Building Applications with AI Agents

Chapter 1. Introduction to Agents

We are witnessing a profound technological transformation driven by autonomous agents—intelligent software systems capable of independent reasoning, decision making, and interacting effectively within dynamic environments. Unlike traditional software, autonomous agents interpret contexts, adapt to changing scenarios, and perform sophisticated actions with minimal human oversight.

Defining AI Agents

Autonomous agents are intelligent systems designed to independently analyze data, interpret their environment, and make context-driven decisions. As the popularity of the term “agent” grows, its meaning has become diluted, often applied to systems lacking genuine autonomy. In practice, agency exists on a spectrum. True autonomous agents demonstrate meaningful decision making, context-driven reasoning, and adaptive behaviors. Conversely, many systems labeled as “agents” may simply execute deterministic scripts or tightly controlled workflows. Designing genuinely autonomous, adaptive agents is challenging, prompting many teams to adopt simpler approaches to achieve quicker outcomes. Therefore, the key test of a true agent is whether it demonstrates real decision making rather than following static scripts.

The rapid evolution of autonomous agents is primarily driven by breakthroughs in foundation models and reinforcement learning. While traditional use cases with foundation models have focused on generating human-readable outputs, the latest advances ...