A staged collection of practical steps and exercises to help teams design, prototype, test, deploy, and monitor reliable AI assistants for real workflows.
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, step-by-step playbook for prototyping reliable AI agents: persona templates, memory patterns, tool integration contracts, scripted test flows, evaluation heuristics, and deployment readiness checklists.
Operational runbook to prevent, detect, and respond to agent misbehavior. Includes concise safety checklist, allowed/disallowed actions, example policy rules, concrete monitoring signals and thresholds, anomaly-detection patterns, a clear escalation and rollback flow, and a reusable post-incident review template.
Practical, operational checklist and templates to monitor agent behavior, enforce policy constraints, detect anomalies, and make agent actions observable and auditable. Includes signals, logging requirements, guardrail examples, escalation flows, KPIs, and periodic review guidance tailored for teams deploying autonomous agents or automated workflows.