Evaluation-Driven Agentic Systems: From Design to Deployment equips AI practitioners, engineers, and product leaders with the tools, frameworks, and workflows to build autonomous agents that perform reliably, safely, and efficiently. In a landscape where agentic systems are tasked with planning, tool usage, multi-step workflows, and continuous adaptation, how can you ensure they meet business objectives, align with human expectations, and maintain operational integrity? This book provides a systematic, practical answer.
Through clear, tutorial-driven guidance, you will learn to implement Evaluation-Driven Development (EDD): a methodology that embeds evaluation at every stage of agent creation and deployment. From defining business-aligned evaluation goals to constructing scenario sets, designing metrics matrices, setting thresholds, and integrating evaluation into CI/CD pipelines, this book ensures agents are rigorously assessed before reaching production. It also covers advanced practices such as monitoring live agents, detecting drift, handling multi-agent interactions, and applying ethical and safety checks, ensuring your systems remain accountable and aligned over time.
Readers will gain practical skills and actionable insights to:
Translate business objectives and user requirements into measurable evaluation goals and success criteria.
Design comprehensive evaluation suites with normal, edge, adversarial, and load-testing scenarios.
Implement multi-dimensional metrics, dashboards, and thresholds to measure task success, planning efficiency, tool usage, and user alignment.
Integrate automated evaluation pipelines into CI/CD workflows for continuous monitoring and regression detection.
Handle agent updates, versioning, and emerging behaviors while maintaining alignment, safety, and governance.
Scale evaluation from single agents to multi-agent systems, ensuring robustness and reliability across complex workflows.
Each chapter combines hands-on code examples, templates, rubrics, and checklists with expert commentary, making it immediately applicable in real-world development and operational environments. The book empowers readers to confidently deploy agents that are tested, traceable, and consistently performant, avoiding common pitfalls and operational risk.
If you are designing autonomous systems, managing AI deployments, or building agentic workflows that require reliability, safety, and measurable impact, Evaluation-Driven Agentic Systems: From Design to Deployment is your essential, practical guide to building agents that meet today’s complex requirements while preparing for the AI challenges of tomorrow.
