
In this episode, Ryan Donovan interviews David Soria Parra, co‑creator of the Model Context Protocol (MCP) and a technical staff member at Anthropic. They discuss the origin of MCP as a solution to the copy‑paste friction when using LLMs, its evolution into an open protocol that lets AI applications seamlessly connect to diverse data sources, and the design of its primitives—prompts, resources, and tools—along with challenges around authentication, OAuth, and security. David explains how the protocol balances flexibility for AI models with deterministic client behavior, and how the community is shaping its future through open‑source implementations and gateways. The conversation also touches on the broader implications for AI safety and trustworthy data handling.

In this episode, Stack Overflow’s Janice Manningham and Josh Zhang chat with Cloudflare VP Will Allen about the newly launched pay‑per‑crawl model that lets publishers charge crawlers for access. They explain how AI‑driven content scraping has upended the traditional open‑versus‑block...

In this episode, Ryan interviews Shireesh Thota, Corporate Vice President of Azure Databases at Microsoft, about the rapid evolution of Microsoft's database offerings, including SQL Server, Cosmos DB, and Postgres, and how they fit into a unified Azure data platform....

In this episode, Ryan interviews Scott Stephenson, CEO and co‑founder of Deepgram, about the latest advances in voice AI, focusing on how deep learning improves speech‑to‑text and text‑to‑speech accuracy across diverse dialects and noisy environments. They discuss Deepgram’s scalable, affordable...