The core insight that enterprises select products on familiarity over anything else, is valuable. I’m going to keep it in mind for future customer engagements.

> And they put it succinctly: buying from a small innovative company is brave while buying from a big, well recognised name is an insurance policy and the risk-averse buyer must have the insurance.

As the article notes, the alternatives from the large companies suck. So this is like buying fire insurance from a company that promptly sets fire to your house. You are buying the insurance while knowing you will need it because the disaster is already happening.

"When the software is being written by agents as much as by humans, the familiar-language argument is the weakest it has ever been - an LLM does not care whether your codebase is Java or Clojure. It cares about the token efficiency of the code, the structural regularity of the data, the stability of the language's semantics across releases."

Isn't familiarity with the language even more the case with a LLM. The language they do best with is the one with the largest corpus in the training set.

> Enterprise knowledge has always been as much a human problem as a technology one. Nobody wants to do the structuring work, and every prior architecture demanded that somebody do the structuring work rather than their actual job

This is correct and very agreeable to everyone, but then after some waffle they then write this:

> Structure, for the first time, can be produced from content instead of demanded from people

These quotes are very much at odds. Where is this structure and content supposed to come from if you just said that nobody makes it? Nowhere in that waffle is it explained clearly how this is really supposed to work. If you want to sell AI and not just grift, this is the part people are hung up on. Elsewhere in the article are stats on hallucination rates of the bigger offerings, and yet there's nothing to convince anyone this will do better other than a pinky promise.