In-context learning

In-context learning is the ability of a language model to pick up a new task from instructions or examples placed in its prompt, without any change to its underlying weights.

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

Also called ICL.