Building
Evals
Tests that measure whether an AI system is actually doing its job well.
Evals, short for evaluations, are the checks builders run to see how well an AI performs on the tasks they care about. Instead of trusting a gut feeling, they score the model against real examples to catch mistakes and track improvements. Good evals are how a team knows whether a change made the AI better or worse before real users ever see it.
For example
Before launching a support bot, a team runs evals on hundreds of sample questions to check its answers.
Related
RAG (retrieval-augmented generation)Letting an AI look up real documents before it answers.AI agentAn AI that can take actions and complete multi-step tasks on its own.Tool useAn AI reaching outside itself to use calculators, search, or other software.MCP (Model Context Protocol)A common standard that lets AI plug into apps and data sources.