What an MCP implementation looks like at a CRM company
Ryan chats with Karen Ng, EVP of Product at HubSpot, to chat about Model Context Protocol (MCP) and how they implemented it for their server for their CRM product.

Ryan chats with Karen Ng, EVP of Product at HubSpot, to chat about Model Context Protocol (MCP) and how they implemented it for their server for their CRM product.
Quinn Slack, CEO and co-founder of Sourcegraph, joins the show to dive into the implications of AI coding tools on the software engineering lifecycle. They explore how AI tools are transforming the work of developers from syntax-focused tasks to higher-level design and management roles and how AI will integrate into enterprise environments.
Ryan welcomes Mahir Yavuz, Senior Director of Engineering at Etsy, to the show to explore the unique challenges that Etsy’s marketplace faces and how Etsy’s teams leverage machine learning and AI to manage product SKUs, enrich inventory metadata, and improve both buyer and seller experiences.
Ryan is joined on the podcast by Confluent’s AI Entrepreneur in Residence, Sean Falconer, to discuss the growing need for standards for AI agents, the emerging Model Context Protocol and agent-to-agent communication, and what we can learn from early web standards while AI continues to evolve.
Ryan welcomes Illia Polosukhin, co-author of the original "Attention Is All You Need" Transformers paper and co-founder of NEAR, on the show to talk about the development and impact of the Transformers model, his perspective on modern AI and machine learning as an early innovator of the tech, and the importance of decentralized, user-owned AI utilizing the blockchain.
Ryan welcomes Matt DeBergalis, CTO at Apollo GraphQL, to discuss the evolution and future of API orchestration, the benefits of GraphQL in managing API complexity, its seamless integration with AI and modern development stacks, and how it enhances developer experience through better tooling and infrastructure.
AI is no longer just a luxury for the most tech savvy companies — it's now a necessity for organizational transformation. How are real teams successfully leveraging and innovating with these new tools?
Positioned at the intersection of automation, decision intelligence, and data orchestration, AI agents are quickly emerging as essential tools for aligning business outcomes with technical workflows.
What challenges do organizations face when adopting AI, and why is understanding its limitations key to success?
Douwe Kiela, CEO and cofounder of Contextual AI, joins Ryan and Ben to explore the intricacies of retrieval-augmented generation (RAG). They discuss the early research Douwe did at Meta that jump started the whole thing, the challenges of hallucinations, and the significance of context windows in AI applications.
Christophe Coenraets, SVP of Developer Relations at Salesforce, tells Eira and Ben about building the new Salesforce Developer Edition, which includes access to the company’s agentic AI platform, Agentforce. Christophe explains how they solicited and incorporated feedback from the developer community in building the developer edition, what types of AI agents people are building, and the critical importance of guardrails and prompt engineering.
Ryan welcomes Jeu George, cofounder and CEO of Orkes, to the show for a conversation about microservices orchestration. They talk through the evolution of microservices, the role of orchestration tools, and the importance of reliability in distributed systems. Their discussion also touches on the transition from open-source solutions to managed services, integration opportunities for AI agents, and the future of microservices in cloud computing.
Is “agentic AI” just a buzzword, or is it the sea change it seems?
Deepak Singh, VP of Developer Agents and Experiences at AWS, helps Ryan break down the hype around agentic AI in software development. They cover the definition and real-world functionality of AI agents, how developers can integrate them into existing workflows, and the importance of establishing guardrails to ensure trust and security in agentic AI.
Some high-level takeaways, with more to come.