Your engineering team is using ChatGPT to write code faster than ever. Yet your projects still miss the mark with customers. Sound familiar? The rise of AI coding tools is exposing an uncomfortable truth: technical skills alone no longer differentiate great developers.
Consider Tesla's early autopilot team. Despite world-class ML engineers, they struggled until bringing in automotive safety experts. The breakthrough? These domain experts helped identify edge cases that pure ML algorithms missed. Result: Tesla's autopilot safety record outperformed human drivers by 10x.
Stripe's breakthrough came when they paired engineers with payment industry veterans. These hybrid teams:
Jeff Lawson's team spent months embedded with customer service teams before building their API. Result?
Jony Ive's design team included both industrial designers and engineers. This fusion led to:
Embed Your Engineers Require every engineer to spend one week per quarter with customers or stakeholders. Twilio still does this, even at their current scale.
Redefine Code Reviews Make domain experts part of your review process. Netflix's Content Engineering team reduced streaming errors by 90% after including media specialists in technical reviews.
Reward Business Impact Change your promotion criteria. Square promotes engineers based on business metrics, not code output. Result? Their point-of-sale system has the industry's highest customer satisfaction.
This week: Identify your top three business challenges. Have your engineers shadow the teams facing these challenges. As GitHub's CEO Thomas Dohmke says: "The best code comes from engineers who understand the problem, not just the solution."
Remember: In an AI-powered world, your competitive advantage isn't how fast your team can code—it's how well they understand what to build.