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 orchestrate AI agent workflows with Apache Airflow. Covers DAG design patterns, custom operators for LLM calls, XCom data passing, sensors, and scheduling strategies.
Learn how to build AI agent automations with n8n. Covers workflow design with AI nodes, triggers, integrations with 400+ services, and self-hosting for full control over your agent infrastructure.
Learn how to build event-driven AI agent workflows with Inngest. Covers event triggers, step functions, automatic retries, fan-out patterns, and rate limiting for production agent systems.
Learn when and how to build a custom agent orchestrator. Covers state machine design, queue integration, monitoring hooks, and the architectural patterns that make custom orchestrators maintainable.
A detailed comparison of Temporal, Prefect, Apache Airflow, and custom-built orchestrators for AI agent workflows. Covers scaling, complexity, team fit, cost, and decision criteria.
Learn how to version and migrate AI agent workflows safely. Covers versioning strategies, backward compatibility patterns, migration techniques, and rollback procedures for zero-downtime updates.
Learn how to build observability into AI agent orchestration systems. Covers dashboard design, metric collection, alert rules, trace correlation, and debugging strategies for agent workflows.
Learn how to implement slot filling patterns in conversational AI agents that collect required information through natural, multi-turn dialog instead of rigid form-like interactions.
