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Claire Vo에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Claire Vo 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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The secret to better AI prototypes: Why Tinder’s CPO starts with JSON, not design | Ravi Mehta (product advisor, previously EIR at Reforge)

54:38
 
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Manage episode 509069191 series 3660816
Claire Vo에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Claire Vo 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Ravi Mehta, now a product advisor, has built and scaled products used by millions. His past roles include Chief Product Officer at Tinder, Entrepreneur in Residence at Reforge, and senior product leadership positions at Facebook, TripAdvisor, and Xbox. In this episode, Ravi demonstrates his data-driven approach to AI prototyping that produces dramatically better results than traditional "vibe prototyping." He also shares his structured framework for generating professional-quality images in Midjourney that look like they were shot by a professional photographer.

What you’ll learn:

  1. Why most product managers and designers are “vibe prototyping” with AI and getting mediocre results
  2. How to use JSON data models instead of design systems as the foundation for better AI prototypes
  3. A simple three-part framework for structuring Midjourney prompts to get professional-quality photos
  4. How to use Claude and Unsplash’s MCP server to generate realistic data and images for your prototypes
  5. Why real data (not Lorem Ipsum) is critical for getting meaningful feedback from stakeholders
  6. The film stock “cheat code” that instantly elevates your AI-generated photos

Brought to you by:

Google Gemini—Your everyday AI assistant

Persona—Trusted identity verification for any use case

Where to find Ravi Mehta:

Website: https://www.ravi-mehta.com/

Reforge: https://www.reforge.com/profiles/ravi-mehta

LinkedIn: https://www.linkedin.com/in/ravimehta/

X: https://x.com/ravi_mehta

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

In this episode, we cover:

(00:00) Introduction to Ravi and data-driven prototyping

(02:31) The problem with “vibe prototyping” in product development

(04:18) Spec-driven prototyping vs. data-driven prototyping

(05:27) Demo: Spec-driven approach to prototyping

(08:26) Limitations of the basic AI prototype approach

(11:24) The data-driven prototyping approach explained

(12:08) Demo: Data-driven prototyping

(17:45) Creating a prototype with the generated JSON data

(23:33) Comparing the quality difference between approaches

(26:44) Modifying the prototype

(28:53) Benefits of this approach

(34:40) Structured Midjourney prompting

(36:20) The subject-setting-style framework for better image prompts

(44:27) Using camera metadata to refine your results

(48:54) Lightning round and final thoughts

Tools referenced:

• Claude: https://claude.ai/

• Reforge Build: https://www.reforge.com/build

• Midjourney: https://www.midjourney.com/

• Unsplash MCP: https://github.com/okooo5km/unsplash-mcp-server-go?utm_source=chatgpt.com

Other references:

• Reforge AI Strategy Course: https://www.reforge.com/courses/ai-strategy

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  continue reading

27 에피소드

Artwork
icon공유
 
Manage episode 509069191 series 3660816
Claire Vo에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Claire Vo 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Ravi Mehta, now a product advisor, has built and scaled products used by millions. His past roles include Chief Product Officer at Tinder, Entrepreneur in Residence at Reforge, and senior product leadership positions at Facebook, TripAdvisor, and Xbox. In this episode, Ravi demonstrates his data-driven approach to AI prototyping that produces dramatically better results than traditional "vibe prototyping." He also shares his structured framework for generating professional-quality images in Midjourney that look like they were shot by a professional photographer.

What you’ll learn:

  1. Why most product managers and designers are “vibe prototyping” with AI and getting mediocre results
  2. How to use JSON data models instead of design systems as the foundation for better AI prototypes
  3. A simple three-part framework for structuring Midjourney prompts to get professional-quality photos
  4. How to use Claude and Unsplash’s MCP server to generate realistic data and images for your prototypes
  5. Why real data (not Lorem Ipsum) is critical for getting meaningful feedback from stakeholders
  6. The film stock “cheat code” that instantly elevates your AI-generated photos

Brought to you by:

Google Gemini—Your everyday AI assistant

Persona—Trusted identity verification for any use case

Where to find Ravi Mehta:

Website: https://www.ravi-mehta.com/

Reforge: https://www.reforge.com/profiles/ravi-mehta

LinkedIn: https://www.linkedin.com/in/ravimehta/

X: https://x.com/ravi_mehta

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

In this episode, we cover:

(00:00) Introduction to Ravi and data-driven prototyping

(02:31) The problem with “vibe prototyping” in product development

(04:18) Spec-driven prototyping vs. data-driven prototyping

(05:27) Demo: Spec-driven approach to prototyping

(08:26) Limitations of the basic AI prototype approach

(11:24) The data-driven prototyping approach explained

(12:08) Demo: Data-driven prototyping

(17:45) Creating a prototype with the generated JSON data

(23:33) Comparing the quality difference between approaches

(26:44) Modifying the prototype

(28:53) Benefits of this approach

(34:40) Structured Midjourney prompting

(36:20) The subject-setting-style framework for better image prompts

(44:27) Using camera metadata to refine your results

(48:54) Lightning round and final thoughts

Tools referenced:

• Claude: https://claude.ai/

• Reforge Build: https://www.reforge.com/build

• Midjourney: https://www.midjourney.com/

• Unsplash MCP: https://github.com/okooo5km/unsplash-mcp-server-go?utm_source=chatgpt.com

Other references:

• Reforge AI Strategy Course: https://www.reforge.com/courses/ai-strategy

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  continue reading

27 에피소드

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