Is There a Drag and Drop Functionality?

Over the past five years, Intuit went through a total cloud transformation—they closed the data centers, built out a modern SaaS development environment, and got cloud native with foundational building blocks like containers and Kubernetes. Now they are looking to continue transforming into an AI-driven organization that leverages the data they have to make their customers’ lives easier. Along the way, they realized that their internal systems have the same requirements to leverage the data they have for AI-driven insights. 

Episode notes

Wadher notes that Intuit uses development velocity, not developer velocity. The thinking is that an engineering org should focus on shipping products and features faster, not making individual devs more productive. 

No, the robots aren’t coming for your jobs. Wadher says their AI strategy relies on helping experts make better insights. The goal is to arm those experts, not replace them. 

In terms of sheer volume, the AI/ML program at Intuit is massive. They make 58 billion ML predictions daily, enable 730 million AI-driven customer interactions every year, and maintain over two million personalized AI models. 

Intuit’s not here to hoard secrets. They’ve outsourced their DevOps pipeline tool, Argo. They found that a lot of companies used it for AI and data pipelines, and have recently launched Numaproj, which open sources a lot of the tools and capabilities that they use internally. 

Congrats to Lifeboat badge winner Bill Karwin for their answer to Understanding MySQL licensing.