alt Hacker NewsYeah, the graphs make some really big assumptions that don't seem to be backed up anywhere except AI maximalist head canon.
There's also a gap in addressing vibe coded "side projects" that get deployed online as a business. Is the code base super large and complex? No. Is AI capable of taking input from a novice and making something "good enough" in this space? Also no.
The later remarks are very strong assumptions underestimating the power AI tools offer.
AI tools are great at unblocking and helping their users explore beyond their own understanding. The tokens in are limited to the users' comprehension, but the tokens out are generated from a vast collection of greater comprehension.
For the novice, it's great at unblocking and expanding capabilities. "Good enough" results from novices are tangible. There is no doubt the volume of "good enough" is perceived as very low by many.
For large and complex codebases, unfortunately the effects of tech debt (read: objectively subpar practices) translate into context rot at development time. A properly architected and documented codebase that adheres to common well structured patterns can easily be broken down into small easily digestible contexts. i.e. a fragmented codebase does not scale well with LLMs, because the fragmentation is seeding the context for the model. The model reflects and acts as an amplifier to what it's fed.