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CYC26 / AI

Building MARVIN: What Teaching a Non-Technical Marketer to Use MCP Taught Me About AI Adoption

Over the 2025 holiday break, I built MARVIN, an AI assistant that connects to my email, calendar, Jira, Confluence, and meeting notes through MCP servers. The most surprising lessons came from teaching a non-technical friend in marketing to use it. Within a day, she took a task that typically required 4+ hours and completed it in 30 minutes. In this talk, I'll share practical insights from building and deploying MCP-powered agents in real workflows: - Architecture decisions: How I structured MCP servers for Gmail, Google Calendar, Jira, and other integrations, and where I got it wrong - The "junior intern" pattern: Why treating AI agents like trainable assistants drives real usage - The naming problem: Why "MCP" is a terrible name for mainstream adoption and what we should call it instead - Curiosity over mandates: Why top-down AI adoption fails, and what ground-up adoption looks like I'll walk through 25 minutes of hard-won lessons from building something real, watching people use it, and iterating based on what actually worked.

Session abstract

What you’ll learn

Over the 2025 holiday break, I built MARVIN, an AI assistant that connects to my email, calendar, Jira, Confluence, and meeting notes through MCP servers. The most surprising lessons came from teaching a non-technical friend in marketing to use it. Within a day, she took a task that typically required 4+ hours and completed it in 30 minutes. In this talk, I'll share practical insights from building and deploying MCP-powered agents in real workflows: - Architecture decisions: How I structured MCP servers for Gmail, Google Calendar, Jira, and other integrations, and where I got it wrong - The "junior intern" pattern: Why treating AI agents like trainable assistants drives real usage - The naming problem: Why "MCP" is a terrible name for mainstream adoption and what we should call it instead - Curiosity over mandates: Why top-down AI adoption fails, and what ground-up adoption looks like I'll walk through 25 minutes of hard-won lessons from building something real, watching people use it, and iterating based on what actually worked.