A naukri.com initiative
The Growth Catalyst
3M
204
Image Credit: The Growth Catalyst
A Brief Guide to Knowledge and Tools That AI PMs Should Master
- The role of AI Product Manager has evolved with the rise of Large Language Models (LLMs) in the AI landscape.
- AI Product Managers need a unique set of skills beyond traditional PM roles, including technical proficiency and AI/ML knowledge.
- Discovery and prioritization of AI use cases require assessing data availability, ROI calculation, and implementation details.
- AI product design involves handling challenges like generative AI products potentially providing misinformation.
- AI engineering involves understanding model selection, architecture, and cost implications, requiring active involvement from PMs.
- AI Agents can work independently with minimal human supervision, and PMs need to understand building processes using tools like AutoGPT.
- Evaluation and improvement of AI products involve designing comprehensive evaluation frameworks and managing dataset quality.
- Ensuring AI safety and ethical considerations is crucial in the evaluation process, using tools like AI Fairness Checklist.
- Pricing and positioning AI products require understanding unique value propositions and crafting pricing strategies based on consumer willingness to pay.
- Product growth and strategy are essential for long-term success of AI products, utilizing special features like novelty and community engagement.
Read Full Article
11 Likes
For uninterrupted reading, download the app