Lost in the middle

Lost in the middle is the observed tendency of language models to use information at the beginning and end of a long context more reliably than information placed in the middle.

Lost in the middle sits in the Prompting & context part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.