AI agents are more than chatbots with tools. Before you build one, understand the core components - memory, planning, and tools - the levels of autonomy, and the pitfalls that derail most projects.

BigData Boutique blog

AI agents differ from chatbots by autonomously controlling workflow through iterative problem-solving rather than single-shot responses. They consist of three core components: memory (short-term, long-term, and working), planning/reasoning (decomposing goals into subtasks), and tools (APIs and external integrations). Autonomy levels range from operator assistance to full independence, with Level 2-3 being optimal for most production systems. Common pitfalls include building agents for deterministic workflows, poor tool definitions, lack of evaluation frameworks, and missing observability. Most production agents struggle with quality issues, and the engineering challenge lies in moving from demo to reliable production system.

Everything You Need to Know Before Building AI Agents

What Makes an Agent Different from a Chatbot

Levels of Autonomy: Not Every Agent Needs Full Control

What Goes Wrong: Pitfalls That Derail Agent Projects