Promptfoo is an open‑source framework that lets AI developers automate prompt evaluation, compare large‑model outputs, and perform red‑team security scans, turning LLM application development from guesswork into a measurable, engineering‑driven process.
This article explains how to treat prompt engineering as a systematic, experiment‑driven practice—distinguishing it from blind prompting—by defining problems, building demo sets, crafting and testing prompt candidates, evaluating accuracy versus cost, and establishing verification loops for reliable large language model applications.
This guide explains how to systematically evaluate industry‑specific AI agents by testing the combined model and engineering stack, building domain‑expert‑driven datasets, designing reproducible testing systems, managing assets, controlling costs, and applying both traditional and LLM‑based methods to ensure reliable, stable performance.
This article walks through the challenges of traditional traffic replay, explains the design of a conventional replay system, and then details a novel LLM‑powered solution that automates data preparation, script generation, validation, and continuous integration for backend service testing.
