Former Google and Apple researchers launched Trajectory, a startup focused on building AI systems that improve continuously through user interaction rather than requiring periodic retraining. The company is applying rapid iteration cycles similar to agile software development to create AI products that adapt and improve in real time based on user feedback. This approach addresses a fundamental limitation in current AI systems—their tendency to stagnate after deployment.

What This Means for Your Business

Organizations deploying AI products should investigate whether continuous learning mechanisms are available for your use cases. Traditional AI systems that degrade or become stale over time represent a hidden cost in production environments. Evaluate your AI vendors' roadmaps for continuous improvement capabilities, and consider whether your data infrastructure supports real-time feedback loops that could drive AI system improvement post-deployment.