Comment by usrbinbash
7 hours ago
> My answer to this is to often get the LLMs to do multiple rounds of code review
So I am supposed to trust the machine, that I know I cannot trust to write the initial code correctly, to somehow do the review correctly? Possibly multiple times? Without making NEW mistakes in the review process?
Sorry no sorry, but that sounds like trying to clean a dirty floor by rubbing more dirt over it.
It sounds to me like you may not have used a lot of these tools yet, because your response sounds like pushback around theoreticals.
Please try the tools (especially either Claude Code with Opus 4.5, or OpenAI Codex 5.2). Not at all saying they're perfect, but they are much better than you currently think they might be (judging by your statements).
AI code reviews are already quite good, and are only going to get better.
Implementation -> review cycles are very useful when iterating with CC. The point of the agent reviewer is not to take the place of your personal review, but to catch any low hanging fruit before you spend your valuable time reviewing.
Well, you can review its reasoning. And you can passively learn enough about, say, Rust to know if it's making a good point or not.
Or you will be challenged to define your own epistemic standard: what would it take for you to know if someone is making a good point or not?
For things you don't understand enough to review as comfortably, you can look for converging lines of conclusions across multiple reviews and then evaluate the diff between them.
I've used Claude Code a lot to help translate English to Spanish as a hobby. Not being a native Spanish speaker myself, there are cases where I don't know the nuances between two different options that otherwise seem equivalent.
Maybe I'll ask 2-3 Claude Code to compare the difference between two options in context and pitch me a recommendation, and I can drill down into their claims infinitely.
At no point do I need to go "ok I'll blindly trust this answer".
Wait until you start working with us imperfect humans!
Humans do have capacity for deductive reasoning and understanding, at least. Which helps. LLMs do not. So would you trust somebody who can reason or somebody who can guess?
People work different than llms they fond things we don't and the reverse is also obviously true. As an example, a stavk ise after free was found in a large monolithic c++98 codebase at my megacorp. None of the static analyzers caught it, even after modernizing it and getting clang tidy modernize to pass, nothing found it. Asan would have found it if a unit test had covered that branch. As a human I found it but mostly because I knew there was a problem to find. An llm found and explained the bug succinctly. Having an llm be a reviewer for merge requests males a ton of sense.