> and they seem - even with a lot of investment in agentic workflows and getting a lot of context into GraphRAG or wiring up MCP - to be good at helping experts get a bit faster, not replace experts. And that's not software development specific - it seems to be the case across all domains of expertise.
For now, this is a good thing: Given how generally LLMs are displacing juniors, if this was a situation where doing the same thing but harder can replace experts, it replaces approximately all of them.
But: in limited domains, not the "G" of "AGI" but just specific places here and there, AI does beat human experts. Those domains are often sufficiently narrow that they don't even encompass the entire role — think "can analyse an X-ray for cancer, can't write up its findings" kind of specificity. Indeed, I can only think of two careers where even the broadest definition of AI (some kind of programmable system) has been able to essentially fully replace that occupation:
For now, this is a good thing: Given how generally LLMs are displacing juniors, if this was a situation where doing the same thing but harder can replace experts, it replaces approximately all of them.
But: in limited domains, not the "G" of "AGI" but just specific places here and there, AI does beat human experts. Those domains are often sufficiently narrow that they don't even encompass the entire role — think "can analyse an X-ray for cancer, can't write up its findings" kind of specificity. Indeed, I can only think of two careers where even the broadest definition of AI (some kind of programmable system) has been able to essentially fully replace that occupation:
1. https://en.wikipedia.org/wiki/Jacquard_machine
2. https://en.wikipedia.org/wiki/Computer_(occupation)