Show notes
In this episode, we're joined by Matt DeBergalis, CTO and Co-Founder of Apollo GraphQL, to explore what happens when AI agents start interacting with enterprise systems that were never designed for them.
We dive into the collision between APIs, MCP, GraphQL, and agentic AI, and why traditional assumptions about trust, permissions, and security are breaking down. Matt argues that AI agents should be treated as untrusted actors by default, and explains why giving agents access to enterprise data creates entirely new challenges around governance, access control, and risk management.
Along the way, we discuss semantic APIs, enterprise data silos, citizen developers, agent permissions, security boundaries, and how GraphQL and MCP can work together to make enterprise systems more accessible to both humans and AI. The conversation also explores why companies are racing to deploy agents despite the risks, and what the future of enterprise software might look like when AI becomes the primary consumer of APIs.
Apollo GraphQL: https://www.apollographql.com
Matt DeBergalis: https://www.linkedin.com/in/debergalis
Alex Salkever: https://www.linkedin.com/in/alexsalkever
Timestamps:
[00:00] AI, APIs, and Trust
[01:16] MCP API Lessons
[06:16] GraphQL and MCP Integration
[12:55] API Security for MCP
[16:10] Linux Kernel Security Concerns
[19:09] API Design and Controls
[21:52] Trust in Autonomous Systems
[25:06] MCP GraphQL Wish List
[27:13] API Access Patterns
[28:44] GraphQL API Perspective
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