Reusable patterns for chaining agents, integrating tools, managing state, and building resilient multi-step automations.
Practical patterns, decision criteria, checklists, test scenarios, security controls, and example architectures to design, prototype, deploy, and maintain reliable multi-step AI agents that integrate into team workflows.
A practical blueprint describing reliable orchestration topologies, integration and state strategies, error-handling tactics, observability, testing guidance, and actionable checklists to compose agents and tools into resilient multi-step workflows.
Practical orchestration patterns, manifests, observability hooks, compensation strategies, idempotency approaches, and testing guidance to make multi-step agent workflows robust, recoverable, and maintainable.