Anyone who thinks they can produce high quality code from an LLM is mistaken about how to judge code. Trust me, I've seen enough PRs to last a life time. A lot of professionals wouldn't know good code if it slapped them in the face.
Ultimately, I would take LLM code + high-quality multi-strategy testing over human code with little to no tests. And some would say "well that's a false dichotomy". I disagree, before LLMs engineers didn't have the time or incentives to aggressively test. The tests either would not exist, or would be shitty unit tests intended to get an arbitrary coverage percentage. Now, we can write high-quality tests, differential testing, fuzzing, and more, in much less time.
Another spectrum that I've found useful to explore is the scope of what I ask the coding agent to do in one turn. I see some people trying to do one massive prompt that the coding agent works on for a day or more. I find a large boost in overall quality if I do 10-20 prompts per day (not counting the prompts where I'm just trying to understand things). It's still much less of my time than hand-coding, but the resulting architecture looks like my own. The quality of the overall system is great. There are certainly issues here and there in the code, but it's always that way once a project gets large enough. Now it's easier to address any particular issue throughout the code base in one go.
The larger issue of good code isn't the actual individual lines, it's the overall architecture. And that's what I'm going to be reviewing first is, is this a good approach? Then the interfaces to other code is this a good interface. Get those two right and we can go back for the details. In a lot of cases, the LLM is plenty good at those details.
In some cases, an LLM is better than what I could do. Well, I suppose I can trace down all the locks in all the different special cases, and I have done that, but that was a huge amount of effort that I really don't want to repeat.
Note that I'm talking about recent models. If you're asking about the models of just one year ago, I would give a very different answer about the type of code an LLM produces.
Sorry, but you are 100% wrong.
I have 30+ years of professional development experience working on complex, very large-scale C++ code used by companies around the world.
I care deeply about code quality and always have. More than any other developer I've worked with in my 30+ year career. And I'm now using Claude Code to push the quality bar much higher.
But you have to learn how to use it properly. It's a tool. Quality doesn't happen automatically.
It's a big mistake, and frankly quite arrogant, to assume that because it doesn't work for you, it can't work for anyone else. Or that the rest of us must either be lying or incompetent.
However, if you’re willing to share how you’re prompting the AI and some examples of where you think the results are poor, we might be able to help identify what’s causing the difference. I’d be genuinely interested in understanding why we’re getting such different results.
Rather than assuming one of us must be wrong, it would be more useful to compare approaches and see what we can learn from each other.