Hamel Husain – AI Evals For Engineers & PMs

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Hamel Husain – AI Evals For Engineers & PMs

Evaluating AI systems isn’t just about running benchmarks,

it’s about designing the right evaluation strategy that aligns with real-world applications.

In AI Evals For Engineers & PMs, Hamel Husain breaks down the core principles of evaluation for

machine learning and generative AI systems, equipping both engineers and product managers

with the frameworks, tools, and mental models to assess performance effectively.

Why This Course Matters

As AI becomes mission-critical, evaluation is the backbone of trust, safety, and product success.

Engineers often struggle with incomplete metrics, while PMs lack the technical grounding to interpret results.

This course closes that gap with practical evaluation methodologies you can immediately

apply to your projects.

Core Takeaways

Evaluation Frameworks That Work – Go beyond accuracy and BLEU scores with metrics

that actually measure product impact.

Practical Tools & Techniques – Learn modern eval stacks, from LLM evals to human-in-the-loop systems.

Cross-Functional Alignment – Build a shared language between engineering teams and product leaders.

Real-World Case Studies – Explore how top AI companies test and validate their models.

Who Will Benefit Most

Engineers – Gain the frameworks to measure and communicate model quality clearly.

Product Managers – Understand the trade-offs behind AI performance and product decisions.

AI Startups & Enterprises – Build evaluation systems that scale with your products.

Researchers & Builders – Learn how to move from academic benchmarks to production-ready evals.

The Transformation You’ll See

By the end of the course, you’ll know how to:

Design robust eval strategies for different AI use cases

Choose and implement metrics that reflect real-world success

Align stakeholders on model performance and product readiness

Confidently guide AI feature launches with data-driven decisions