Python deps can be dynamic, so it can be necessary to download the package and execute code just to find out.
Would be nice to see a resource that lists out the statically defined ones, though. Perhaps that’d pressure the dynamic ones to change – it’s a cause for some of the notorious pain of Python packaging.
IMO it will “succeed” in the early phase. Pre-seed startups will be able demo and get investors more easily, which I hear is already happening.
However, it’s not sustainable, and either somebody figures out a practical transition/rewrite strategy as they try to go to market, or the startup dies while trying to scale up.
We’ll see a lower success rate from these companies, in a bit of an I-told-you-so-moment, which reduces over-investment in the practice. Under a new equilibrium, vibe coding remains useful for super early demos, hackathons, and throwaway explorations, and people learn to do the transition/rewrite either earlier or not at all for core systems, depending on the resources founders have available at such an early stage.
IMO it’s time for a reckoning of what’s systematic/automated vs what’s not.
For example, “no expectation of privacy in public” meant you should be okay with appearing in someone else’s (manual) photo while out in public. However, I don’t think that should extend to persistent systematic surveillance, e.g. suppose every Tesla’s camera captures were combined with person recognition systems and tracking.
Just because something is theoretically okay at a small scale doesn’t mean the same applies at large scales.
Another example: Society funds public roads via government taxes for personal use and for regulated commercial use. Uber systematically consumes public road space under the guise of personal use vehicles, for commercial use.