VP of engineering Jackie Brosamer and principal engineer Brad Axen join me to demo Goose, Block’s open-source AI agent that runs locally, plugs into your existing tools through model context protocol (MCP) servers, and peels away the rote parts of work so people can focus on insight and impact.

This episode is packed with in-depth demos: starting with a messy farm-stand sales CSV, Goose analyzes the data, builds visualizations, and generates a shareable HTML report. We then spin up an MCP that lets Goose talk to Square’s dashboard for inventory management, vibe code an email MCP that can send payment links automatically, and unpack how environment setup, debugging, and tool orchestration get handled behind the scenes.

What you’ll learn:

A practical, repeatable workflow for turning any working script or function into a custom MCP—and exposing it to natural-language control
How to transform messy CSVs into visualizations, HTML reports, and actionable business insights without needing a data science background
Ways to hook Goose into live business systems (e.g. Square inventory, payments) so analysis flows directly into operational action
The thinking behind Block’s decision to open-source Goose
Lessons from Block’s bottom-up meets top-down adoption model
Why organizational transformation, not just picking the right LLM, will separate AI winners from laggards over the next few years
How to scale an internal MCP catalog
The organizational transformation required to fully leverage AI capabilities