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Content provided by Immad Akhund and Rajat Suri, Immad Akhund, and Rajat Suri. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Immad Akhund and Rajat Suri, Immad Akhund, and Rajat Suri 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.
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Building Enterprise AI That Actually Works with Glean's Arvind Jain

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Manage episode 501198079 series 3462101
Content provided by Immad Akhund and Rajat Suri, Immad Akhund, and Rajat Suri. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Immad Akhund and Rajat Suri, Immad Akhund, and Rajat Suri 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.

Arvind Jain is the founder and CEO of Glean, building enterprise AI that connects to all internal company data, and co-founder of Rubrik, which recently went public. Starting as an enterprise search company in 2019, Glean has evolved into what Arvind calls "a more powerful version of ChatGPT inside your company," now approaching 1,000 employees and serving the world's most iconic companies.

What you'll learn:

  1. How Glean evolved from search to conversational AI without pivoting by riding AI model capabilities
  2. Why making it easy for customers to leave can be a competitive advantage in enterprise sales
  3. The challenges of competing against every major software company building similar products
  4. How to recruit from FAANG companies when you can't match their compensation
  5. The difference between building for established markets vs. creating new product categories
  6. Why enterprise buyers are tired of AI overpromising and prefer honest positioning
  7. How to stay close to product development while scaling to 1,000 employees
  8. The transition from Google engineer to startup co-founder and the skills you have to relearn
  9. Why customer success and shared roadmaps are critical for complex AI implementations
  10. The decision framework for staying independent vs. acquisition when building at scale

In this episode, we cover:

(00:00) Introduction to Arvind Jain and his journey from Rubrik to Glean

(01:27) Lessons learned building two different types of enterprise companies

(03:09) How Glean works as enterprise search and AI assistant

(06:00) The natural evolution from search to conversational AI

(08:00) Navigating the AI hype cycle and competitive landscape

(11:04) Competition strategy and staying ahead of major software companies

(16:40) Honest positioning vs. overpromising in AI sales

(20:01) Building enterprise reputation and customer relationships

(24:41) Motivation for continuing to build after previous success

(26:56) Staying close to product at scale and avoiding bottlenecks

(31:08) Using Glean internally and rapid iteration cycles

(32:18) The decision to stay independent vs. acquisition

(37:24) Transition from Google to startup founder

(43:45) Rapid fire questions and leadership lessons

(48:31) Uncomfortable feedback about constraining team speed

  continue reading

76 episodes

Artwork
iconShare
 
Manage episode 501198079 series 3462101
Content provided by Immad Akhund and Rajat Suri, Immad Akhund, and Rajat Suri. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Immad Akhund and Rajat Suri, Immad Akhund, and Rajat Suri 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.

Arvind Jain is the founder and CEO of Glean, building enterprise AI that connects to all internal company data, and co-founder of Rubrik, which recently went public. Starting as an enterprise search company in 2019, Glean has evolved into what Arvind calls "a more powerful version of ChatGPT inside your company," now approaching 1,000 employees and serving the world's most iconic companies.

What you'll learn:

  1. How Glean evolved from search to conversational AI without pivoting by riding AI model capabilities
  2. Why making it easy for customers to leave can be a competitive advantage in enterprise sales
  3. The challenges of competing against every major software company building similar products
  4. How to recruit from FAANG companies when you can't match their compensation
  5. The difference between building for established markets vs. creating new product categories
  6. Why enterprise buyers are tired of AI overpromising and prefer honest positioning
  7. How to stay close to product development while scaling to 1,000 employees
  8. The transition from Google engineer to startup co-founder and the skills you have to relearn
  9. Why customer success and shared roadmaps are critical for complex AI implementations
  10. The decision framework for staying independent vs. acquisition when building at scale

In this episode, we cover:

(00:00) Introduction to Arvind Jain and his journey from Rubrik to Glean

(01:27) Lessons learned building two different types of enterprise companies

(03:09) How Glean works as enterprise search and AI assistant

(06:00) The natural evolution from search to conversational AI

(08:00) Navigating the AI hype cycle and competitive landscape

(11:04) Competition strategy and staying ahead of major software companies

(16:40) Honest positioning vs. overpromising in AI sales

(20:01) Building enterprise reputation and customer relationships

(24:41) Motivation for continuing to build after previous success

(26:56) Staying close to product at scale and avoiding bottlenecks

(31:08) Using Glean internally and rapid iteration cycles

(32:18) The decision to stay independent vs. acquisition

(37:24) Transition from Google to startup founder

(43:45) Rapid fire questions and leadership lessons

(48:31) Uncomfortable feedback about constraining team speed

  continue reading

76 episodes

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