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://gautambaghel.com/

https://www.linkedin.com/in/gautambaghel/

Links from the show:

https://www.hashicorp.com/en/blog/build-secure-ai-driven-workflows-with-new-terraform-and-vault-mcp-servers

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