Arvind Jain
speaker
456 appearances
1 recordings
1 series
first heard Jul 2026
last heard 11 Jul
Arvind Jain’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Jul 2026 with 1.
Appearances
So today, the way to think about Glean is that first, it's a super set of JetGPT, Cloud, Gemini, all of those combined into one product experience.
It's a coworker for your employees, and it's connected to all of your company's context, how work happens inside your company.
Two things.
One, they're terrified of them, like in the sense that, I mean, just like every software company is worried about that, hey, will we be in business?
Will the models eat it all?
Similarly, enterprises leaders also worried that is their sort of core IP, their data, their information, as well as their way of learning, their way of doing things, like would it all be, will they be subject to too much of technology dependence on these model providers?
So that feeling is there for sure.
But I think what he said was that AI is not working in enterprises, then everybody's afraid to actually say so, because it's not a cool thing to say.
Well, depending on the enterprise, yes.
If we are talking about fundamentally changing how people work, and if we are saying that majority of the work that we do today is going to be done by an agent, which is fully powered by one of these frontier model companies, then in some sense, you've now transferred a lot of your operations to these technology providers.
This is more than technology dependence.
This is actually real sort of operational dependence on the companies that are actually running those agents for you.
It's actually interesting.
If you think about how work happens over time, like when you initially do a task for the first time, maybe you'll document a process, like what are the 10 steps you need to take to actually complete some piece of work.
And then over time, people start to sort of optimize and tweak that process.
A lot of it never gets documented.
And you're sort of based on doing this work over and over again, you've now built all these learnings that you apply in real time to do this work.
In the future, all of that institutional learning is actually going to accumulate in that agent that is doing that work.
If you don't have any control on running that agent yourself, if you don't own the learning that it actually gains over the years, then you're basically fully dependent on these AI companies to get your work done.
So it's absolutely, I think there's a fundamental question in front of enterprises today.
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