In the rapidly evolving landscape of generative AI, the most impactful products aren’t built by chasing the latest models—they're built by deeply understanding user needs. This post outlines 10 essential principles for designing AI features.

Conducting user research goes beyond mere data collection; it necessitates a methodical approach encompassing the validation of hypotheses at various stages. Every product concept relies on a foundation of assumptions.

Discover how AI-powered tools like Productboard and Dovetail are revolutionizing user research by automating insight extraction, reducing bias, and making feedback more transparent and actionable across teams.

Learn how the Dual-Track Agile approach balances product discovery and delivery to accelerate product-market fit. This post shows how continuous learning and cross-functional collaboration can help teams build the right products, faster.

A practical guide to the key qualitative and quantitative metrics that signal PMF—like retention, growth, user sentiment, and engagement. Featuring expert insights from leading founders and product leaders.

Explore how early data model validation, ethical considerations, and user-centered design are essential to creating successful AI-enabled products. This post introduces the concept of AI–Problem Fit.