AI Agents Explained: How to Build with Them Safely | Docker

This post defines AI agents, distinguishing them from chatbots and generative AI by their autonomy and tool-use capabilities. It details the core components of an agent (model, tools, memory, orchestration, environment) and explains the agent loop (perceive, reason, act, observe, adapt). The post highlights the shift in software development towards treating agents as an infrastructure problem, emphasizing the importance of the execution environment for safety and security. It discusses common misconceptions and provides guidance on building and running agents safely, advocating for isolated, disposable environments like Docker Sandboxes and microVMs. It also introduces Docker's AI Governance for team-wide rule enforcement.