Why We’re Only Using 1% of AI | Glean CEO Arvind Jain
Timestamps are as accurate as they can be but may be slightly off. We encourage you to listen to the full context.
Podcast Summary
Arvind Jain, founder and CEO of Glean, returns to the show as his company has grown into a $7.2B AI platform serving enterprise customers. This episode explores the intense challenges of scaling an AI company in the most competitive landscape imaginable. (00:00) Jain discusses how Glean has evolved from being the only player in enterprise search to competing against tech giants like OpenAI, while growing to over 1,000 employees. The conversation delves into his philosophy that "if you build something last year, that it's got to be obsolete" (25:00), and reveals how he's fundamentally changed his own working habits using AI to conduct strategic research before engaging his team.
- Main Theme: Managing hypergrowth and brutal competition in AI while maintaining innovation velocity and organizational agility.
Speakers
Arvind Jain
Founder and CEO of Glean, a $7.2B enterprise AI platform and workplace search company. Previously co-founded Rubrik, which went public, establishing him as a serial entrepreneur with deep experience in enterprise software. He started his career at Google where he learned the importance of strategic thinking and writing from some of the industry's best leaders.
Joubin Mirzadegan
Partner at Kleiner Perkins where he focuses on enterprise software and AI investments. He has been closely involved with Glean since its early days, when the company was literally started in the Kleiner Perkins basement. Currently incubating his own pricing and billing software company.
Key Takeaways
Embrace Organizational Evolution as You Scale
When Glean crossed 1,000 employees, Jain's first emotion wasn't celebration but panic, recognizing that the skills that got them there wouldn't take them further. (07:48) He realized that with a thousand people across 100 cities, alignment and prioritization became exponentially harder. What used to be solved by walking into a room and announcing a decision now requires sophisticated organizational design. The key insight is that founders must force themselves to learn and adapt, developing process-building skills even when it goes against their natural instincts. This means accepting that creating systems and documentation isn't bureaucracy—it's enabling scale without losing velocity.
Default to Obsolescence Thinking
Jain operates with the mindset that "if you build something last year, that it's got to be obsolete" because the technology stack evolves at unprecedented pace. (26:00) This philosophy extends beyond just updating code—it means actively rewarding teams for throwing out old code at the same level as building new features. In the AI era, traditional moats become liabilities because you must evolve constantly to adapt to shifting technological foundations. Companies that cling to what worked before will find themselves with legacy systems that can't compete with focused players building on cutting-edge capabilities.
Focus Beats Scale in Competition
Despite pressure to expand into multiple areas, Jain believes that "if you're trying to be everything to everyone, then you just cannot compete with somebody who's focused on a smaller problem and going deep into that." (36:00) Even tech giants like OpenAI will eventually consolidate their bets and go deeper into the most important areas. For Glean, this means positioning as a horizontal AI platform that provides deep enterprise context to other vertical solutions, rather than trying to build the best product for every function and department. The winning strategy is becoming an indispensable platform that powers other experiences.
Transform Decision-Making with AI Research
Jain has fundamentally changed his working model by using AI to conduct deep strategic research before engaging his team. (54:00) Instead of immediately asking team members questions and creating distractions, he first asks Glean to produce comprehensive two-page reports on complex business questions. This allows him to come to discussions more informed and surgical in how he consumes others' time. The approach eliminates bias since AI provides more objective, comprehensive analysis compared to asking team members who might filter information through their departmental worldview. This creates a new collaborative model where AI serves as an incredibly effective personal colleague.
Test for AI Fluency Across All Roles
Glean now tests for "AI fluency" in all hiring, not looking for expertise but for curiosity and willingness to do things differently. (40:00) The goal is identifying candidates who show interest in the AI revolution happening around them and demonstrate they want to approach work with new methods rather than traditional approaches. This isn't about technical AI knowledge but about mindset—are they someone who will be AI-forward and open to reinventing their processes? The hiring approach recognizes that in a rapidly changing technological landscape, adaptability and curiosity matter more than just past accomplishments.
Statistics & Facts
- Glean has crossed 1,000 employees and is spread across more than 100 different cities with their field team. (07:48) This milestone triggered Jain's realization about the complexity of organizational alignment at scale.
- The company is valued at $7.2 billion and is likely to double their workforce again this year, potentially reaching 2,000 employees. (58:08)
- According to Jain, we've only used about 1% of current AI model capabilities, indicating massive untapped potential even without further model improvements. (32:30)
