TrueCode

Traditional hiring methods often focus solely on final code results, overlooking how candidates reason through AI suggestions or recover from errors. TrueCode addresses this by capturing interaction signals during full sessions in an AI-enabled workspace, allowing teams to review verification habits and overall process quality. The scoring system breaks down performance into key areas including outcome success, verification steps, calibration accuracy, AI tool usage, and planning depth. These combine into a single defensible metric that highlights differences between candidates who verify work carefully and those who accept suggestions without checks. Beyond hiring, the platform supports candidate practice for building skills and university programs for teaching AI-augmented engineering. Organizations can customize challenges and integrate results into existing workflows for consistent evaluation.