121–130 of 291 posts
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I don't know why that's funny. This is not a post about a vibe coding session. It's Kenton Varda['s coding session]. later updated to clarify kentonv didn't write this article
The sequence of commits talked about by the OP -- i.e. kenton's coding session's commits -- are like one degree removed from 100% pure vibe coding.
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Can we please stop using the em-dash as a metric to “detect” LLM writing? It’s lazy and wrong. Plenty of people use em-dashes, it’s a useful punctuation mark . If humans didn’t use them, they wouldn’t be in the LLM training data. There are better clues, like the kind of vague pretentious babble bad marketers use to make their products and ideas seem more profound than they are. It’s a type of bad writing which looks…
Very few people use n dashes in internet writing as opposed to dashes as they are not available on the default keyboard.
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have you no tests?
Irrelevant, really. Tests establish a minimum threshold of acceptability, they don't (and can't) guarantee anything like overall correctness.
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No, what's happening here is we're talking past each other. An agent lints and compiles code . The LLM is stochastic and unreliable. The agent is ~200 lines of Python code that checks the exit code of the compiler and relays it back to the LLM. You can easily fool an LLM. You can't fool the compiler. I didn't say anything about whether code needs to be reviewed line-by-line by humans. I review LLM code line-by-line.…
> If the LLM hallucinates, then the code it produces is wrong. That wrong code isn't obviously or programmatically determinable as wrong, the agent has no way to figure out that it's wrong, it's not as if the LLM produces at the same time tests that identify that hallucinated code as being wrong. The only way that this wrong code can be identified as wrong is by the human user "looking closely" and figuring out that…
That's not how I use it. I see hallucination as a very specific kind of mistake: one where the LLM outputs something that is entirely fabricated, like a class method that doesn't exist.
The agent compiler/linter loop can entirely eradicate those. That doesn't mean the LLM won't make plenty of other mistakes that don't qualify as hallucinations by the definition I use!
It's newts and salamanders. Every newt is a salamander, not every salamander is a newt. Every hallucination is a mistake, not every mistake is a hallucination.
https://simonwillison.net/2025/Mar/2/hallucinations-in-code/
Many of you are failing to conprehend the potential scale of AI generated codebases. Take note - there is no limit. Every feature you or the AI can prompt can be generated. Imagine if you were immortal and given unlimited storage. Imagine what you could create. That’s a prompt away. Even now you’re still restricting your thinking to the old ways.
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Models are improving every day. People are figuring out thousands of different optimizations to training and to hardware efficiency. The idea that right now in early June 2025 is when improvement stops beggars belief. We might be approaching a limit, but that's going to be a sigmoid curve, not a sudden halt in advancement.
I think at this point we're reaching more incremental updates, which can score higher on some benchmarks but then simultaneously behave worse with real-world prompts, most especially if they were prompt engineered for a specific model. I recall Google updating their Flash model on their API with no way to revert to the old one and it caused a lot of people to complain that everything they've built is no longer workin…
I asked this in the other thread (no response, but I was a bit late) How does anyone using AI like this have confidence that they aren't unintentionally plagiarizing code and violating the terms of whatever license it was released under? For random personal projects I don't see it mattering that much. But if a large corp is releasing code like this, one would hope they've done some due diligence that they have to jus…
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If a junior engineer ships a similar repo to this with the help of AI, sure, I'll buy that. But as of now, it's senior engineers who really know what they 're doing who can spot the errors in AI code.
Hold on. You said "really know what they're doing". Yes, I agree with that. What I don't buy is the coupling of that concept with "seniority".
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Have a better term for "knows what they're doing" other than senior?
That's not what "senior" means.