Agentic AI Explained: Workflows vs Agents

The emergence of agentic AI systems marks a transformative shift in artificial intelligence, emphasizing autonomous decision-making and goal-oriented processes. These systems, categorized into AI agents and agentic workflows, operate independently, adapting to changing environments and learning from outcomes without explicit step-by-step instructions. AI agents are standalone entities equipped with reasoning capabilities, often driven by large language models (LLMs), and are suited for dynamic tasks like chatbots or coding assistants. In contrast, agentic workflows are complex, orchestrated processes that integrate multiple agents, APIs, and even human inputs to manage multi-step tasks that require governance and reliability, making them ideal for enterprise environments. Orkes Conductor is highlighted as a platform that facilitates the creation of these workflows, providing tools for orchestration, integration, and observability, thus enabling the deployment of intelligent automation systems with built-in governance and adaptability.

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