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>But all now seems like a transition phase. Transition to f-ing what though? It feels like being in the middle of a tornado. But I think it helps to turn off s

>But all now seems like a transition phase. Transition to f-ing what though? It feels like being in the middle of a tornado. But I think it helps to turn off screens, sit in a desk, and calmly remember first principles and consider them slowly. Quoting obama, "reality has a way of catching up with you". I see a lot of talk, but iOS is not delivering a decade of features and fixes on each yearly release. Literally no one does, if anything people are complaining that existing functionality is breaking down. So it can't be true that we're at 10x productivity, and this fact will eventually catch up with us. Let's be human, and remember that many people are emotionally invested. Juniors want this to be a chance to shine in a market that otherwise rejected them. CEOs placed their bet on AI and don't want to walk that back. Seniors want to signal that they are not obsolete. AI companies will poison discourse. But all this smoke will eventually clear.

patates 4mo ago
> Juniors want this to be a chance to shine in a market that otherwise rejected them. I actually am training 2 trainees (Azubi in German) and 1 working student. All three are somewhat anxious about the future but also all are learning in a significantly increased pace, compared to the ones I worked with 1.5 years ago. They don't have to wait for random senior to answer questions, so they get stuck way less often. They aren't allowed to use AI to generate code though, so not sure how that'd look like learning-wise if we/they went all-in on AI.
- runarberg 4mo ago
  I am skeptical. This is a testable hypothesis, and I know there have been tons of research done trying to provide evidence of claims like these. However I have yet to see a convincing evidence. If this statement was indeed true, I think experimental data backing it up would be old news at this point, it however is not, and I suspect that is because junior developers are by and large in fact not learning faster or more with the help of AI.
- leononame 4mo ago
  Is that a good thing? I think getting stuck is an intrinsic part of the learning process and sometimes it's good that there isn't an immediate answer from a senior. For some things you'd never have solved yourself, sure. But pain and suffering is a big and important chunk of learning and I fear we just throw it all out of the window with asking AI.
thedevilslawyer 4mo ago
I sense your comment as saying: "AI is hype, and reality will catch-up.". But the simple fact is there's massive evidence that in skilled hands 10x or 100x engineers are possible. We're seeing evidence of it across major open source project as well. And definitely behind closed doors across companies. Reality will catch-up with that too, once the other smoke clears.
- shinryuu 4mo ago
  100x is achieving something in two days, what it took an entire year before. I strongly doubt that is happening for an individual.
  - mistersquid 4mo ago
    > 100x is achieving something in two days, what it took an entire year before. Reduce your scale: "100x achieves in 1 hour what used to take 1 week." One year of work could require levels of complexity and human judgement that can't be accelerated past a certain point. 1 week of work can be reduced to an hour and some change.
    - shinryuu 4mo ago
      That requires that you not only one-shot the thing. You will also not have the time to verify the solution yourself in that time period. Besides 1h what used to to take 1 week is basically 40x given a workweek is 40h.
    - ruszki 4mo ago
      That’s also not possible in “skilled” hands. My output is roughly the same. It does the scaffolding, but I need to rewrite almost every line, because it introduces footguns around that often. And before I had about 20000 LOC it failed even with scaffolding, ie architecture. And it wasn’t taste, just footguns all around, architecture ones. Nowadays for example still introduce mutability or completely unnecessary complexity where it shouldn’t, even when the example code which does almost the same is pristine. Many times it’s like StackOverflow, when a question doesn’t need 90% of the accepted answer, but people happily copy it brainlessly. This is especially bad with new, or quickly improving frameworks, like Android Compose. LLMs use completely outdated, deprecated APIs all the time, when they are not completely supervised. Or at least, I hope so that the framework causes it. Because if that’s not the case, then your products are fucked. Also even with the best prompts it could never produce more working code in an hour than what I can produce in a day. Regardless of quality, just “working somehow”. Not even with an uninterrupted session. If that’s the case for some, then there is definitely also a developer skill issue. And so would definitely not trust anything coming out of their “supervision” of an LLM.
Folcon 4mo ago
I've been thinking a fair bit about what I'm seeing in terms of the output I experience It's quite hard to quantify, but I think it's one shot nature really makes it hard to gauge it's capability Friends have spoken of good days and bad coding days with me, and I find it odd nodding along, it's a strange new normal At times it feels like we're just coding with one-armed bandits, trying to carefully line them up for a jackpot and just discarding and retrying if we don't hit I think about some of the more complex systems I've built and I wonder how well we can build them like this And over engineering, there seems to be over engineering everywhere, and yet, more fragility to our systems It's all a little surreal
- customguy 4mo ago
  I imagine this stuff is probably really good at iterative changes to improve objective benchmarks like CPU or RAM use. I'm thinking of little contained optimizations that you can understand in and of themselves, that you maybe have done yourself before in other places, found really quickly and applied uniformly. Stuff you can confirm to be what you expect it to be by mostly just scanning. Low hanging fruit for sure, but something where you can actually know what is a fruit and what is crap, and only keep the fruit, and develop some confidence in the process, if that makes sense? Or trying to reduce complexity, increasing readability and coherence of variable names (the opposite of code golf if you will), while staying within a certain limit of performance regression (e.g. "make this code as nice as you can while making it at most 0.5% slower"). Making the stuff millions of people have been using for decades better, in a way that also makes it better for humans when they read the code. Surely that's possible, some people are probably doing it but it doesn't go viral as much, because it's too mundane. And of course, making new stuff is more exciting. I mean, you could hit on something with a vibe coded thing, and then know it's now worth to make a non-sloppy version, but you won't get much fame for making ffmpeg twice as fast by prompting an LLM. Though on the other hand, it's like a safe investment (if not in "fame", then in "improving the stuff we all have to use daily"), because you know ffmpeg and many many other things will still be around, whereas a vibe coded thing that wasn't special will be 100% forgotten the next day, or have just the one user forever.
kibwen 4mo ago
> But all this smoke will eventually clear. I wish I could be so optimistic. Our lives are ruled by distorted, irrational, inefficient, failed markets, and the markets can remain distorted, irrational, inefficient, and failed for longer than we as individuals can remain solvent. "In the long term the market is a weighing machine", for term lengths that include the heat death of the universe.
abustamam 4mo ago
> iOS is not delivering a decade of features and fixes on each yearly release This is insinuating that code was the bottleneck in the first place, or that every line of code is to build a new feature and not fixing existing bugs, or that apple didn't lay off enough engineers and reallocate resources to other departments to make up for the productivity boost. I do think that companies with poor AI practices will eventually pay the piper in the form of technical debt or debilitating bugs. But let's not equate a productivity boost with a boost in releasing features, because there's plenty of business reasons to not release thousands of new features every year. I agree with you on the rest of your points. Eventually the smoke will clear. What awaits to be seen is who is left standing when it does? I don't think I like the answer to that question.
sph 4mo ago
> It feels like being in the middle of a tornado. But I think it helps to turn off screens, sit in a desk, and calmly remember first principles and consider them slowly. It’s been enormously alienating talking to laypeople about the apocalyptic atmosphere in the tech world, while for them ChatGPT is a cool piece of software but the world still hasn’t changed very much. They look at me bug eyed when I tell them how dramatically software engineering has changed in the matter of a couple years. We are in a bubble, or we’re just, as you say, in the eye of the cyclone which still has to hit the rest of the world.

patates 4mo ago

> Juniors want this to be a chance to shine in a market that otherwise rejected them. I actually am training 2 trainees (Azubi in German) and 1 working student. All three are somewhat anxious about the future but also all are learning in a significantly increased pace, compared to the ones I worked with 1.5 years ago. They don't have to wait for random senior to answer questions, so they get stuck way less often. They aren't allowed to use AI to generate code though, so not sure how that'd look like learning-wise if we/they went all-in on AI.

runarberg 4mo ago
I am skeptical. This is a testable hypothesis, and I know there have been tons of research done trying to provide evidence of claims like these. However I have yet to see a convincing evidence. If this statement was indeed true, I think experimental data backing it up would be old news at this point, it however is not, and I suspect that is because junior developers are by and large in fact not learning faster or more with the help of AI.
leononame 4mo ago
Is that a good thing? I think getting stuck is an intrinsic part of the learning process and sometimes it's good that there isn't an immediate answer from a senior. For some things you'd never have solved yourself, sure. But pain and suffering is a big and important chunk of learning and I fear we just throw it all out of the window with asking AI.

thedevilslawyer 4mo ago

I sense your comment as saying: "AI is hype, and reality will catch-up.". But the simple fact is there's massive evidence that in skilled hands 10x or 100x engineers are possible. We're seeing evidence of it across major open source project as well. And definitely behind closed doors across companies. Reality will catch-up with that too, once the other smoke clears.

shinryuu 4mo ago
100x is achieving something in two days, what it took an entire year before. I strongly doubt that is happening for an individual.
- mistersquid 4mo ago
  > 100x is achieving something in two days, what it took an entire year before. Reduce your scale: "100x achieves in 1 hour what used to take 1 week." One year of work could require levels of complexity and human judgement that can't be accelerated past a certain point. 1 week of work can be reduced to an hour and some change.
  - shinryuu 4mo ago
    That requires that you not only one-shot the thing. You will also not have the time to verify the solution yourself in that time period. Besides 1h what used to to take 1 week is basically 40x given a workweek is 40h.
  - ruszki 4mo ago
    That’s also not possible in “skilled” hands. My output is roughly the same. It does the scaffolding, but I need to rewrite almost every line, because it introduces footguns around that often. And before I had about 20000 LOC it failed even with scaffolding, ie architecture. And it wasn’t taste, just footguns all around, architecture ones. Nowadays for example still introduce mutability or completely unnecessary complexity where it shouldn’t, even when the example code which does almost the same is pristine. Many times it’s like StackOverflow, when a question doesn’t need 90% of the accepted answer, but people happily copy it brainlessly. This is especially bad with new, or quickly improving frameworks, like Android Compose. LLMs use completely outdated, deprecated APIs all the time, when they are not completely supervised. Or at least, I hope so that the framework causes it. Because if that’s not the case, then your products are fucked. Also even with the best prompts it could never produce more working code in an hour than what I can produce in a day. Regardless of quality, just “working somehow”. Not even with an uninterrupted session. If that’s the case for some, then there is definitely also a developer skill issue. And so would definitely not trust anything coming out of their “supervision” of an LLM.

Folcon 4mo ago

I've been thinking a fair bit about what I'm seeing in terms of the output I experience It's quite hard to quantify, but I think it's one shot nature really makes it hard to gauge it's capability Friends have spoken of good days and bad coding days with me, and I find it odd nodding along, it's a strange new normal At times it feels like we're just coding with one-armed bandits, trying to carefully line them up for a jackpot and just discarding and retrying if we don't hit I think about some of the more complex systems I've built and I wonder how well we can build them like this And over engineering, there seems to be over engineering everywhere, and yet, more fragility to our systems It's all a little surreal

customguy 4mo ago
I imagine this stuff is probably really good at iterative changes to improve objective benchmarks like CPU or RAM use. I'm thinking of little contained optimizations that you can understand in and of themselves, that you maybe have done yourself before in other places, found really quickly and applied uniformly. Stuff you can confirm to be what you expect it to be by mostly just scanning. Low hanging fruit for sure, but something where you can actually know what is a fruit and what is crap, and only keep the fruit, and develop some confidence in the process, if that makes sense? Or trying to reduce complexity, increasing readability and coherence of variable names (the opposite of code golf if you will), while staying within a certain limit of performance regression (e.g. "make this code as nice as you can while making it at most 0.5% slower"). Making the stuff millions of people have been using for decades better, in a way that also makes it better for humans when they read the code. Surely that's possible, some people are probably doing it but it doesn't go viral as much, because it's too mundane. And of course, making new stuff is more exciting. I mean, you could hit on something with a vibe coded thing, and then know it's now worth to make a non-sloppy version, but you won't get much fame for making ffmpeg twice as fast by prompting an LLM. Though on the other hand, it's like a safe investment (if not in "fame", then in "improving the stuff we all have to use daily"), because you know ffmpeg and many many other things will still be around, whereas a vibe coded thing that wasn't special will be 100% forgotten the next day, or have just the one user forever.

kibwen 4mo ago

> But all this smoke will eventually clear. I wish I could be so optimistic. Our lives are ruled by distorted, irrational, inefficient, failed markets, and the markets can remain distorted, irrational, inefficient, and failed for longer than we as individuals can remain solvent. "In the long term the market is a weighing machine", for term lengths that include the heat death of the universe.

abustamam 4mo ago

> iOS is not delivering a decade of features and fixes on each yearly release This is insinuating that code was the bottleneck in the first place, or that every line of code is to build a new feature and not fixing existing bugs, or that apple didn't lay off enough engineers and reallocate resources to other departments to make up for the productivity boost. I do think that companies with poor AI practices will eventually pay the piper in the form of technical debt or debilitating bugs. But let's not equate a productivity boost with a boost in releasing features, because there's plenty of business reasons to not release thousands of new features every year. I agree with you on the rest of your points. Eventually the smoke will clear. What awaits to be seen is who is left standing when it does? I don't think I like the answer to that question.

sph 4mo ago

> It feels like being in the middle of a tornado. But I think it helps to turn off screens, sit in a desk, and calmly remember first principles and consider them slowly. It’s been enormously alienating talking to laypeople about the apocalyptic atmosphere in the tech world, while for them ChatGPT is a cool piece of software but the world still hasn’t changed very much. They look at me bug eyed when I tell them how dramatically software engineering has changed in the matter of a couple years. We are in a bubble, or we’re just, as you say, in the eye of the cyclone which still has to hit the rest of the world.