Join us as Gautam breaks down the evolution of tool use in generative AI and dives deep into MCP.
Gautam walks through the progression from simple prompt engineering to function calling, structured outputs, and now MCP—explaining why MCP matters and how it’s changing the way AI systems interact with external tools and data. You’ll learn about the differences between MCP and traditional API integrations, how to build your first MCP server, best practices for implementation, and where the ecosystem is heading. Whether you’re building AI-powered applications, integrating AI into your infrastructure workflows, or just trying to keep up with the latest developments, this episode provides the practical knowledge you need. Gautam also shares real-world examples and discusses the competitive landscape between various AI workflow approaches. Subscribe to vBrownBag for weekly tech education covering AI, cloud, DevOps, and more!
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Timestamps
0:00 Introduction & Welcome
7:28 Gautam’s Background & Journey to AI Product Management
- 12:45 The Evolution of Tool Use in AI
- 18:32 What is Model Context Protocol (MCP)?
- 24:16 MCP vs Traditional API Integrations
- 30:41 Building Your First MCP Server
- 36:52 MCP Server Discovery & Architecture
- 42:18 Real-World Use Cases & Examples
- 47:35 Best Practices & Implementation Tips
- 51:12 The Competitive Landscape: Skills, Extensions, & More
- 52:14 Q&A: AI Agents & Infrastructure Predictions
- 55:09 Closing & Giveaway
How to find Gautam:
https://www.linkedin.com/in/gautambaghel/
Links from the show:
Presentation from HashiConf:
https://youtu.be/eamE18_WrW0?si=9AJ9HUBOy7-HlQOK
Kiro Powers: https://www.hashicorp.com/en/blog/hashicorp-is-a-kiro-powers-launch-partner
Slides: https://docs.google.com/presentation/d/11dZZUO2w7ObjwYtf1At4WnL-ZPW1QyaWnNjzSQKQEe0/edit?usp=sharing