3 ms·

So, I admit that I'm finally getting into this "let Claude help you write code" stuff, and I'm enjoying it a bit for the stuff I, honestly, just don't want to w

So, I admit that I'm finally getting into this "let Claude help you write code" stuff, and I'm enjoying it a bit for the stuff I, honestly, just don't want to write; but ... I still read it. I still review it. I still look at the code like I'm peer-reviewing it and go, "Uh ... I don't like this area at all. That's going to be really hard to debug at 3am" and so on. I guess my thought / question is: this is your code. Why are you submitting the code to the git repo like that, with all the wrong text? I get making mistakes here or there; but ... everywhere? Enough that it's causing huge problems you can't quickly correct? And ... aren't you lucky you still *have* the context in your mind? What if you hadn't caught it, or someone else had done that and you inherited that code with those wrong comments that you let through the PR and into the main branch?

bojan 1mo ago
> Why are you submitting the code to the git repo like that, with all the wrong text? According to my enterprise architect I shouldn't be reviewing code, it's a waste of time in this new reality. I'm still doing it because it's going to be me answering that 3 AM call. But I don't know for how long I'll be allowed to swim upstream like that.
- qsera 1mo ago
  I have found manual reviewing of LLM generated code to be an uphill battle. LLMs does not believe in abstraction. So complexity spills everywhere. Some details in the lowest level might be handled separately in more than one place, at the higher levels. In a short while it is a copiously documented unreadable mess (both code and documentation). LLM written PR descriptions and comments are a sight to behold. I am not sure how stuff can be written so cryptically. It seems that LLMs just make up what ever terminology so that it can cram as much details into a single sentence as possible! I generally just paste it to chatgpt and ask it to decrypt it.
  - sfn42 1mo ago
    Yeah, that happens when you vibe code and just let the LLM be in control of everything. If you take responsibility for the architecture and instruct it to do things properly it will do them properly. You can tell it exactly how to do it or you can ask it to handle it in a way that avoids duplication, you can tell it to design a reusable abstraction for this usecase etc.
    - qsera 1mo ago
      >If you take responsibility for the architecture and instruct it to do things properly it will do them properly. The problem here is that after a while it is impossible to detect when such potential abstractions is overlooked in the generated code. Because it has become hard to reason about the existing code. Not all work is green field.
      - voakbasda 1mo ago
        I have wondered about this. Can’t you ask the AI to find the patterns than need abstracting?
        fortzi 1mo ago
        Yes you can. Sometimes it’ll find them, sometimes it won’t. I find myself having to use Claude to untangle its own mess piece by piece, a as it charged full steam ahead with the design we made together. However, not everything can be foreseen in a design, unless you go full waterfall. Sometimes I find myself in front of a mountain of bad abstractions stemming from a subtle oversight in the design. Before AI coding, I would find details while coding and catch them in time before they became sinful abominations
        sfn42 1mo ago
        You can do that, with varying results. Or you can just do actual software engineering like we used to do, and tell it what patterns to abstract and how. You choose your level of effort and involvement. The LLM can write whatever you tell it to write. If you send a drawing of an app and say "make this" then you'll get whatever it comes up with. If you tell it how to make it then it will make it the way you tell it to. If your AI code is trash that's because you're trash at directing it.
cs02rm0 1mo ago
> So, I admit that I'm finally getting into this "let Claude help you write code" stuff, and I'm enjoying it a bit for the stuff I, honestly, just don't want to write; but ... I still read it. I still review it. I still look at the code like I'm peer-reviewing it and go, "Uh ... I don't like this area at all. That's going to be really hard to debug at 3am" and so on. I used to. I've stopped in recent months, only because I just can't keep up with the pace it's churning out the code. If I was to read it, it would take multiples longer to develop anything, maybe into orders of magnitude longer. Occasionally I'll dip in just to get a sense of things, especially if it's struggling with something, or at the opposite end, if it's completely trivial. But I'm hardly reading anything now.
- menaerus 1mo ago
  Exactly. That would mean going back to square one, and I also personally don't review the code anymore but I am more focused on asking the model to demonstrate the value it created through benchmarks, workload-generators, and e2e tests. Mostly it proves as a valid approach, barring the bugs the model can introduce to value-demonstrating benchmarks which can of course skew the evidence on hypotheses, and thus code trajectory the model opts to go with. The problem I see with this is really that I am not anymore under the control but I am not sure I see other alternative. I am becoming more and more like a system observer with surface-level understanding of the system rather than the engineer with zoomed-in level of understanding of how the code actually behaves. Perhaps we're transitioning into a QA roles present.
  - fortzi 1mo ago
    Are you working on complex systems that serve many users in production? Do you actually save time?
    - menaerus 1mo ago
      Yes, I can't say exactly what but the backbone of cloud computing and/or infra, think databases, distributed storage, filesystems, ...
killix 1mo ago
[flagged]
ghoul2 1mo ago
The problem, in my experience is: 1. It writes SO MUCH code, in minutes, that theres no way I as a human can review it. 2. I am not very motivated to read/review this code anyway: it was cheaply written, by some _thing_ that is not going to improve from my feedback. 3. If you DO review it conscientiously , it becomes a never ending thing: you keep finding issue upon issue. 4. If you report the issues for fixes, the fixes normally fix that immediate issue, and typically add another parallel path/another option/another 100-odd lines of code, instead of a structural fix. 5. If the code base is large, and if you let AI write a meaningful amount of code in it, its no longer _your_ code. You lose the depth+width of understanding needed to reason thru things mentally, cause you no longer KNOW enough about the code. 6. If you do review seriously, and either fix things yourself, or have the ai/harness fix the issues for you, the rounds of fixes take so long, if you look back you realize it would have been better to just do it yourself in the first place. My personal opinion there are really only two choices: A. If you want to build FAST, using an agent, just let the agent write tests, validations, extensively, have it keep running them (it likes to call them gates), and just let it loose. Give up on the idea that its your code, and that you understand it. The bottom line becomes: does it work, and WHEN it breaks in weird ways, just use the agent to find and fix the issue (probably breaking something else in the process). B. limit AI use for non trivial, prod-quality projects to limited research, very tiny targeted changes, write most of the code yourself still, and review every line. You won't get much speedup, maybe 20-30%, but it will still be YOUR code, and you will still be able to reason about it.
- t-writescode 1mo ago
  Route A seems genuinely horrifying to me - maybe not for small and/or helper scripts; but for anything substantial. For anything that bites you or someone else hard when things go bad. I don’t want a vibe-coded, mass-produced diabetes tracking app, or banking tool, or tax management software. I don’t want a vibe-coded power grid analysis software. I don’t care if a person’s little, local scripting thing is vibe-coded. I don’t care if an artist’s 0->1 game code is vibe-coded; but that’s not what a lot of the things we’re talking about here really are.
  - anon373839 1mo ago
stuaxo 1mo ago
Yeah - the comments it writes are often "waypoint comments" [1] - great for the LLM during creation but just crap for us - I ask it to remove those before committing. [1] Not sure if I read that or came up with it.
- vitorsr 1mo ago
  I believe the general phenomenon is metadiscourse and those in specific are signposting constructions.

bojan 1mo ago

> Why are you submitting the code to the git repo like that, with all the wrong text? According to my enterprise architect I shouldn't be reviewing code, it's a waste of time in this new reality. I'm still doing it because it's going to be me answering that 3 AM call. But I don't know for how long I'll be allowed to swim upstream like that.

qsera 1mo ago
I have found manual reviewing of LLM generated code to be an uphill battle. LLMs does not believe in abstraction. So complexity spills everywhere. Some details in the lowest level might be handled separately in more than one place, at the higher levels. In a short while it is a copiously documented unreadable mess (both code and documentation). LLM written PR descriptions and comments are a sight to behold. I am not sure how stuff can be written so cryptically. It seems that LLMs just make up what ever terminology so that it can cram as much details into a single sentence as possible! I generally just paste it to chatgpt and ask it to decrypt it.
- sfn42 1mo ago
  Yeah, that happens when you vibe code and just let the LLM be in control of everything. If you take responsibility for the architecture and instruct it to do things properly it will do them properly. You can tell it exactly how to do it or you can ask it to handle it in a way that avoids duplication, you can tell it to design a reusable abstraction for this usecase etc.
  - qsera 1mo ago
    >If you take responsibility for the architecture and instruct it to do things properly it will do them properly. The problem here is that after a while it is impossible to detect when such potential abstractions is overlooked in the generated code. Because it has become hard to reason about the existing code. Not all work is green field.
    - voakbasda 1mo ago
      I have wondered about this. Can’t you ask the AI to find the patterns than need abstracting?
      - fortzi 1mo ago
        Yes you can. Sometimes it’ll find them, sometimes it won’t. I find myself having to use Claude to untangle its own mess piece by piece, a as it charged full steam ahead with the design we made together. However, not everything can be foreseen in a design, unless you go full waterfall. Sometimes I find myself in front of a mountain of bad abstractions stemming from a subtle oversight in the design. Before AI coding, I would find details while coding and catch them in time before they became sinful abominations
      - sfn42 1mo ago
        You can do that, with varying results. Or you can just do actual software engineering like we used to do, and tell it what patterns to abstract and how. You choose your level of effort and involvement. The LLM can write whatever you tell it to write. If you send a drawing of an app and say "make this" then you'll get whatever it comes up with. If you tell it how to make it then it will make it the way you tell it to. If your AI code is trash that's because you're trash at directing it.

cs02rm0 1mo ago

> So, I admit that I'm finally getting into this "let Claude help you write code" stuff, and I'm enjoying it a bit for the stuff I, honestly, just don't want to write; but ... I still read it. I still review it. I still look at the code like I'm peer-reviewing it and go, "Uh ... I don't like this area at all. That's going to be really hard to debug at 3am" and so on. I used to. I've stopped in recent months, only because I just can't keep up with the pace it's churning out the code. If I was to read it, it would take multiples longer to develop anything, maybe into orders of magnitude longer. Occasionally I'll dip in just to get a sense of things, especially if it's struggling with something, or at the opposite end, if it's completely trivial. But I'm hardly reading anything now.

menaerus 1mo ago
Exactly. That would mean going back to square one, and I also personally don't review the code anymore but I am more focused on asking the model to demonstrate the value it created through benchmarks, workload-generators, and e2e tests. Mostly it proves as a valid approach, barring the bugs the model can introduce to value-demonstrating benchmarks which can of course skew the evidence on hypotheses, and thus code trajectory the model opts to go with. The problem I see with this is really that I am not anymore under the control but I am not sure I see other alternative. I am becoming more and more like a system observer with surface-level understanding of the system rather than the engineer with zoomed-in level of understanding of how the code actually behaves. Perhaps we're transitioning into a QA roles present.
- fortzi 1mo ago
  Are you working on complex systems that serve many users in production? Do you actually save time?
  - menaerus 1mo ago
    Yes, I can't say exactly what but the backbone of cloud computing and/or infra, think databases, distributed storage, filesystems, ...

killix 1mo ago

[flagged]

ghoul2 1mo ago

The problem, in my experience is: 1. It writes SO MUCH code, in minutes, that theres no way I as a human can review it. 2. I am not very motivated to read/review this code anyway: it was cheaply written, by some _thing_ that is not going to improve from my feedback. 3. If you DO review it conscientiously , it becomes a never ending thing: you keep finding issue upon issue. 4. If you report the issues for fixes, the fixes normally fix that immediate issue, and typically add another parallel path/another option/another 100-odd lines of code, instead of a structural fix. 5. If the code base is large, and if you let AI write a meaningful amount of code in it, its no longer _your_ code. You lose the depth+width of understanding needed to reason thru things mentally, cause you no longer KNOW enough about the code. 6. If you do review seriously, and either fix things yourself, or have the ai/harness fix the issues for you, the rounds of fixes take so long, if you look back you realize it would have been better to just do it yourself in the first place. My personal opinion there are really only two choices: A. If you want to build FAST, using an agent, just let the agent write tests, validations, extensively, have it keep running them (it likes to call them gates), and just let it loose. Give up on the idea that its your code, and that you understand it. The bottom line becomes: does it work, and WHEN it breaks in weird ways, just use the agent to find and fix the issue (probably breaking something else in the process). B. limit AI use for non trivial, prod-quality projects to limited research, very tiny targeted changes, write most of the code yourself still, and review every line. You won't get much speedup, maybe 20-30%, but it will still be YOUR code, and you will still be able to reason about it.

t-writescode 1mo ago
Route A seems genuinely horrifying to me - maybe not for small and/or helper scripts; but for anything substantial. For anything that bites you or someone else hard when things go bad. I don’t want a vibe-coded, mass-produced diabetes tracking app, or banking tool, or tax management software. I don’t want a vibe-coded power grid analysis software. I don’t care if a person’s little, local scripting thing is vibe-coded. I don’t care if an artist’s 0->1 game code is vibe-coded; but that’s not what a lot of the things we’re talking about here really are.
- anon373839 1mo ago

stuaxo 1mo ago

Yeah - the comments it writes are often "waypoint comments" [1] - great for the LLM during creation but just crap for us - I ask it to remove those before committing. [1] Not sure if I read that or came up with it.

vitorsr 1mo ago
I believe the general phenomenon is metadiscourse and those in specific are signposting constructions.