As AI models improve, agents are becoming more prevalent and capable, prompting the need for formal definitions to clarify their use.

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

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.

A simple definition of an agent is a clever prompt on top of a knowledge base or context, resembling a human agent's interaction.

An AI agent is defined as a system that allows a language model to autonomously decide how many times to run processes until it finds a resolution, rather than following a predefined path.

AI agents are often defined as systems that perform complex planning and interact with external systems, but this definition overlaps with many current language models.

An agent is something a human can delegate tasks to, and we're aiming for agents to handle more complex tasks over time.

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.

The concept of agents includes both those that replace human tasks and those that operate as low-level system processes, complicating the definition further.