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Something I've been thinking about is that most claims of AI productivity apply just as well (and more concretely and reliably) to just... better tooling and ab

Something I've been thinking about is that most claims of AI productivity apply just as well (and more concretely and reliably) to just... better tooling and abstractions Code already lets us automate work away! I can stamp out ten instances of a component or call a function ten times and cut my manual labor by 90% I'm not saying AI has nothing to add, but the "assembly line" analogies - where we precisely factor out mundane parts of the process to be automated - is what we've been doing this whole time AI demands a whole other analogy. The intuitions from automating factories really don't apply, imo. Here's one candidate: AI is like gaining access to a huge pool of cheap labor, doing tasks that don't lend themselves to normal automation. Something like when manufacturing got offshored to China in the late 20th century If you're chronically doing something mundane in software development, you're doing something wrong. That was true even before AI.

fhd2 1y ago
100%. I keep thinking this, and sometimes saying it. Sure, if you're stuck in a horrible legacy code base, it's harder. But you can _still_ automate tedious work, given you can manage to put in the proverbial stop for gas. I've seen loads of developers just happily copy paste things together, not stopping to wonder if it was perhaps time to refactor.
Cthulhu_ 1y ago
Exactly that. Software development isn't about writing code, never was, it's about what code to write. Doesn't matter if I type in the code or tell an AI what code it should type. I'll admit that assuming it's correct, an AI can type faster than me. But time spent typing represents only a fraction of the software development cycle. But, it'll take another year or two on the hype cycle for the gullible managers being sold AI to realise this fully.
- fhd2 1y ago
  Worse: If typing in code takes more time (i.e. costs more), there's a larger incentive to refactor. I spent quite a bit of time as a CTO, and at some point there's a conversation about the business value of refactoring. That's a great conversation to have I think, it should ultimately be about business value, but good code vs bad code is a bit hard to quantify. What I usually reached for is that refactoring brings down lead time of changes, i.e. makes them faster. Tougher story these days I guess :D
- sanderjd 1y ago
  I've been telling friends and family - and kids interested in going entering this field - this for years (decades actually, at this point), that I don't spend much of my time typing out code. I've found that it's very hard for people to conceptualize what else it would be that we're spending our time doing.
  - skydhash 1y ago
    I think that's a good part of the issue. You have the computer that is doing stuff. And you have the software engineer that was hired to make it do the stuff. And the connection between them is the code. That's pretty much the simplistic picture that everyone has. But the truth is that the way the computer works is alien and anything useful becomes very complex. So we've come up with all those abstractions, embed them in programming languages with which we create more abstractions trying to satisfy real world constraints. It's an imaginary world which is very hard to depict to other people. It's not purely abstract like mathematics, nor it's fully physical like mechanics. The issue with LLMs is whatever they produce have a great chance of being distorted. At first glance, it looks like it's being correct, but the more you add to it, the more visible the flaws are until you're left with a Frankenstein monster.
    - sanderjd 1y ago
      Yep, well put. But to your last part, this is why I think the worst fears I see from programmers (here and in real life) are unlikely to be a lasting problem. If you're right - and I think you are - that the direction things may be headed as-is, with increasingly less sophisticated people relying increasingly more on AIs to build an increasingly large portion of software, is going to result in big messes of unworkable software. But if so, people are going to get wise to that, and stop doing it. It won't be tenable for companies to go to market with "Frankenstein monsters", in the long term. The key is to look through the tumultuous phase and figure out what it's gonna look like after that. Of course this is a very hard thing to predict! But here are the outcomes I personally put the most weight on: 1. AIs might really get good enough that none of us write code anymore, in the same way that it's quite rare to write assembly code now. In this case, I think entrepreneurship or research will be the way to go. We'll be able to do so much more if software is truly easy to create! 2. We're still writing, editing, and debugging code artifacts, but with much better tools. In this case, I think actually understanding how software works will be a very valuable skill, as knocking out subtly broken software will be a dime a dozen, while getting things working well will be a differentiator. Honestly I don't put much weight on the version of this where nobody is doing anything because AI is running everything. I recognize that lots of smart people disagree with me about this, but I remain skeptical.

fhd2 1y ago

100%. I keep thinking this, and sometimes saying it. Sure, if you're stuck in a horrible legacy code base, it's harder. But you can _still_ automate tedious work, given you can manage to put in the proverbial stop for gas. I've seen loads of developers just happily copy paste things together, not stopping to wonder if it was perhaps time to refactor.

Cthulhu_ 1y ago

Exactly that. Software development isn't about writing code, never was, it's about what code to write. Doesn't matter if I type in the code or tell an AI what code it should type. I'll admit that assuming it's correct, an AI can type faster than me. But time spent typing represents only a fraction of the software development cycle. But, it'll take another year or two on the hype cycle for the gullible managers being sold AI to realise this fully.

fhd2 1y ago
Worse: If typing in code takes more time (i.e. costs more), there's a larger incentive to refactor. I spent quite a bit of time as a CTO, and at some point there's a conversation about the business value of refactoring. That's a great conversation to have I think, it should ultimately be about business value, but good code vs bad code is a bit hard to quantify. What I usually reached for is that refactoring brings down lead time of changes, i.e. makes them faster. Tougher story these days I guess :D
sanderjd 1y ago
I've been telling friends and family - and kids interested in going entering this field - this for years (decades actually, at this point), that I don't spend much of my time typing out code. I've found that it's very hard for people to conceptualize what else it would be that we're spending our time doing.
- skydhash 1y ago
  I think that's a good part of the issue. You have the computer that is doing stuff. And you have the software engineer that was hired to make it do the stuff. And the connection between them is the code. That's pretty much the simplistic picture that everyone has. But the truth is that the way the computer works is alien and anything useful becomes very complex. So we've come up with all those abstractions, embed them in programming languages with which we create more abstractions trying to satisfy real world constraints. It's an imaginary world which is very hard to depict to other people. It's not purely abstract like mathematics, nor it's fully physical like mechanics. The issue with LLMs is whatever they produce have a great chance of being distorted. At first glance, it looks like it's being correct, but the more you add to it, the more visible the flaws are until you're left with a Frankenstein monster.
  - sanderjd 1y ago
    Yep, well put. But to your last part, this is why I think the worst fears I see from programmers (here and in real life) are unlikely to be a lasting problem. If you're right - and I think you are - that the direction things may be headed as-is, with increasingly less sophisticated people relying increasingly more on AIs to build an increasingly large portion of software, is going to result in big messes of unworkable software. But if so, people are going to get wise to that, and stop doing it. It won't be tenable for companies to go to market with "Frankenstein monsters", in the long term. The key is to look through the tumultuous phase and figure out what it's gonna look like after that. Of course this is a very hard thing to predict! But here are the outcomes I personally put the most weight on: 1. AIs might really get good enough that none of us write code anymore, in the same way that it's quite rare to write assembly code now. In this case, I think entrepreneurship or research will be the way to go. We'll be able to do so much more if software is truly easy to create! 2. We're still writing, editing, and debugging code artifacts, but with much better tools. In this case, I think actually understanding how software works will be a very valuable skill, as knocking out subtly broken software will be a dime a dozen, while getting things working well will be a differentiator. Honestly I don't put much weight on the version of this where nobody is doing anything because AI is running everything. I recognize that lots of smart people disagree with me about this, but I remain skeptical.