5 AI Agent Patterns Every Developer Should Know in 2026

AI agents are moving from research demos to production systems. But most tutorials still show toy examples. Here are 5 battle-tested patterns that actually work at scale. 1. ReAct (Reasoning + Acting) The most versatile pattern. The agent thinks about what to do, takes an action, observes the result, and repeats. def run_react_agent ( task , tools , max_steps = 10 ): messages = [{ " role " : " user " , " content " : task }] for step in range ( max_steps ): response = client . messages . create ( model = " claude-sonnet-4-20250514 " , tools = tools , messages = messages ) if response . stop_reason == " tool_use " : tool_results = execute_tools ( response ) messages . extend ([ { " role " : " assistant " , " content " : response . content }, { " role " : " user " , " content " : tool_results } ]) else : return response . content [ 0 ]. text When to use: General-purpose tasks — research, data analysis, customer support. 2. Router Pattern Instead of one agent doing everything, use a lightw