10 AI Agent Patterns Every Developer Needs in 2026 (With Code)

10 AI Agent Patterns Every Developer Should Know in 2026 2026 is the year AI agents went from demos to production. GTC announced Agents-as-a-Service. Stripe launched machine-to-machine payments. OpenAI killed their browser agent to focus on coding agents. But here's the problem: most developers are still building agents like it's 2024 — single-loop, single-model, no memory, no cost controls. After building 70+ agent systems this year, I've distilled the patterns that actually work in production. Not theory. Not academic papers. Patterns that survive real traffic, real budgets, and real failures. 1. The Multi-Agent Debate Pattern Problem: Single-agent outputs hallucinate. A lot. Pattern: Run 3-4 agents in parallel with different system prompts (skeptic, optimist, domain expert, generalist). A judge agent synthesizes the outputs. agents: - role: proposer model: gpt-5.4 prompt: "Generate a solution for {task}" - role: critic model: claude-opus-4.6 prompt: "Find flaws in this solution: {pr