Shruti Tiwari

While both traditional (non-AI) PMs and AI PMs require strong customer understanding, product sense, execution, and stakeholder management skills, AI PMs need additional ...

With product vision, we need to carefully tread the line between making it too generic/vague or too technical. Other things to consider are - it should clarify what impac...

My one piece of advice would be to be outcome-driven. A lot of them don’t make it to deployment or don’t deliver as expected. To ensure that efforts turn into outcomes, b...

Yes, we incorporate user feedback to improve the model and reduce drift over time. There are several ways to gather feedback:1. Direct user feedback through thumbs-up and...

Based on my experience, some common mistakes AI PMs make include focusing too much on technology instead of user needs and business impact, ignoring data quality and feas...

I would think about Gen AI integration into any application based on its use case. There are two major purposes that Gen AI serves - Content generation and natural langua...

I would divide the hard skills into 4 categories -AI foundational knowledge at conceptual level including understanding of AI/ML model lifecycle, different algorithms lik...

Exact metrics would vary by product and application, but I would think about metrics in three categories-Model performance metrics like accuracy, precision, recall, AUC-R...

There are already Product managers focused towards data science teams in many companies and I am one of them. Generally, I see three different types of Product Management...

Well, the good news is as the first PM in the team, you can introduce some new ways of doing things. The bad news is that its a journey and it'll take some time to change...