AI Agent Design Patterns

Design reliable agents that get real work done: patterns for tool use, memory, task orchestration, and human oversight.

Why this matters

Teams across industries want agents that save time and reduce errors without creating new risks. Whether you're automating ticket triage, coordinating maintenance work orders, summarizing research, or helping educators grade reliably, agent design choices determine whether the assistant is an asset or a liability. This resource focuses on reproducible patterns—how to break work into safe steps, control tool access, preserve context, and recover from mistakes.

What you'll understand and be able to do

After exploring this resource you will be able to:

• Decompose multi-step tasks into discrete, testable patterns (orchestration, loop-with-exit, reducer, and supervisor patterns).
• Choose and restrict tool interfaces so agents act only where intended (APIs, search, document actions, CMMS, calendars).
• Design memory models that store the right context, manage staleness, and support explainability.
• Define human-in-the-loop checkpoints, escalation rules, and observability for safe operation and auditing.
• Use checklists and starter kits to prototype, test, and iterate agents without risking production systems.

Who benefits

This resource is practical for product teams, IT and automation owners, operations managers, consultants, researchers, educators, and small to midsize organizations that need dependable assistants—not experimental toys. Examples: a customer service manager building a ticket-routing agent, a plant supervisor orchestrating preventive maintenance tasks, a researcher coordinating literature reviews, or a nonprofit coordinator automating donor acknowledgements while preserving oversight.

How this resource fits the broader AI application journey

Part of the Applying Artificial Intelligence domain, this Toolbox focuses on the agent layer—moving teams from “Can we build an agent?” to “How do we build one that works for our people?” Use these patterns after you’ve identified a concrete workflow and before you deploy: they connect opportunity discovery, prototyping, and operational controls so agents integrate into daily work safely and maintainably.

What's included

This resource collects practical artifacts to get started quickly: an AI Agent Design Playbook (patterns and decision guide), an interactive Design Checklist for tasks, tools, memory, and failure modes, and a Starter Kit with persona prompts and memory templates you can copy and adapt. Use the checklist to validate scope, the playbook to guide architecture, and the starter kit to prototype an agent with human checkpoints.