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The Evolution of AI: From Agents to Agentic Workflows
In recent years, the world of artificial intelligence has witnessed a significant shift in focus from AI agents to agentic workflows. This transition represents a leap forward in how we approach automation and decision-making processes. Let’s explore why this change is occurring and what it means for the future of AI.
Understanding AI Agents and Agentic Workflows
Before we dive into the reasons for this shift, let’s clarify the key differences between AI agents and agentic workflows.
AI Agents
AI agents are specialized programs designed to perform specific tasks autonomously. They operate within predefined frameworks and can adapt to certain inputs, but their scope is generally limited to their programming.
Agentic Workflows
Agentic workflows, on the other hand, represent a more advanced and holistic approach. They involve multiple AI agents working together to handle complex, multi-step processes. These workflows can learn, adapt, and make decisions across various domains, offering a higher level of autonomy and flexibility.
