Look at this one:
> Ask Claude to remove the "backup" encryption key. Clearly it is still important to security-review Claude's code!
> prompt: I noticed you are storing a "backup" of the encryption key as `encryptionKeyJwk`. Doesn't this backup defeat the end-to-end encryption, because the key is available in the grant record without needing any token to unwrap it?
I don’t think a non-expert would even know what this means, let alone spot the issue and direct the model to fix it.
The main value I've gotten out of AI writing software comes from the two extremes; not from the middle-ground you present. Vibe coding can be great and seriously productive; but if I have to check it or manually maintain it in nearly any capacity more complicated than changing one string, productivity plummets. Conversely; delegating highly complex, isolated function writing to an AI can also be super productive, because it can (sometimes) showcase intelligence beyond mine and arrive at solutions which would take me 10x longer; but definitionally I am not the right person to check its code output; outside of maybe writing some unit tests for it (a third thing AI tends to be quite good at)
Are you being serious here?
Let's do the math.
1200 lines in a hour would be one line every three seconds, with no breaks.
And your figure of 1200 lines is apparently omitting whitespace and comments. The actual code is 2626 lines. Let's say we ignore blank lines, then it's 2251 lines. So one line per ~1.6 seconds.
The best typists type like 2 words per second, so unless the average line of code has 3 words on it, a human literally couldn't type that fast -- even if they knew exactly what to type.
Of course, people writing code don't just type non-stop. We spend most of our time thinking. Also time testing and debugging. (The test is 2195 lines BTW, not included in above figures.) Literal typing of code is a tiny fraction of a developer's time.
I'd say your estimate is wrong by at least one, but realistically more likely two orders of magnitude.