AI Agents are SO simple to build

Understanding AI Agents: Building Blocks and Functionality

Basics of AI Agents

• AI agents are fundamentally simple to construct, primarily consisting of a while loop and tool calls.

• They operate by repeatedly calling Large Language Models (LLMs), adding new messages to the message history with each iteration.

• The process includes a step counter to prevent infinite loops, allowing for a maximum of five iterations.

Tool Invocation and Message Streaming

• During execution, the agent streams text from an LLM to the console, indicating successful operations like file writing.

• The finish reason from the LLM is crucial; it determines when the model believes it has completed its output.

Step Count and Loop Mechanics

• Each interaction with the LLM counts as a step; in this example, two steps were taken—one for invoking a tool and another for summarizing results.

• Advanced frameworks can abstract away manual handling of loops and message histories, simplifying agent development.

Conclusion on Agent Simplicity

• Overall, agents are straightforward constructs that rely on iterative communication with LLMs to determine subsequent actions based on user input.