A dev’s guide to production-ready AI agents

At its core, an agent is an autonomous entity that reasons, takes action, and improves over time. The agent's brain is a large language model — a cognitive engine that understands tasks, generates responses, and makes decisions based on context. Unlike a static tool, an agent adapts as it works. It follows a recursive loop: Think, then Act, then Observe. Each cycle moves the agent forward, refining its approach as it goes.

Surrounding this core is the orchestration layer — the nervous system that manages communication and data flow. Think of it as a conductor coordinating specialized tools and external services. These include short-term memory (Session State) for immediate recall, long-term memory (Memory Service) for retaining past interactions, information retrieval (RAG), and modules for executing actions in the outside world (Tool Use). A security framework ensures the agent operates safely and within its intended boundaries. The goal of this architecture is ...