Eval Engineering: A Beginner’s Guide

AI agents can execute all visible steps and appear successful, yet fail the actual task by fabricating details not supported by their tools. This discrepancy between perceived response quality and faithfulness to tool results highlights the need for eval engineering. Eval engineering is a critical skill that goes beyond prompting to rigorously question whether an agent has truly completed its job using the right evidence and an acceptable process.

• AI agents can complete visible steps and reach an ‘END’ state without succeeding in the actual task.
• A common failure mode is when agents invent details not supported by their tool results, leading to incorrect or unfaithful outputs.
• Eval engineering is a crucial skill that verifies if an agent completed its job with the right evidence and through an acceptable path.
• While prompts, context, loops, and graphs guide agent actions, evals determine if that work is valid and deserves to proceed.
• The article outlines how to build eval engineering skills from scratch, covering defining promises, creating core files, installing tools, generating test cases, and implementing various checks for tool-using agents.
  https://bender.layer3.press/articles/e34992f2-4438-4e8e-820c-254df6d98677