AI evaluation framework design for product managers (Hindi)

Shipping AI without an AI evaluation framework is like letting a driver take the wheel without a test. Learn how to define what good means for your product. Product managers get stuck between engineers building models and users receiving broken answers. To fix this, write the rulebook for your model. Just like the DMV tests driving skills, you must set evaluation datasets and grading rubrics. Because AI outputs are fuzzy, your rubric must handle answers that are only halfway right. If an AI writes support emails, it might sound polite but hallucinate a fake policy. A strong rubric penalizes hallucinations so the factual model wins. Collaborate with engineers to list what the AI must and must never do. Then, gather real user examples to create your first test route before building. In this lesson: - Why shipping AI without an evaluation framework fails - Selecting evaluation datasets from real user questions - Designing grading rubrics for fuzzy AI outputs - Action steps to whiteboard your AI driving test U2xAI Academy - AI skills for product managers. यह लेसन हिंदी में है. This lesson is narrated in Hindi.