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> In my experience, AI really lowered the bar for bad code in the name of delivering faster. I would've believed that 6 months ago, but not now. If you have a

> In my experience, AI really lowered the bar for bad code in the name of delivering faster. I would've believed that 6 months ago, but not now. If you have a good codebase with proper rails, hygiene and architecture, AI will produce better code than most engineers out there. People forget that 90% of the field has always been charlatans barely able to implement a fizz buzz or go much beyond trial and error googling. I'll say even more. I'm in the 10%, and it's increasingly clear to me that AI writes in minutes code that's better than mine. Even stellar and respected OSS engineers are nowadays leveraging AI and guiding it less and less everyday beyond giving indications of what kind of data structure they may want for a complex problem or the kind of architecture they are looking for. In any case, I don't like this field anymore, I have no joy from it, way too much work, way too many changes a human can cope with both on product and technological level (not even counting AI and its tooling itself). The interesting parts of thinking an entire afternoon or week experimenting to get that design right disassembling the pros and cons are gone. Even if you want to do that, it's just faster to launch 6/7 worktrees with the different ideas and judge the results. But you don't get as intimate with the problem and the amount of information is way more than you can process.

lbrito 6mo ago
Forgive my ignorance, but if the corpus of coding data was always 90% bad, isn't that the same data being used for training LLMs? How are they magically any better than that average?
- epolanski 6mo ago
  Because LLMs are not stochastic parrots.
- thoman23 6mo ago
  Programmer: "What is this slop that I found in your code?" AI: "I LEARNED IT FROM YOU, DAD!"
- bigstrat2003 6mo ago
  They aren't. The guy you're replying to is just hyping them up based on nothing.
all2 6mo ago
I'm hand rolling a project right now because even frontier models I use bloat things beyond comprehension. Because I'm intimately familiar with the domain, I know the shape of things, how the data should flow, and so on, and if l even if I spec it clearly AI will write 2x to 5x the amount of code necessary to make something work.
- gw32 6mo ago
  "beyond comprehension" is a good way of putting it. I've been genuinely baffled by some of these AI designs - why any intelligent thing would write >10 lines of bloat for what should be a one-liner.
  - palmotea 6mo ago
    > "beyond comprehension" is a good way of putting it. I've been genuinely baffled by some of these AI designs - why any intelligent thing would write >10 lines of bloat for what should be a one-liner. As Anthropic's drones say: treat Claude as your genius coworker. Don't think yourself, don't judge, the machine must know better than you. It is the genius, after all, not you.
johnnyanmac 6mo ago
>If you have a good codebase with proper rails, hygiene and architecture Okay, so Ai is completely useless in my industry. Got it.
jagenabler2 6mo ago
Proper rails, hygiene and architecture need to be actively maintained, they don’t just continue to exist in a developing codebase. Historically, a small proportion (the 10% as you say) had a disproportionate amount of influence on coding standards. When they can no longer keep up with that ongoing maintenance, which we’re seeing with the increased pressure to ship code, the hygiene will regress. We’re riding the tail of all the engineering practices we’ve developed as an industry. This is what I’m seeing, anyways. Junior engineers are being rewarded for shipping so much code, it’s impossible to evaluate it all, and subtle changes in existing patterns are slipping through. Eventually all those subtle changes transform the rails.
tns_admin 6mo ago
> Even if you want to do that, it's just faster to launch 6/7 worktrees with the different ideas and judge the results. This means you take less time reviewing code than it took for the machine to churn it out. All that code must be a ticking time bomb.
achierius 6mo ago
90% of software engineers are not charlatans, and it's convenient that you at confidently place yourself in the "10%"

lbrito 6mo ago

Forgive my ignorance, but if the corpus of coding data was always 90% bad, isn't that the same data being used for training LLMs? How are they magically any better than that average?

epolanski 6mo ago
Because LLMs are not stochastic parrots.
thoman23 6mo ago
Programmer: "What is this slop that I found in your code?" AI: "I LEARNED IT FROM YOU, DAD!"
bigstrat2003 6mo ago
They aren't. The guy you're replying to is just hyping them up based on nothing.

all2 6mo ago

I'm hand rolling a project right now because even frontier models I use bloat things beyond comprehension. Because I'm intimately familiar with the domain, I know the shape of things, how the data should flow, and so on, and if l even if I spec it clearly AI will write 2x to 5x the amount of code necessary to make something work.

gw32 6mo ago
"beyond comprehension" is a good way of putting it. I've been genuinely baffled by some of these AI designs - why any intelligent thing would write >10 lines of bloat for what should be a one-liner.
- palmotea 6mo ago
  > "beyond comprehension" is a good way of putting it. I've been genuinely baffled by some of these AI designs - why any intelligent thing would write >10 lines of bloat for what should be a one-liner. As Anthropic's drones say: treat Claude as your genius coworker. Don't think yourself, don't judge, the machine must know better than you. It is the genius, after all, not you.

johnnyanmac 6mo ago

>If you have a good codebase with proper rails, hygiene and architecture Okay, so Ai is completely useless in my industry. Got it.

jagenabler2 6mo ago

Proper rails, hygiene and architecture need to be actively maintained, they don’t just continue to exist in a developing codebase. Historically, a small proportion (the 10% as you say) had a disproportionate amount of influence on coding standards. When they can no longer keep up with that ongoing maintenance, which we’re seeing with the increased pressure to ship code, the hygiene will regress. We’re riding the tail of all the engineering practices we’ve developed as an industry. This is what I’m seeing, anyways. Junior engineers are being rewarded for shipping so much code, it’s impossible to evaluate it all, and subtle changes in existing patterns are slipping through. Eventually all those subtle changes transform the rails.

tns_admin 6mo ago

> Even if you want to do that, it's just faster to launch 6/7 worktrees with the different ideas and judge the results. This means you take less time reviewing code than it took for the machine to churn it out. All that code must be a ticking time bomb.

achierius 6mo ago

90% of software engineers are not charlatans, and it's convenient that you at confidently place yourself in the "10%"