I have my own anecdata but my comment is more about the dissonance here.
A counterpoint is Google saying the vast majority of their code is written by AI. The developers at Google are not inexperienced. They build complex critical systems.
But it still feels odd to me, this contradiction. Yes there’s some skill to using AI but that doesn’t feel enough to explain the gap in perception. Your point would really explain it wonderfully well, but it’s contradicted by pronouncements by major companies.
One thing I would add is that code quality is absolutely tanking. PG mentioned YC companies adopted AI generated code at Google levels years ago. Yesterday I was using the software of one such company and it has “Claude code” levels of bugginess. I see it in a bunch of startups. One of the tells is they seem to experience regressions, which is bizarre. I guess that indicates bugs with their AI generated tests.
Alternatively, it could be there’s a large swath of people out there so stupid they are proud of code your mom can somehow review and suggest improvements in despite being nontechnical.
I don't think this is a hypothesis.
Outside of asking for one-shot tasks that have been done a million times before, LLMs do not "default" to good work.
If you ask them over-and-over again to find holes in their solution, to fix them, to evaluate for tech debt, to test all cases, to re-asses after the cases if it's architecturally coherent, to compare to the closest available known good implementations, etc etc, they can eventually get what you want done unbelievably cheaply to an acceptable level of quality.
I mentioned initially - their work is unbelievably cheap, you should be EAGER to reject it. Most people wouldn't even bend down to pick a penny up off the sidewalk. They can literally pump out CLs for a penny. You shouldn't even waste time looking at "I'm done" until they've gone through 10+ rounds of reviews, refactors, bug fixes, thought of more test cases, compared to known implementations, etc.
Why are you going to spend ~$50-$100+ of your time reviewing $0.01 of LLM time?! It makes no sense!
If you just listen to them say "I'm done" and move on to their next task, it won't take too many days before you're swimming in a sea of incoherent garbage.
Someone pointed out to me in the comments that the username had posted long replies to 3 completely different threads in the same minute. That and looking back at its post history confirmed it was a bot.
For example I’m working on a huge data migration right now. The data has to be migrated correctly. If there are any issues I want to fail fast and loud.
Claude hates that philosophy. No matter how many different ways I add my reasons and instructions to stop it to the context, it will constantly push me towards removing crashes and replacing them with “graceful error handling”.
If I didn’t have a strong idea about what I wanted, I would have let it talk me into building the wrong thing.
Claude has no taste and its opinions are mostly those of the most prolific bloggers. Treating Claude like a peer is a terrible idea unless you are very inexperienced. And even then I don’t know if that’s a good idea.
I often think that LLMs are like a reddit that can talk. The more I use them, the more I find this impression to be true - they have encyclopedic knowledge at a superficial level, the approximate judgement and maturity of a teenager, and the short-term memory of a parakeet. If I ask for something, I get the statistical average opinion of a bunch of goons, unconstrained by context or common sense or taste.
That’s amazing and incredible, and probably more knowledgeable than the median person, but would you outsource your thinking to reddit? If not, then why would you do it with an LLM?
Love this paragraph; it's exactly how I feel about the LLMs. Unless you really know what you are doing, they will produce very sub-optimal code, architecturally speaking. I feel like a strong acumen for proper software architecture is one of the main things that defines the most competent engineers, along with naming things properly. LLMs are a long, long way from having architectural taste
My guess is that there must be something about the language(go) or the domain (a data migration tool that uses Kafka) that triggers this.
I, on the other hand, am doing a new UI for an existing system, which is exactly where you want more freedom and experimentation. It's great for that!
> No matter how many different ways I add my reasons and instructions to stop it to the context
Is it generating JS code for that?
I've had interesting chats where it explained that it's choice of tailwind for example was because it had a ton of training knowledge on it.
I've also had it try to build more in one chat than it should many times.
For some reason openai codex handles building too much without failing better - but that is total anecdata from my particular projects and ymmv.
I've had these things try to build big when a little nudge gets them to change direction and not build so much. Explain which libraries and such and asking it to change the tech stack and the steps to build at once seem to make things much better for my use cases.
Also running extra checks and cleanup later is a thing, that sure a human might have seen an obvious thing at time of build, but we have bigger memory context comparatively imho.
From my observations, generally AI-generated code is average quality.
Even with average quality it can save you a lot of time on some narrowly specialized tasks that would otherwise take you a lot of research and understanding. For example, you can code some deep DSP thingie (say audio) without understanding much what it does and how.
For simpler things like backend or frontend code that doesn't require any special knowledge other than basic backend or frontend - this is where the bars of quality come into play. Some people will be more than happy with AI generated code, others won't be, depending on their experience, also requirements (speed of shipping vs. quality, which almost always resolves to speed) etc.