In this episode, Noam Rubin, a Software Developer at Vanta reveals how his team uses data-driven strategies to design, test, and improve cutting-edge AI features. Learn how customer insights, rapid prototyping, and iterative development transform raw ideas into tools that make compliance and security easier for businesses everywhere.
Chapters:
00:00 - Introduction02:47 - The process of building AI products at Vanta04:51 - The role of customer feedback in product development06:59 - Integrating AI into security and compliance workflows08:06 - Using data specifications to guide product development10:10 - Collaborating with subject matter experts to refine AI models12:14 - Iterative testing and refining AI features14:10 - Quality control and ensuring AI accuracy16:00 - The importance of dogfooding and internal feedback loops18:23 - Scaling AI features and rolling them out to wider audiences20:50 - Educating engineers and democratizing AI at Vanta22:20 - Key lessons learned from building AI products24:12 - Maintaining AI quality through continuous feedback26:00 - The future of AI in business and product development
