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 measure AI agent conversation quality using automated scoring rubrics, LLM-as-judge patterns, and human correlation validation to ensure your agent produces coherent and helpful responses.
A hands-on guide to measuring AI agent latency at every stage of the pipeline, from time-to-first-token through tool execution to total response time, with percentile reporting and SLA compliance tracking.
Learn to accurately track and optimize the total cost of AI agent conversations including token usage, tool call expenses, infrastructure overhead, and strategies for reducing cost per interaction.
Learn how to evaluate multi-agent AI systems by measuring handoff accuracy, information retention across agents, routing correctness, and end-to-end coordination quality.
A practical guide to creating high-quality evaluation datasets for AI agents using synthetic data generation, human annotation pipelines, active learning for efficient labeling, and dataset versioning strategies.
Learn how to implement continuous evaluation for production AI agents with sampling strategies, real-time quality dashboards, alerting on quality degradation, and feedback loops that drive iterative improvement.
Understand how indirect prompt injection attacks work against AI agents, explore real attack vectors from web pages, emails, and tool outputs, and learn detection and prevention strategies to protect your agent systems.
Learn how to build robust permission models for AI agent tool access, including policy engines, dynamic permissions, role-based access control, and comprehensive audit logging for every tool invocation.
