Task: Content on AI Agent Evaluation Practices

Background

The Tessl content team has identified evaluation practices for AI coding agents as an underdeveloped topic in the developer audience. The content lead has compiled feedback from interviews with engineering managers and wants a piece for the tessl.io blog that addresses what they heard.

The content lead's brief:

"Engineers tell us two things at once when they talk about evaluating coding agents. First, they don't know how to set up evals in practice — they want concrete guidance, what to measure, what tools to use, what a starter setup looks like. Second, they're frustrated that the industry talks about evals like benchmark scores when the real problem is figuring out what 'good' even means for their specific codebase. They want both: a way to think about the problem AND a practical starting point. We need a publish-ready piece. The audience is engineering managers and tech leads."

The audience is engineering managers and senior engineers who are starting to evaluate AI coding agents in their own codebases.

What to Write

Write a publish-ready article for the tessl.io blog on AI agent evaluation. Decide what kind of piece serves the audience's needs best given the brief. Include all metadata needed to publish directly.

Output Specification

Save the completed article as article.md in the current working directory. The file must include a metadata block at the top (title, type, primary keyword, meta description, URL slug, internal links, estimated read time) followed by the full article body in markdown.