Convex

Why Can't Anyone Answer Questions About the Business? — Garrett Galow, WorkOS

Jun 11, 2026 · 19:06

Garrett Galow from WorkOS built Studio, an internal workspace where anyone can ask natural language questions against Snowflake, Linear, and Notion, and get reusable widgets instead of filing a request. The LLM generates declarative JavaScript widgets that call data sources directly, making subsequent runs deterministic and cheap. Three techniques made it reliable: preflight sequencing injects schema context only when a tool is invoked, a layering rule tells the model to distrust its own knowledge about WorkOS and use primary sources, and query validation catches valid SQL that returns zero rows before hardcoding it into a widget.

We accidentally made an AI platform: Jamie Turner

Oct 8, 2024 · 5:36

Jamie Turner, co-founder of Convex, explains how his company's backend platform accidentally became an AI platform because its reactive data flow paradigm—extending React's state reactivity to the server with subscribable queries and mutations—perfectly suits generative AI workflows. He describes Convex's architecture as seamlessly syncing state between backend steps and the application, enabling concurrent chains of tasks like automatic speech recognition, summarization, embedding generation, and finding related notes. Turner notes that post-ChatGPT, over 90% of Convex projects are generative AI. To support this shift, Convex added native vector indexes for schema fields and launched a startups program with discounts and exclusive forums. Upcoming high-level components will encapsulate state machines for sophisticated workflows. Turner presents Convex as a way for generative AI engineers to ship quickly and confidently.