Fireside Chat, Interview
CJ Desai, MongoDB & Laura Modiano, OpenAI in Conversation | RAISE Summit 2026
- MongoDB aims to leverage AI to drive four strategic outcomes: faster innovation, increased sales, improved service, and greater operational efficiency.
- The pace of model release is projected to accelerate from a historical 15-month cycle to just six weeks, while software building costs are expected to decrease significantly as AI democratizes development.
- Version 5.6 is currently in development, following the February launch of a desktop application that has achieved three times faster adoption rates among non-technical users.
- Strategic plans include deploying forward-engineering support for OpenAI customers to address Codex usage gaps, where the application already reports over 5 million weekly active users.
- The timeline for the industry shift from prototyping or prompting to production deployment is now expected to occur in 2026, a revision from the previous 2025 prediction.
- MongoDB intends to direct customers toward using OLTP as the primary foundation for agentic architecture while advising against the use of its database for analytical use cases to prevent implementation failures.
- A specific large customer in Paris is developing a horizontal agentic architecture to serve all lines of business for AI initiatives, requiring a data layer that scales commensurately with company growth.
- The company positions itself as the sole hybrid multi-cloud database capable of operating on-premises, in public clouds, or across multiple public clouds.
- With a customer base of 67,500 ranging from AI-native firms like 11 Labs to JPMorgan Chase, MongoDB generated $2.5 billion in revenue and maintains a presence spanning 19 years since its 2007 inception.
- Rapid innovation in the sector necessitates close, regular engagement with founders and enterprises, exemplified by the observation that some companies have grown from zero to $100 million ARR in just eight months.