> Here’s the reality check: One panelist mentioned that 95% of AI agent deployments fail in production. Not because the models aren’t smart enough, but because the scaffolding around them, context engineering, security, memory design, isn’t there yet.

It's a big pet peeve of mine when an author states an opinion, with no evidence, as some kind of axiom. I think there is plenty of evidence that "the models aren't smart enough". Or to put it more accurately, it's an incredibly difficult problem to get a big productivity gain when an automated system is blatantly wrong ~1% of the time but when those wrong answers are inherently designed to look like right answers as much as possible.