The definition of an agent may evolve as we explore the capabilities of AI, particularly in how they interact with users and perform tasks.

As AI agents become more prevalent, the management mindset will need to adapt to understand what these agents can and cannot do, leading to more complex managerial decisions.

There's significant disagreement on what constitutes an AI agent, with varying definitions emerging from both technical and marketing perspectives.

One overhyped aspect of AI agents is their perceived capabilities, while the underhyped aspects include the importance of understanding when and how to use them effectively in production, as well as how they can save people time by automating tasks that take only a minute, significantly changing dynamics and allowing you to perform those tasks many more times than before.

As AI agents begin to work more with each other, the dynamics of their communication and reasoning may evolve significantly.

The behavior of AI systems is not just about what they produce but also how they produce it, which can significantly impact user trust.

The evolution of AI agents will lead to more complex use cases as users gain trust in their capabilities, allowing them to handle more advanced tasks.

There's a lot of excitement around AI agents, but many people are unsure of their practical applications, often trying to apply them to problems that simpler solutions could address.

The core AI agent acts as the brain of the system, handling logic, knowledge, and workflows, similar to how human agents are trained.