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Fixing Online Shopping: The Future of AI Fashion Search & Discovery - With Chang Liu of Plush

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Manage episode 514588998 series 3650264
Content provided by Julia Lach. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Julia Lach or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

What if your shopping search could think like you do: mood, context, and all the tiny details that make an outfit feel right? In this epidsde I sit down with Chang Liu, co‑founder and CEO of Plush, to unpack how she transformed a personal frustration with endless scrolling into an AI‑powered fashion discovery platform that feels like talking to a stylist who actually gets you.
Chang’s path runs from Yale to Wellington Management, then through analytics and product at DoorDash, where she helped scale DashPass and learned to ship minimal, lovable products. Those experiences shape Plush’s DNA: clear moats, real unit economics, and a relentless focus on clean, structured data. We explore the technology unlocks that finally make intuitive fashion search possible: multimodal models that see silhouette and fabric, instruction‑tuned LLMs that turn “elevated basics for a fall birthday party” into actionable parameters, and stronger embeddings that map vibes to precise results.
But this isn’t about handing your wardrobe to a faceless agent. Chang argues for curation with evidence: fewer, better picks and a clear why behind each one, trend cues, fabrication, brand identity, and styling insights. We talk co‑founder fit, rebuilding hybrid search from the ground up to 3x retention, and real user moments ranging from “upstage the bride, but don’t” to postpartum black‑tie comfort. The future she’s building preserves the joy of browsing while removing the grind of filtering.
If you’re curious about AI in fashion, personalization, or how product, data, and taste come together, this conversation delivers both strategy and heart. Subscribe, share with a friend who loves style and tech, and leave a review telling us your most specific search you’d want AI to nail.

Links Chang/Plush:

Links Julia/aiflow/Consulting:

  continue reading

Chapters

1. Fixing Online Shopping: The Future of AI Fashion Search & Discovery - With Chang Liu of Plush (00:00:00)

2. Opening And Guest Introduction (00:00:03)

3. Career Path: Finance To Tech (00:01:35)

4. Inspiration From Founders And Grit (00:05:41)

5. Lessons From Investing, Data, And Product (00:09:51)

6. The Shopping Problem Plush Solves (00:16:14)

7. New AI Capabilities Enabling Plush (00:19:02)

8. Co-Founder Match And Team Strengths (00:22:28)

9. Early Wins, Retention Gains, Validation (00:26:00)

10. The Future: Mood-Based Discovery (00:27:41)

11. Quirky Searches And Personalization (00:32:46)

12. Closing And Listener Invitation (00:34:57)

10 episodes

Artwork
iconShare
 
Manage episode 514588998 series 3650264
Content provided by Julia Lach. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Julia Lach or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

What if your shopping search could think like you do: mood, context, and all the tiny details that make an outfit feel right? In this epidsde I sit down with Chang Liu, co‑founder and CEO of Plush, to unpack how she transformed a personal frustration with endless scrolling into an AI‑powered fashion discovery platform that feels like talking to a stylist who actually gets you.
Chang’s path runs from Yale to Wellington Management, then through analytics and product at DoorDash, where she helped scale DashPass and learned to ship minimal, lovable products. Those experiences shape Plush’s DNA: clear moats, real unit economics, and a relentless focus on clean, structured data. We explore the technology unlocks that finally make intuitive fashion search possible: multimodal models that see silhouette and fabric, instruction‑tuned LLMs that turn “elevated basics for a fall birthday party” into actionable parameters, and stronger embeddings that map vibes to precise results.
But this isn’t about handing your wardrobe to a faceless agent. Chang argues for curation with evidence: fewer, better picks and a clear why behind each one, trend cues, fabrication, brand identity, and styling insights. We talk co‑founder fit, rebuilding hybrid search from the ground up to 3x retention, and real user moments ranging from “upstage the bride, but don’t” to postpartum black‑tie comfort. The future she’s building preserves the joy of browsing while removing the grind of filtering.
If you’re curious about AI in fashion, personalization, or how product, data, and taste come together, this conversation delivers both strategy and heart. Subscribe, share with a friend who loves style and tech, and leave a review telling us your most specific search you’d want AI to nail.

Links Chang/Plush:

Links Julia/aiflow/Consulting:

  continue reading

Chapters

1. Fixing Online Shopping: The Future of AI Fashion Search & Discovery - With Chang Liu of Plush (00:00:00)

2. Opening And Guest Introduction (00:00:03)

3. Career Path: Finance To Tech (00:01:35)

4. Inspiration From Founders And Grit (00:05:41)

5. Lessons From Investing, Data, And Product (00:09:51)

6. The Shopping Problem Plush Solves (00:16:14)

7. New AI Capabilities Enabling Plush (00:19:02)

8. Co-Founder Match And Team Strengths (00:22:28)

9. Early Wins, Retention Gains, Validation (00:26:00)

10. The Future: Mood-Based Discovery (00:27:41)

11. Quirky Searches And Personalization (00:32:46)

12. Closing And Listener Invitation (00:34:57)

10 episodes

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