No, it wouldn't, because he didn't actually read the readme which clearly states that they are still working on passing the CPython test suite and that 5x performance is an aspirational goal, not something they accomplished yet.
>What is explicitly not done yet — this is the active roadmap, in order:
>CPython test suite (cpython-full): the standing grind; failures are clustered and burned down per wave.
>Stdlib build-out: _io/os, math/struct/random, collections/itertools/json, datetime, importlib parity — each lands as a native module plus a differential corpus module.
>Performance ratchets: tagged small-int flip, TLAB allocation, dict fast paths, float unboxing, call/attribute specialization, generator tiering — toward the ≥5× CPython geomean target (numerics ≥20×).
>AoT parity growth toward the full corpus, plus single-binary product polish.
>No-GIL/free-threaded runtime hardening: thread/GC/signal stress is now on the default runtime path, with remaining gaps tracked by the ratcheted suites.
Overall the substantial parts of his comment are completely wrong and the subjective parts are not much better
>With AI it's 100x easier to maintain than by hand.
This is an unsubstantiated opinion. In practice AI has a limit well below 100x.
>It reminds my on pperl. same approach using crane lift. Looks good
The only thing I can find on the internet that mentions "pperl" is this https://metacpan.org/pod/PPerl
>This program turns ordinary perl scripts into long running daemons, making subsequent executions extremely fast. It forks several processes for each script, allowing many proceses to call the script at once.
Which sounds nothing like pon, which is heavily inspired by bun. Meanwhile if it's this: https://perl.petamem.com/ which took quite a while to find, then I'm wondering why that would have precedence over bun?
Once you add the first sentence, it basically turns into a negative value comment that shouldn't have been posted.