The Anatomy of an Autonomous Agent | by Eric Broda

A blueprint for autonomous agents in an Agentic Mesh ecosystem

Recent massive investment by tech giants almost guarantee that an ecosystem of autonomous agents will soon be upon us. But what is an “autonomous agent”?

Sebastian Thielke, Platform Economics Lead at AWS, describes it like this (paraphrasing): “An autonomous agent reacts to environmental stimuli, is proactive in pursuit of a goal(s), has social interaction capabilities, and can continuously learn and improve”. Wikipedia offers a similar definition: “autonomous agents are computational systems that inhabit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks for which they are designed.” And in a previous article, I offered the following definition which I think captures both: autonomous agents use agentic AI (sophisticated reasoning and iterative planning) to independently plan and execute tasks.

With that out of the way, I want to get to the primary focus of this article: What does an autonomous agent (hereinafter called an “agent”) architecture look like, and what are its major components? What capabilities need to be in place to create a “smart” agent that can plan and execute tasks? And since no agent stands alone but rather works in an ecosystem of…