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Using AI to write better code more slowly

nolanlawson.com

401–410 of 511 posts

Re: Using AI to write better code more slowly

#401

I've hit this point with AI where it's not a simple process, but a long drawn out back and forth. I'll use AI to design the implementation of a medium sized, cross cutting feature. Review all the details, maybe iterate on just that. Then implement with Claude 4.7 Max - which runs slower, but does a better job. Then review the implementation, then have Codex GPT 5.5 xhigh fast review it - which almost always finds cor…

> I've hit this point with AI where it's not a simple process, but a long drawn out back and forth. In my experience, even on a relatively trivial task, you can ask an LLM at least 20 times: Is this actually done, or only partially implemented? Did you finish x, y, z? And the LLM will say, no, I'm not done and keep working. After that, I'll feed the branch to a different LLM, and ask if the implementation matched the…

This is where the human element is critical, but cause it'll infinite loop review feedback if you let it and the code will easily go off the rails into an over engineered mess. That's why I review the code before/after as well as review the actual feedback itself - and often give the feedback to different AI to get its opinion as the other AI doesn't have a vested interest in it and can be more critical. At some point though you do have to cut them off and ship.

Re: Using AI to write better code more slowly

#402

Earlier quoted context omitted.

I really like this pattern and use it often, this 'not showing my cards'. The second I hint towards the LLM what I prefer it will become sycophantic and invent nonsense why my preferred solution is better. I'm sure there's an interesting study on how users 'leak' their preference unintentionally to the LLM; perhaps when users list their options, they often put their prefered option first; but not showing the cards on…

LLMs flip positions when users push back ~70% of the time even when they were right. RLHF optimizes for approval, not correctness

Interesting thing about psychponancy is it’s asymmetric. If an LLM is used to train an LLM it may not have the same level of aggressiveness that humans do when punishing back on trainee. Human pushback has specific patterns which we might be able to compensate due to asymmetry.

Re: Using AI to write better code more slowly

#403

Earlier quoted context omitted.

LLMs flip positions when users push back ~70% of the time even when they were right. RLHF optimizes for approval, not correctness

Tangentially related but I’ve been using Claude to practice interviewing on system design problems, and it’s actually pretty great. But even when it likes my answers it always finds something, however small, to push on. Once it actually was completely wrong and admitted it after I had it realize. So maybe you have to prime it to be contrary and not agree with everything you say, putting it in the role of a tough inte…

Take a look at hellointerview.com their model is very stubborn, similar to some interviewers who refuse to acknowledge even valid solutions that differ from the canon.

No affiliation.

Re: Using AI to write better code more slowly

#404
post #38

I find myself spending on average more time in LLM review/resolution loops than it would take for me to write the code by hand. Partially because once I'm in the flow I write very very quickly and the code pours out sometimes faster than I can write. But also because the LLM code on the first few tries is generally really really bad. What I find interesting though is that spending the time to personally review and di…

If your AI is writing bad code then you need to change your AI. No current high-end AI should be producing bad code.

This is delusional. Opus 4.7 regularly produces pretty bad code.

Re: Using AI to write better code more slowly

#406
post #127

Earlier quoted context omitted.

>You argue to teach yourself. Oh. I am aware. It is not that deep. But who you argues with still matter. There was a point where I have abandoned Reddit and HN. I came back to HN because people here also seem to have grown up. Reddit stays mostly the same. I credit the moderation here for that, I mean allowing people to grow out of the echo chamber.

It does to an extent. One thing I will give AI, because of the nature of LLMs, you are essentially arguing with the median level of the input that trained the model. So, for someone new to the subject, you get access to patterns that will bring them up to a certain level. Getting past that is problem we face now.

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Re: Using AI to write better code more slowly

#407
post #65

Earlier quoted context omitted.

>I argue about design and architecture all day with a robot. You will outgrow it at some point.

Its like that phase people go through where they argue with morons on reddit, and then one day grow up and realize that most of these people are unemployed/underemployed terminally online nobodies aren't ever going to learn anything, and even if they did it wouldn't impact the world since they were just some below average hobbyist anyway and aren't in charge of anything more important than a box of paperclips.

[dead]

Re: Using AI to write better code more slowly

#408

I've hit this point with AI where it's not a simple process, but a long drawn out back and forth. I'll use AI to design the implementation of a medium sized, cross cutting feature. Review all the details, maybe iterate on just that. Then implement with Claude 4.7 Max - which runs slower, but does a better job. Then review the implementation, then have Codex GPT 5.5 xhigh fast review it - which almost always finds cor…

Your comment begins like ai slop.

I think you're projecting.

Re: Using AI to write better code more slowly

#409

I've hit this point with AI where it's not a simple process, but a long drawn out back and forth. I'll use AI to design the implementation of a medium sized, cross cutting feature. Review all the details, maybe iterate on just that. Then implement with Claude 4.7 Max - which runs slower, but does a better job. Then review the implementation, then have Codex GPT 5.5 xhigh fast review it - which almost always finds cor…

I've settled on the same workflow. Also I never multitask with multiple agents doing other stuff. Meh I focus on just the one task.

I do multi-task a bit while AI is running, sometimes working on another feature with AI in parallel, but jumping between reviewing different feature iterations is draining, though not much different than the real world juggling PR reviews for a team of devs.
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