Arvind Jain
Co-founder + CEO, Glean · Former Distinguished Engineer at Google; co-founder, Rubrik
aka Arvind
“You hear these 95% of projects fail. But like, you know, like, that's actually what you want. Like when you are actually experimenting with new technology, if all of your projects are failing, that means you just not trying enough at the moment. So when I read the study, it was not a surprise for me. We're gonna actually see hopefully similar stats next year too, because we want everybody in the industry to be really eager and experiment and actually figure out how to actually get benefits from this technology.”
“AI is not actually extending software in a marginal way. It's a different product and in fact it's actually going to grab a lot of revenue that actually today is in services industry which is 25 times larger than software industry. So there's a lot of spend that is going to move. I mean the spend that you see happen on AI is actually sort of those service dollars that are converting into AI or software dollars.”
“I'm excited about products that are going to change the paradigm where instead of you building a product and expecting people to come to you, if you understand your user, your customer very deeply and actually bring AI to them, that's the category that I'm excited about. I want to see more proactive AI products coming into the market next year. That is what is going to actually take it from a 5% of the users being power users to 100%.”
“It's actually an interesting thing with engineering today is you build systems and never before have you been in this mode where you start with a great idea and it doesn't seem like a good idea anymore within two weeks because we see a new development that happened. So we have numerous failures and in engineering on that front, like for example, some of our fine tuning work, building models for a specific use case within our product didn't really pan out for us. And ultimately the choice was that we can go with already built models, whether they are small open source models hosted on databricks or one of the large foundation models.”
Arvind Jain
One-line summary: Co-founder + CEO of Glean (enterprise AI search / personal-companion platform); previously co-founded Rubrik; Distinguished Engineer at Google. Tracked here for Dec 2025 framing on enterprise AI deployment patterns and the 'proactive AI products' vision.
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Speaker-attributed claims extracted from diarized sources. Each bullet mirrors one entry in quotes: frontmatter — keep them in sync.
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"You hear these 95% of projects fail. But like, you know, like, that's actually what you want. Like when you are actually experimenting with new technology, if all of your projects are failing, that means you just not trying enough at the moment. So when I read the study, it was not a surprise for me. We're gonna actually see hopefully similar stats next year too, because we want everybody in the industry to be really eager and experiment and actually figure out how to actually get benefits from this technology." — 2025-12-23-bg2-databricks-glean-enterprise-ai (2025-12-23)
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"AI is not actually extending software in a marginal way. It's a different product and in fact it's actually going to grab a lot of revenue that actually today is in services industry which is 25 times larger than software industry. So there's a lot of spend that is going to move. I mean the spend that you see happen on AI is actually sort of those service dollars that are converting into AI or software dollars." — 2025-12-23-bg2-databricks-glean-enterprise-ai (2025-12-23)
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On chatgpt-super-assistant-vision:
"I'm excited about products that are going to change the paradigm where instead of you building a product and expecting people to come to you, if you understand your user, your customer very deeply and actually bring AI to them, that's the category that I'm excited about. I want to see more proactive AI products coming into the market next year. That is what is going to actually take it from a 5% of the users being power users to 100%." — 2025-12-23-bg2-databricks-glean-enterprise-ai (2025-12-23)
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"It's actually an interesting thing with engineering today is you build systems and never before have you been in this mode where you start with a great idea and it doesn't seem like a good idea anymore within two weeks because we see a new development that happened. So we have numerous failures and in engineering on that front, like for example, some of our fine tuning work, building models for a specific use case within our product didn't really pan out for us. And ultimately the choice was that we can go with already built models, whether they are small open source models hosted on databricks or one of the large foundation models." — 2025-12-23-bg2-databricks-glean-enterprise-ai (2025-12-23)
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