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Arif Ender

Arif Ender

Director of Compensation for EMEA & LATAM at Palo Alto Networks; Total Rewards expert with 20+ years experience including Meta and Mars.

Aug 9, 2026

11:00
saying is data, you know, as the foundation of your AI models and getting your house in order before you build is a pivotal moment.
11:15
Of course, yeah.
11:18
And I can give you an example on that one.
11:21
We are in Google Workspace here.
11:23
So we are using Notebook LM.
11:25
And one of the ideas we had, like, you know, we are getting a lot of tickets from the recruiting about, you know, what is the allowance in this country? What is, I don't know, job to price in that country? Is this country eligible for providing RSU? Like all these questions, technically super basic questions with maybe one policy to be explained or referred to and stuff.
11:50
So let's do a... a library on notebook lm you know basically we just upload all the policies all the tables that is open to ta and create it as a chat bot you know they can go instead of raising a ticket waiting for a certain sla they can literally get it in seconds they typed an excellent idea yeah the problem we had one or two policies uh we used the outdated versions And that's where I say, you know, that that mistake can multiply at scale.

9 MINS LATER

21:03
First of all,
11:16
yeah.
11:18
And I can give you an example on that one.
11:21
We are in Google Workspace here.
11:23
So we are using Notebook LM.
11:25
And one of the ideas we had, like, you know, we are getting a lot of tickets from the recruiting about, you know, what is the allowance in this country? What is, I don't know, job to price in that country? Is this country eligible for providing RSU? Like all these questions, technically super basic questions with, with maybe one policy to be explained or referred to and stuff.
11:50
So let's do, let's do a. a library on notebook lm you know basically we just upload all the policies all the tables that is open to ta and create it as a chat bot you know they can go instead of raising a ticket waiting for a certain sla they can literally get it in seconds they type an excellent idea yeah the problem we had one or two policies uh we used the outdated versions And that's where I say, you know, that that mistake can multiply at scale.
12:28
Basically we had to clean up so much mess in couple of offers because the outdated policy had obviously different numbers, which were outdated.

6 MINS LATER

18:53
But what's your advice for them in terms of how they can upscale and avoid becoming obsolete in the market? But it's not just for juniors, right? It's also for seniors.

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