all those youtube videos people upload nowadays aren't worth it, we already have keyboardcat (^ basically telling ppl creativity is done with, don't bother)
The parent comment is just pointing out that LLM written forks pushed out within hours of a “buzzy” repo release on GitHub are a pretty useless signal for gauging actual adoption/interest.
Which is, IMO, accurate based on the state of the AI dev space in 2026. Stars/forks drafting off the hype from a well known name are constantly gamed for eyeballs/personal brand-building courtesy of free advertising via the Github UI when the only cost is a few sentence prompt and some tokens.
Maintaining a fork costs you mental space, time and energy, even if someone else (i.e. AI) can reliably do all the work. (In my experience they're not quite there yet.)
I've been contemplating that recently. You're of course correct that subsidized tokens won't be forever, but that might only be half the story, since there's two opposing forces in action:
1. Phasing out of subsidized tokens.
2. Token prices being brought down through scaling, better hardware, etc.
It's possible that these might balance each other out sufficiently that token customers won't notice any substantial increase in price.
That was yesterday's "LLMs might". Time passes. Nothing stays the same. "Local models might" X Y or Z today has no influence on the limitations of tomorrow's local models except to remove them. Yesterday's LLMs are the exact same thing, except your computer is connected to their local model for you to use.
Disc drives used to be measured in megabytes—now in terabytes. Technically useful tend to get more optimized with time, not less.