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 control sensitive data in OpenAI Agents SDK traces using trace_include_sensitive_data, environment variables, and GDPR-compliant tracing strategies for production AI systems.
Learn how to build production monitoring and alerting for AI agent systems including latency tracking, error rate dashboards, token usage analytics, alerting pipelines, and SLA enforcement.
Master the art of debugging multi-agent systems using OpenAI's built-in tracing infrastructure to trace handoffs, profile tool calls, and identify bottlenecks in complex agent pipelines.
Build custom trace processors and exporters for the OpenAI Agents SDK to ship agent telemetry to Elasticsearch, Datadog, or any backend using TraceProvider, BatchTraceProcessor, and BackendSpanExporter.
Learn how to choose the right OpenAI model for each agent in your system, comparing GPT-4.1, GPT-5, and GPT-5-mini across cost, latency, reasoning capability, and tool-use accuracy.
Integrate Anthropic, Google, Mistral, and other LLM providers into OpenAI's Agents SDK using LiteLLM's unified interface with LitellmModel, provider prefix notation, and cross-provider tracing.
Enable WebSocket transport in the OpenAI Agents SDK for persistent connections, reduced latency, and faster multi-turn agent interactions using set_default_openai_responses_transport.
Design and build a multi-tenant AI agent SaaS platform with user isolation, API key management, token metering, billing integration, and scalable infrastructure using the OpenAI Agents SDK.
