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.
You can write good and bad code with and without AI, on a managed service, self-hosted, or something in between.
And the comment I was replying to said something about not trusting something written in Akron, OH 2 years ago, which makes no sense and is barely an argument, and I was mostly pointing out how silly that comment sounds.
Regarding the unix philosophy argument, comparing it to AI tools just doesn't make any sense. If you look at what the philosophy is, it's obvious that it doesn't just boil down to "use many small tools" or "use many dependencies", it's so different that it not even wrong [0].
In their Unix paper of 1974, Ritchie and Thompson quote the following design considerations:
- Make it easy to write, test, and run programs.
- Interactive use instead of batch processing.
- Economy and elegance of design due to size constraints ("salvation through suffering").
- Self-supporting system: all Unix software is maintained under Unix.
In what way does that correspond to "use dependencies" or "use AI tools"? This was then formalised later to
- Write programs that do one thing and do it well.
- Write programs to work together.
- Write programs to handle text streams, because that is a universal interface.
This has absolutely nothing in common with pulling in thousands of dependences or using hundreds of third party services.
Then there is the argument that "AI is just a higher level compiler". That is akin to me saying that "AI is just a higher level musical instrument" except it's not, because it functions completely differently to musical instruments and people operate them in a completely different way. The argument seems to be that since both of them produce music, in the same way both a compiler and LLM generate "code", they are equivalent. The overarching argument is that only outputs matter, except when they don't because the LLM produces flawed outputs, so really it's just that the outputs are equivalent in the abstract, if you ignore the concrete real-world reality. Using that same argument, Spotify is a musical instrument because it outputs music, and hey look, my guitar also outputs music!