Evals for AI Engineers Systematically Measuring and Improving AI Applications
Evals for AI Engineers: Systematically Measuring and Improving AI Applications by Shreya Shankar, Hamel Husain
English | November 17th, 2026 | ISBN: 9798341660724 | 238 pages | True EPUB (Retail Copy) | 5.84 MB
Stop using guesswork to find out how your AI applications are performing. Evals for AI Engineers gives you a practical framework for systematically testing, measuring, and improving AI applications, especially those built with LLMs. Written by Shreya Shankar and Hamel Husain, AI engineers with extensive experience across 35+ AI products and cutting-edge research, this book focuses on the techniques teams actually need to build reliable AI systems in production.
Ideal for software engineers, technical product managers, and technical leads, this hands-on guide shows you how to build an evaluation process that improves alongside your product.
* Find and prioritize failures through systematic error analysis and representative test sets
* Build trustworthy evaluations using code based checks, LLM judges, human feedback, and synthetic data
* Improve production systems over time by monitoring regressions and optimizing quality, latency, and cost
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