Insights for Engineering Excellence
Engineers Don’t Trust AI Equally.
Engineers don’t trust AI equally. Learn why trust varies across software development workflows, what drives confidence in AI-generated code, and how trust directly affects software delivery performance.Engineers don’t trust AI equally. Learn why trust varies across software development workflows, what drives confidence in AI-generated code, and how trust directly affects software delivery performance.
The Best AI Workflow We Found Wasn’t Coding.
What if the best use of AI in software engineering isn’t writing code? Discover why debugging, research, and understanding emerged as the highest-value AI workflows in our engineering study.What if the best use of AI in software engineering isn’t writing code? Discover why debugging, research, and understanding emerged as the highest-value AI workflows in our engineering study.
We Asked 250 Engineers Where AI Fails. The Answers Were Surprisingly Consistent.
AI doesn’t fail randomly. It fails predictably. Discover the patterns 250 engineers identified and learn where AI creates value, where it creates friction, and why understanding remains the biggest bottleneck in software development.AI doesn’t fail randomly. It fails predictably. Discover the patterns 250 engineers identified and learn where AI creates value, where it creates friction, and why understanding remains the biggest bottleneck in software development.
The Highest-Performing AI Teams Aren’t Using Better Models. They’re Using Better Delivery Practices
AI success isn’t determined by model quality alone. Learn how high-performing engineering teams use AI for debugging, implementation, and delivery while avoiding review overload, rework, and trust issuesAI success isn’t determined by model quality alone. Learn how high-performing engineering teams use AI for debugging, implementation, and delivery while avoiding review overload, rework, and trust issues
