AI Agent Evaluation

Benchmarking and Testing Agent Quality for Product Leaders
Erscheinungsjahr 2027
ISBN: 978-3-032-41056-6
Verlag: Springer

Buch, Englisch, 330 Seiten, Format (B × H): 155 mm x 235 mm

AI agents can impress in a demonstration and still fail when users, tools, costs, and policies collide. Product leaders need a practical way to decide what good means, what evidence a release must produce, and when an agent should be held back.

AI Agent Evaluation is written for product managers, founders, educators, and technical leaders, including readers without a computer science background. It explains each idea in plain language and moves from product decision to measurement method. Readers learn todefine an Agent Contract, evaluate behavior, capability, reliability, and safety, and track cost and latency alongside quality.

The book shows readers how to apply Evaluation-Driven Development. Teams define acceptance criteria before changing an agent, compare every version with a trusted baseline, and turn production failures into repeatable tests. The book covers rubrics, deterministicchecks, LLM-based judges, benchmark design, regression gates, stress testing, human review, observability, authorization, prompt and context governance, and continuous improvement.

Four recurring examples in sales, healthcare, booking, and coaching show how the same evaluation discipline travels across domains and technology stacks. Practical checklists, worksheets, templates, and guided AI-assistant workflows help readers apply the methods to their own products. The result is a practical operating discipline for making AI agent quality measurable, auditable, and actionable.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Mansoor, Abdullah

Bokhari, Fawaz

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Technische Informatik Eingebettete Systeme
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Bauelemente, Schaltkreise

Inhaltsverzeichnis

The AI Agent Illusion.- Why Evaluation Matters More Than Building.- A Brief History of Notorious AI Failures.- Why Agents Fail in Production (Patterns & Antidotes).- The Agent’s Contract – Defining “Done Right”.- The Business Lens – Proving Value in the Wild.- AI Agent Frameworks.- Evaluating Behavior and Quality.- Evaluating Capabilities and Knowledge.- Evaluating Reliability and Robustness.- Evaluating Safety and Ethics.- Tracking Efficiency and Budget Adherence.- Data, Telemetry, and Governance.- Vendor/Model Variance & Reproducibility.- Metrics & Methods that Survive Production.- Human-in-the-Loop Benchmarking.- Evaluation-Driven Development (EDD).- Adaptive Stress Testing and Scaling Up.- Toward a Unified Evaluation Stack.- The AI Quality Movement.- From Feature to Learning System: Your Toolk it for Monday Morning.

Über Autor(innen)

Abdullah Mansoor is an AI engineer and researcher with a PhD focused on artificial intelligence from Portland State University. He is Co-Founder of InklyAI.io and Chief Strategy Consultant at Kogents.ai. He spent a decade at Intel, working across design automation, software research, data systems, and machine learning for chip design. His doctoral research applied reinforcement learning to monolithic 3D integrated-circuit placement. He now focuses on AI agent evaluation and Evaluation-Driven Development.

Fawaz Bokhari is Director of Technical Strategies and Partnerships at Senarios and Co-Founder of PoochoAI, an on-premises multilingual voice-agent platform. He has worked across software development, AI and machine learning, large-scale data systems, and technology education. He co-authored Object-Oriented Design Interview: An Insider's Guide. He earned a PhD in Computer Science and Engineering from the University of Texas at Arlington and is a Fulbright Scholar.