I’m not joking, but weirdly enough, that’s what most AI arguments boil down to. Show me what the difference is while I pull up the endless CVE list of which ever coreutils package you had in mind. It’s a frustrating argument because you know that authors of coreutils-like packages had intentionality in their work, while an LLM has no such thing. Yet at the end, security vulnerabilities are abundant in both.
The AI maximalists would argue that the only way is through more AI. Vibe code the app, then ask an LLM to security review it, then vibe code the security fixes, then ask the LLM to review the fixes and app again, rinse and repeat in an endless loop. Same with regressions, performance, features, etc. stick the LLM in endless loops for every vertical you care about.
Pointing to failed experiments like the browser or compiler ones somehow don’t seem to deter AI maximalists. They would simply claim they needed better models/skills/harness/tools/etc. the goalpost is always one foot away.
That's why I wrote my own compiler and coreutils. Can't trust some shit written by GNU developers 30 years ago.
And my own kernel. Can't trust some shit written by a Finnish dude 30 years ago.
And my own UEFI firmware. Definitely can't trust some shit written by my hardware vendor ever.
Yeah definitely no difference between GNU coreutils and some vibe coded AI tool released last month that wants full oAuth permissions.
I’m not joking, but weirdly enough, that’s what most AI arguments boil down to. Show me what the difference is while I pull up the endless CVE list of which ever coreutils package you had in mind. It’s a frustrating argument because you know that authors of coreutils-like packages had intentionality in their work, while an LLM has no such thing. Yet at the end, security vulnerabilities are abundant in both.
The AI maximalists would argue that the only way is through more AI. Vibe code the app, then ask an LLM to security review it, then vibe code the security fixes, then ask the LLM to review the fixes and app again, rinse and repeat in an endless loop. Same with regressions, performance, features, etc. stick the LLM in endless loops for every vertical you care about.
Pointing to failed experiments like the browser or compiler ones somehow don’t seem to deter AI maximalists. They would simply claim they needed better models/skills/harness/tools/etc. the goalpost is always one foot away.
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So it’s not a binary thing, there’s context and nuance?
Embrace the suck.
cue Jeopardy theme song
Who is Apple?
TempleOS, is that you?