AI evals have been the "it" skill for product teams for over a year. I've even called evals a new discovery habit. But I still meet product teams who only have a vague idea of what evals are. And it's not their fault. Most of the writing on this topic is intended for engineers or just isn't specific enough. I recently created an in-depth eval guide to explain what evals are and why product teams can and should create them. I did my best to make it practical, hands-on, and easy to follow. AI evals (short for evaluations) are methods for measuring whether an AI product or workflow is performing well. Evals give teams confidence that their AI applications are doing what they expect them to do. They help teams maintain quality and catch issues before they reach users. Similar to other discovery habits like interviewing and assumption testing, evals can act as a feedback loop to ensure we are on the right track. If you want to learn more about this new discovery habit, explore my new guide: