Agentic applications are premised on basic LLM related skills like decomposing a problem into smaller sub-tasks, and leveraging reasoning to move from task to task, by observing and assessing each task.
The Self-Discover approach allows Large Language Models Automatically Compose Their Own Reasoning Structures.