On this episode of Deployed we talk with Lijuan Qin, Head of Product for Zoom AI, about how her team is moving beyond AI meeting transcriptions and note-taking to a mission of agents helping from "conversation to completion." That's how Lijuan describes her vision of the future for Zoom AI, where AI doesn't just summarize your meetings, it actually follows through on the work that comes after.

Lijuan has a PhD in AI and spent 20 years at Microsoft working on NLP and video understanding before joining Zoom. She brings a long-arc perspective on what's changed and what hasn't in AI, and shares how her team thinks about building an AI companion that acts more like a team member than a search engine.

Key insights for builders include:

* Why high engagement with an AI product can be a negative signal. i.e. if users keep going back and forth with your AI, the product might be failing them ("you got it wrong! try again").
* How Zoom measures AI quality by *output* value and task completion, instead of usage metrics or individual response accuracy
* Their "AI-first, intent-driven" approach: starting from what the user needs to get done, not which tool to use
* How they personalize AI features in stages: role-based outputs first, then memory, then live conversation context, rather than trying to build something like a full "digital twin" on day one
* A concrete example: Drafting different kickoff documents for each meeting attendee that is personalized for the priorities of their role (PM vs. engineer vs. CTO)
* Why transparent decision frameworks let big organizations experiment fast without approval loops
* How the Zoom AI team balances speed and enterprise trust

Links from our conversation:

* Zoom AI Companion: https://ai.zoom.us
* Find Lijuan on LinkedIn: https://www.linkedin.com/in/lijuanqin/
* Freeplay (that's us): https://freeplay.ai

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