> If GPT-4 had ingested the entire code-base code reviews would easily be automated, humans would still do their passes but as a co-worker GPT would be invaluab

> If GPT-4 had ingested the entire code-base code reviews would easily be automated, humans would still do their passes but as a co-worker GPT would be invaluable. It would find swaths of missed efficiencies, fix slow SQL queries, look for testing gaps, and perhaps even assist in refactoring. This is where my 3-5x efficiency improvement estimate came from for GPT4-based Copilot, especially for CRUD apps using popular frameworks, which while game changing is far from the great efficiency gains programming has seen in the past. Compilers have conservatively led to 100x-1000x gains of efficiency at scale as have operating systems and various key libraries. GPT-assisted code generation doesn't yet seem to offer the same result. Even if it did, if history is our guide, this would lead to developers being able to generate far more economic value with less, which has consistently led to more developer jobs than before. > Personally I think we are underestimating the potential, I feel like we are where the world was in 1990 looking at the emerging internet. It doesn't feel correct to me to think of GPT-x as some technology similar to the internet as much as it is a way of experiencing the already existing internet, like a smart, context-aware search for specific details (though there aren't any good analogies for the role LLMs play/will play in tech moving forward.) If search engines had continued to improve with the momentum they had in the early days, we should've expected some experience not unlike GPT a decade ago (or more.) > However, small studios do because they are cheap and serve a purpose where it's just WordPress maintenance and HTML POCs. Those jobs will disappear. That seems very possible.