There's so much white space - this is the cost of a brand new technology. Similar issues with figuring out what cloud tools to use, or what python libraries are most relevant.
This is also why not everyone is an early adopter. There are mental costs involved in staying on top of everything.
> This is also why not everyone is an early adopter.
Usually, there are relatively few adopters of a new technology.
But with LLMs, it's quite the opposite: there was a huge number of early adopters. Some got extremely excited and run hundreds of agents all the time, some got burned and went back to the good old ways of doing things, whereas the majority is just using LLMs from time to time for various tasks, bigger of smaller.
I follow your reasoning. If we just look at businesses, and we include every business that pays money for AI and one or more employees use AI to do their their jobs, then we're in the Early Majority phase, not the Innovator or Early Adopter phases.
This is also why not everyone is an early adopter. There are mental costs involved in staying on top of everything.