Design, Not Hype, Saves AI Products
As a branding and content curator, I endorse this urgent wake up call for product teams. It explains why many AI features are built to impress investors, not solve human problems. The article draws on RAND interviews, and Gartner forecasts, to map failure patterns, and fixes. Design leaders get a practical playbook, from committing to year long efforts, to anchoring the problem statement. It exposes how missing designers, and sidelined data engineers break models, drain institutional memory, and stall projects. The result is expensive experiments that never reach users, and products that satisfy no discernible need at launch.
Read this if you care about building AI that earns trust, avoids expensive failures, and actually helps people. It equips design and product leaders with language to stop pointless AI theater, and to start solving real problems. This short, sharp read will change how you brief teams, hire practitioners, and measure success. You will learn practical steps to include designers and data engineers from day one, and to align goals with outcomes. Adopt the one year rule, resist shiny feature pressure, and prioritize solving measurable user problems over vendor hype now.
Source: uxdesign.cc
