a souped up llm workflow I wouldn't be too surprised if they are as productive as 10 pre-llm juniors. Maybe even more, because a bad dev can actually produce negative productivity (stealing from the senior), in which case it's infinityx. Even a decent junior is mostly limited to doing the low level grunt work, which llms can already do better. Point is, I can see how jobs could be lost, legitimately.

Loughla 1y ago
The item lost is pipeline of talent in all of this though. Precision machining is going through an absolute nightmare where the journeymen or master machinists are aging out of the work force. These were people who originally learned on manual machines, and upgraded to CNC over the years. The pipeline collapsed about 1997. Now there are no apprentice machinists to replace the skills of the retiring workforce. This will happen to software developers. Probably faster because they tend to be financially independent WAY sooner than machinists.
- thunky 1y ago
  > The item lost is pipeline of talent in all of this though. Totally agree. However, I think this pipeline has been taking a hit for a while already because juniors as a whole have been devaluing themselves: if we expect them to leave after one year, what's the point of hiring and training them? Only helping their next employer at that point.
  - deleted 1y ago
    [deleted]
  - hobs 1y ago
    That old canard? If you pay people in a way that incentivizes them to stay, they will. If you train people and treat them right and pay them right, they wont leave. If they are, try to fix one of those things, stop blaming the juniors for their massive collusion in a market where they literally are struggling to get jobs.

ericmcer 1y ago

Its great when they use AI to write a small app “without coding at all” over the weekend and then come in on Monday to brag about it and act baffled that tasks take engineers any time at all.

tom_m 1y ago

Expectations are absolutely way too high. It's going to lead to a lot of toxicity and people being fired. It's really going to suck.