The case for context engineering in scientific AI
Talks & Insights · · 4 min read
On February 17, 2026, Anthony Kougkas spoke at the monthly meeting of Earth Science Information Partners (ESIP) on context engineering for environmental data systems. His argument, first made at an Illinois Tech seminar six days earlier, was that AI agents in science fail or succeed on the quality of the context they receive, not on the size of the model.