What Is the AI Evals for Engineers and PMs Course on Hamel's Blog?

The course is a co-taught program on AI evaluations ("evals") aimed at engineers and product managers, listed on hamel.dev under "Learn With Me." The site says it has drawn over 5,000 students from 500+ companies, including OpenAI, Anthropic, and Google. It is the main teaching offering behind Hamel Husain's stated focus: helping teams debug, analyze, and measure AI systems. The page does not list a price, schedule, or enrollment requirements, so those details must be checked on the course page itself, where upcoming cohorts are posted.

Who it is for

The course is explicitly positioned for two audiences:

• Engineers building or maintaining AI/LLM products who need to measure whether changes improve or degrade behavior.
• Product managers who need to reason about quality, failure modes, and evaluation tradeoffs without treating evals as a purely technical afterthought.

It is not described as an introductory machine learning course. The author's framing assumes you are working on applied AI products and want to make evaluation a practical part of the development loop.

What "evals" means in this context

Hamel Husain describes evals as the work of helping teams "debug, analyze, and measure their systems." In practice, that means building repeatable ways to check whether an AI product behaves correctly—rather than relying on spot checks or intuition. The blog's related writing covers decision models for evals, automated evals, LLM-as-a-judge, and selecting eval tools, which indicates the course sits on top of a substantial body of applied material rather than abstract theory.

A concrete example of the problem the course addresses: a team changes a prompt or model and cannot tell whether support-answer quality went up or down. Evals give them a defined set of cases, a scoring approach, and a way to compare versions before shipping.

What the site tells you about format and access

Because price, dates, and prerequisites are not on the blog page, treat the course page as the source of truth before committing. The mention of named companies reflects the site's own claim about past participation, not an endorsement you can independently verify from the page.

How to decide whether it fits you

Use these conditions to judge fit:

• Choose the course if you are shipping an AI product and need a structured method for evaluation, and you want material aimed at both technical and product roles.
• Start with the free writing first if you are still exploring. The site links an "AI Evals Guide" for common questions and hosts long-form posts such as "AI Evals: Everything You Need to Know," "Your AI Product Needs Evals," and "Selecting The Right AI Evals Tool." Reading one or two of these will tell you whether the author's approach matches how your team works.
• Look elsewhere if you want a general machine learning or model-training curriculum; the stated focus here is measurement and debugging of AI systems, not model building.

Practical next steps

1. Open the "Learn With Me" section of hamel.dev and follow the link to the course page for cohort dates and enrollment details.
2. Read the AI Evals Guide for answers to common questions before enrolling.
3. Skim one long-form post on a problem you actually have—for example, automated evals or LLM-as-a-judge—to test whether the teaching style and depth suit you.
4. Confirm cost, time commitment, and any prerequisites on the course page, since the blog page does not provide them.

The blog also offers a newsletter for updates, which is a low-commitment way to see new material on evals before deciding on the paid program.