At its heart, agentic AI is a paradigm shift marked by multi-agent collaboration, dynamic task decomposition, persistent memory, and coordinated autonomy. Unlike a standard AI agent that follows a rigid script, an Agentic AI system is the overarching framework that orchestrates one or more agents, maintaining their memory and allowing them to collaborate to achieve complex multi-step objectives. The term itself was coined and popularized by AI pioneer Andrew Ng, who argues that agentic workflows will drive massive AI progress this year, perhaps even more than the next generation of foundation models.
Absolute autonomy is rarely desired in high-stakes environments. Cognitive architectures must include deterministic checkpoints that mandate human approval. Common HITL triggers include: the agentic ai bible pdf new
Multi-step reasoning loops require frequent, expensive LLM API calls. At its heart, agentic AI is a paradigm
: Focuses on building self-directed systems that can perceive and reason independently. : Focuses on building self-directed systems that can
The Agentic AI framework consists of the following components: