Glean’s Breakthrough: CEO Arvind Jain on Scaling AI Agents & Search
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Why are AI model races accelerating and what does it mean for enterprises?
The future that I see with AI is that every person who works is going to have this amazing team of assistants, coworkers and coaches around them that is going to actually make them a lot more effective.
Welcome to the Matt Podcast. I'm your host, Matt Turk from Firstmark. Today, my guest is Arvin Jane, the CEO of Glean, one of the hottest enterprise AI companies in the generative AI wave, widely rumored to be valued at $7 billion in a new round of financing. Early in his career, Arvin spent more than 10 years at Google, which he joined pre IPO as an early engineer on search. He then went on to be the co founder of Rubrik, a data security. Startup that's now become a public company with a market capitalization of over $11 billion. In this conversation, we go deep on Glean's AI search product and then spend plenty of time on AI agents in the enterprise, both technically and from a broader industry standpoint.
Given his life's work, Arvin has a unique and very pragmatic perspective on the evolution of search and what AI can actually do within organizations.
There is real value being delivered to customers, but agents are still better run in a supervised manner where a human is in charge and can get the work of the agent.
Please enjoy this great conversation with Arvind of Galeen. Arvin, welcome to the Metapodcast.
Thank you for having me.
This feels like a very uh timely uh moment to have the conversation uh about Glean. It seems that you guys are uh firing on all cylinders. You had uh a uh well publicized uh remarkable year in terms of of AR acceleration. Uh you made just a few weeks ago what feels like a really important release around agentic reasoning. Uh and uh of course there are rumors which I will not ask You to confirm nor deny that there may be another big round afoot uh with a rumored uh seven billion dollar uh valuation. So thanks for making the time in the in the middle of all this to to chat with us. We're going to unpack all things at Glean, so enterprise search, uh rag agents. Uh but before we do that, I thought it'd be a fun uh way to start to sort of riff a little bit on what's going on in the industry.
So It's been yet another wild week in in AI. Uh, you know, over the last few days, we had the release of uh 03, of 04 mini, and then the just the day after there was a release of uh GNI 2.5 Flash. So I'm curious, uh, as an industry participant and an observer, uh, what do you make of all of this? And and uh where do you think we're heading in terms of uh what the AI model world? Is going to look like in a few years? Are we going to have a bunch of models? Are we going to have a small number of like very powerful model and model companies?
I think all indications are that there's going to be a very large number of models that are going to be available to us uh in the industry. Uh it's going to be both close close uh models uh from companies like OpenAI and Entropic and Google. Um but also there's gonna be a lot of open domain models. Um models that are like, you know, for example Lama and then a lot of derivatives as well um that are going to be available to us. So that's that that is already happening. It's just gonna you know, there's gonna be more and more of that in the future. Um what it means for us is like we you know we we will be in this world where it's gonna be hard to actually always keep up with um the model technology uh like for for all of us.
I think it will become increasingly more a deeper uh infrastructure level thing that then software developers actually make sense of and figure out like for for a given application for For a given use case, what's the right model technology to use? And hopefully for enterprises, for customers, the L LMs, you know, become a technology that they don't really think about. Uh it's just, you know, something in the background.
And you just mentioned uh open source, and I think you've said somewhere that um 80% of the AI work may rely on open models. Um what's your sense of the reality in the enterprise today, of the state of preparedness and and adoption of uh open source AI models?
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Chapters
5 chapters
1
Why are AI model races accelerating and what does it mean for enterprises?
0:00–12:23
2
When should enterprises choose open‑source models over closed‑source ones?
12:23–24:35
3
What exactly are AI agents and why are they emerging now?
24:35–35:58
4
Which real‑world business processes are best automated with Glean agents?
35:58–48:01
5
Is the technology ready for fully autonomous agents by 2025?
48:01–52:08
Speakers
1 identifiedMore from The MAD Podcast with Matt Turck
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