Step-by-step tutorials on building voice and chat AI agents using OpenAI Agents SDK, Realtime API, function calling, multi-agent orchestration, and production deployment patterns.
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Learn how to create effective operational runbooks for AI agent systems, covering runbook design principles, step-by-step troubleshooting procedures, automation opportunities, and knowledge transfer practices.
Design effective on-call systems for AI agents with PagerDuty setup, rotation design, escalation policies, alert routing, and post-incident review processes tailored to the unique demands of autonomous agent systems.
Define and measure Service Level Agreements for AI agent systems with practical guidance on SLA definition, measurement methodology, automated reporting, and penalty handling for production agent deployments.
Implement canary deployments for AI agent systems with traffic splitting, health checking, automated rollback, and progressive delivery strategies that catch regressions before they affect all users.
Ensure database reliability for AI agent systems with high-availability setups, automatic failover, backup testing, disaster recovery planning, and connection management strategies that keep agents running through database failures.
Run effective post-incident reviews for AI agent failures using blameless retrospective techniques, structured PIR templates, timeline reconstruction, root cause analysis, and follow-up tracking to prevent recurring failures.
A full project walkthrough for building a production-grade customer support platform using multi-agent orchestration, tool integration, deployment pipelines, and real-time monitoring.
Build a complete retrieval-augmented generation knowledge base with document ingestion, semantic search, a chat interface for users, and an admin panel with analytics for managing content.
