AI Agents: Autonomous Systems, Tool Use & ReAct Patterns
Understand AI agents — autonomous systems that perceive, plan, use tools, and execute actions to accomplish complex goals. AI agents represent the next evolution of artificial intelligence — systems that don't just generate text but can perceive their environment, make plans, use tools, and take actions to accomplish goals autonomously. They are transforming how we think about AI, from passive chatbots to active digital workers. What is an AI Agent? An AI agent is a system that can autonomously pursue goals by perceiving its environment, reasoning about actions, and executing those actions to achieve desired outcomes. Unlike a simple LLM that responds to prompts, an agent maintains state, uses tools, and can work toward multi-step objectives. Key characteristics of agents include autonomy (operating without human intervention for each step), goal-directed behavior (working toward specific objectives), tool use (interacting with external systems and APIs), memory (maintaining context across interactions), and planning (breaking complex tasks into manageable steps). The ReAct Pattern ReAct (Reasoning + Acting) is the most influential agent architecture. It interleaves reasoning traces with actions, allowing the agent to think about what to do, take an action, observe the result, and adjust its plan. The typical ReAct loop works like this: Thought — the agent considers the current state and what needs to be done next. Action — the agent selects and executes a tool or action. Observation — the result of the action is fed back to the agent.