Creating a private AI assistant in Thunderbird
Practical AI · 2025-09-23 · 53 min
Episode notes
In this episode, Daniel and Chris are joined by Chris Aquino, software engineer at Thunderbird to hear the story of how they developed a privacy-preserving AI executive assistant. They discuss various design decisions including remote (but confidential) inference, local encryption, and model selection. Chris A. does an amazing job describing the journey from "let the big LLM do everything" to splitting apart the workflow to be handled by multiple models. Featuring: Chris Aquino - LinkedIn Chris Benson - Website , LinkedIn , Bluesky , GitHub , X Daniel Whitenack - Website , GitHub , X Links: Thunderbird Thunderbird Pro Sponsors: Shopify - The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business - no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalai Upcoming Events: Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they’ve scaled AI solutions.
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