Demystifying AI Agents: Uncovering their Capabilities, Applications, and Construction

Demystifying AI agents, Googlers Aja Hammerly and Jason Davenport provide a comprehensive overview of their capabilities, applications, and construction. In this article, we will delve into the diverse definitions of AI agents, explore compelling use cases, and discuss the different architectural approaches for building intelligent agents.

Introduction to AI Agents

AJA HAMMERLY: Hey, Jason. What's today's topic? JASON DAVENPORT: Agents. As Aja Hammerly and Jason Davenport introduce the topic, they acknowledge that the term "agent" is often used but not clearly defined. Introduction to AI Agents They begin by questioning what exactly an agent is, with Jason noting that "no one seems to agree what exactly an agent is." Aja shares her mental model of an agent as "an AI with a job and the tools necessary to do that job."

Defining AI Agents

Defining AI Agents Jason suggests thinking of an agent like a customer service agent, which helps individuals accomplish tasks more effectively. Aja mentions that some folks say agents must act autonomously, but this term is also vague. They discuss how an agent that uses tools to research a topic and then summarizes the results for the user could be considered autonomous to some degree.

Agentic Systems Examples

Agentic Systems Examples Aja and Jason provide various examples of agentic systems, including an agent that helps review emails and create tasks, an agent that uses weather data to decide when to water a garden, and an agent that responds to bug reports. These examples demonstrate the diverse range of applications for agents.

Agentic Architectures

Agentic Architectures They discuss how agents can be built using different architectures, including those that incorporate large language models (LLMs) and those that do not. Aja notes that an agent doesn't necessarily need to incorporate an LLM and that simple, hard-coded algorithms can be used to achieve a goal.

Building Agents

Building Agents Jason and Aja emphasize the importance of considering the specific requirements of the agent being built. They discuss how agents can work together to accomplish a goal, such as a shipping agent and a customer service agent interacting to resolve an issue.

Getting Started with Agent Building

Getting Started with Agent Building For those interested in building agents, Aja and Jason recommend starting with simple business logic and an interface to enable interaction with the environment or user. They also suggest exploring frameworks for building agents, such as Vertex AI Agent Builder, and tutorials using different approaches and degrees of agenticness.

Agent Interactions and Collaborations

Agent Interactions and Collaborations They discuss how agents can interact with each other to improve output, such as a blog post producer agent and a critic agent that refines the post until it meets the desired standards.

Conclusion and Next Steps

Conclusion and Next Steps In conclusion, Aja and Jason emphasize that the concept of an agent is complex and multifaceted, and that it's more important to focus on the degree of agenticness rather than a specific definition. They encourage viewers to explore the provided tutorials and resources to get started with building their own agents, and they look forward to seeing the innovative applications that will be created.