He co-founded a $25B company. Then built a $7.2B one - Arvind Jain [Glean]

Today on BILLIONS, I’m sitting down with Arvind Jain, founder and CEO of Glean. Before Glean, Arvind spent years at Google working on search, then co-founded Rubrik, which became a multi-billion-dollar public company.Instead of retiring, he started again from scratch. Today, Glean has crossed $300M ARR and was last valued at $7.2B. And Arvind has some very strong views on where AI is going next.He believes open-source models will ultimately win for most technologies, and says they can already handle 80–90% of what enterprises want to do with AI. He also believes frontier models will increasingly become indistinguishable from one another.Which raises a much bigger question:If the model itself becomes a commodity, where does the real value live? For Arvind, the answer is context. In this conversation, we break down: → Why Arvind started again after already building a multi-billion-dollar company → How a problem inside Rubrik led to the creation of Glean → Why enterprise context may matter more than the underlying AI model → How Glean reduces hallucinations by validating AI outputs against company data → Why enterprises need more than “zero data retention” to safely deploy AI → Why Arvind believes open source will ultimately win → Why open-source models can already handle 80–90% of enterprise AI tasks → Why frontier models could become increasingly commoditized → How Glean routes every task to the right model based on quality and cost → Why specialized smaller models can outperform frontier models on specific tasks → Why AI may actually make us work MORE, not less → Whether intelligence still matters when everyone has access to AI → How AI agents could fundamentally change the way the internet is designed → Why autonomous agents could potentially spend hundreds of thousands of dollars per day without the right guardrails → What Arvind thinks Google and Gemini need to do next → The biggest mistake he made while building Glean One of the most interesting parts of the conversation:Glean was already training transformer-based language models for individual enterprise customers in 2019, years before ChatGPT launched. If you want to understand where enterprise AI is really going, beyond the hype around the latest models, this is the episode. TIMELINE: 00:26 – Arvind Jain: from Rubrik to $7.2B Glean 00:52 – Why start again after already building a huge company 02:24 – How Glean works and why enterprise context matters 04:57 – Solving AI hallucinations with validation 06:28 – Keeping enterprise data safe with AI 09:43 – Why Arvind believes open source will win 11:57 – If AI models become commodities, where is the moat 14:47 – Why specialized AI models will outperform general models 16:50 – How Glean chooses the best model for every task 19:00 – How to actually measure whether AI did a good job 21:13 – Will AI make us work less… or more? 23:42 – What happens when intelligence becomes abundant 26:41 – How AI agents will change the internet 29:24 – Building at AI speed inside slow-moving enterprises 34:09 – Arvind’s take on Google, Gemini and frontier models 36:16 – The one thing he would do differently building Glean 37:28 – Where to follow Arvind and Glean