AI Agent Design Patterns

Your AI "Tech Debt" is Exploding. Here's Why.

Production AI agents need standard patterns. Without them, teams run into tech debt, cascading failures, and agent sprawl fast.

The Only 6 AI Agent Patterns You'll Ever Need

Six agent patterns cover every major control-flow choice in production AI systems. This overview shows why a seventh pattern adds nothing.

The Single Agent Pattern — Deep Dive

Deep dive into the single agent pattern — the simplest agentic architecture where one LLM instance with registered tools handles the entire workflow.

The Sequential Agent Pattern — Deep Dive

Deterministic execution order with shared session state flowing data between specialized sub-agents via output_key and template variables.

The Parallel Agent Pattern — Deep Dive

Concurrent execution for independent subtasks using fan-out/fan-in architecture. Covers parallel dispatch, session state collection, and sequential aggregation.

Stop Hardcoding Your Agents: Master the Coordinator Pattern

LLM-driven agent to dynamically route requests to specialist sub-agents at runtime using ADK's transfer_to_agent mechanism.

Stop Delegating, Start Controlling: The Agent-as-Tool Pattern

Wrapping specialist agents as callable functions that a primary agent invokes on demand. Unlike coordinator-style delegation, the primary agent retains full control.

Stop Shipping AI Hallucinations: The Loop & Critique Pattern

Quality-control layer for agent workflows: a generator produces output, a critic checks hard constraints, loop retries until result passes or safety cap is hit.