Enterprise AI Needs More Than an AI Engineer
InfoWorld, Tuesday, October 20th, 2026
Matt Asay argues AI success depends on pairing engineers with domain experts who know which data actually matters.
Matt Asay points to Anthropic's plan to train 10,000 frontier deployed engineers as a sign that AI's hardest problems are about people.
He argues that developers must work with business experts who can make distinctions explicit, such as superseded policies or conflicting definitions of a customer, and build examples that catch errors.
He cites a PwC finding that top AI performers were twice as likely to redesign workflows.
Bridgewater's Vault repository is his example: an agent left on its own used stale July research, but once connected to the curated store it pulled seven documents from the right October window.