The blog post details a process for developing AI agents using Test-Driven Development (TDD) with the Eval Protocol, a pytest-centric framework aimed at ensuring reliability and structure in agent development. The author outlines their experience of building a digital store concierge agent capable of interacting with a music database, employing the AI coding assistant Cursor to convert high-level project ideas into a structured plan saved in a project.md file. The development environment was set up using a Postgres database and the Eval Protocol, facilitating the creation of machine-checkable tests that guide the agent's functionality. Initial tests focused on simple user requests, such as identifying Jazz tracks under a specific price, while subsequent tests incorporated safety measures like red teaming to prevent security risks. This TDD workflow, supported by AI-assisted scaffolding, observable testing, and a focus on safety, allows developers to build robust, reliable AI agents capable of evolving without unexpected regressions.