Accelerate Automotive UI Development with Kiro, Squish, and Virtual Targets on AWS

This article describes how AWS and Qt Group are collaborating to accelerate automotive UI development by combining AI-powered code generation (Kiro), automated testing (Squish), and virtual targets on AWS.

• Automotive HMIs transitioning to safety-critical, software-defined vehicle components requiring complex testing
• Kiro generates test scripts from natural language specifications using AI
• Squish provides automated behavior-driven development testing across platforms
• Virtual embedded development targets (vEDTs) on AWS enable parallel development without physical hardware bottlenecks
• Feedback loop between Kiro and Squish via Model Context Protocol enables continuous improvement
• Early defect detection reduces costs exponentially versus late-stage fixes
• Global teams collaborate securely via Amazon WorkSpaces accessing cloud-based virtual devices
• Shift-left testing approach enables continuous quality validation on every code commit

This cloud-native approach transforms automotive UI development by eliminating hardware constraints, enabling parallel workflows, and catching defects early when fixes are cheapest.