AWS Public Sector Blog
Author: Jim Kim
Jim leads the product acceleration team at AWS, helping EdTech and GovTech companies launch new products and features more quickly. Before joining AWS, Kim built and led sales and customer success teams at BetterLesson and EVERFI. He began his career as a freshman dean at Stanford University and Bowdoin College. Kim holds an MBA from Duke University's Fuqua School of Business, a master's in education from Harvard Graduate School of Education, and a bachelor's degree from Johns Hopkins University.
5 pillars to stabilize your AI product development strategy
In this blog, learn how five durable pillars—full-stack builders, parallel decision-making, context as a competitive moat, disciplined prioritization, and trust at AI speed—can stabilize your AI product development strategy amid rapid technological change. Drawn from the AWS Product Acceleration team’s work with AI-native product leaders, these principles help organizations cut through the noise and convert AI-driven speed into real customer value rather than chaos.
Generative AI in EdTech: 5 pitfalls to avoid for long-term success
Today’s education technology (EdTech) leaders face intense pressure to “do something with AI.” Fear of missing out has created a mentality where companies rush out AI features without understanding what problems they’re solving for their users. At AWS, we work closely with EdTech leaders navigating the generative AI landscape, and we’ve seen these patterns emerge repeatedly. Based on our experience collaborating with EdTech organizations across the education spectrum, we’ve created a list of five common pitfalls that derail generative AI efforts and the strategic approaches we recommend to avoid them.