Tech Titans: Agents Built Around People with Mohak Shroff, former SVP of Engineering at LinkedIn

# Episode 983: Tech Titans: Agents Built Around People with Mohak Shroff, former SVP of Engineering at LinkedIn

**Section 1 of 2**

(Mohak (LinkedIn employee/engineer) at 00:00:00) But there's something novel about what we're seeing now where it's not just data extraction. I think we see that. We think of that as tedious. We think of that as a utility.

(Mohak (LinkedIn employee/engineer) at 00:00:10) This feels like it's so much more than a utility now, right? It feels like it has responsiveness. It has reaction to the things we want. It feels far more personalized.

(Mohak (LinkedIn employee/engineer) at 00:00:20) And I think that's actually probably the thing that's most magical about it—that level of personalization. It feels like... And again, at the end of the day, it's just a bunch of code. It's clearly not thinking, but it feels like it understands me.

(Joel Beasley at 00:00:42) So, you know, one of the things that caught my attention was Alastair saying you guys are building... LinkedIn's building AI agents. You gotta tell me about that. What's going on there?

(Mohak (LinkedIn employee/engineer) at 00:00:51) Yeah, absolutely. So, you know, it's interesting. LinkedIn has a little bit of a history lesson. I'd say I've been here now...

(Mohak (LinkedIn employee/engineer) at 00:00:58) What is it? It's coming up on 17, sixteen and a half years. It's a long time. And LinkedIn, it's this thing which I didn't appreciate about LinkedIn from the outside, and honestly, sometimes even from the inside, it...

(Mohak (LinkedIn employee/engineer) at 00:01:10) You have to sort of step back and take a moment to really appreciate it. But LinkedIn at its core has always been essentially an AI application, right? What do we do? We're connecting people to opportunity at massive scale. The moment you add connecting and scale, AI sort of peaks into the picture.

(Mohak (LinkedIn employee/engineer) at 00:01:29) It's part of its core, part of the picture. The way you connect people to things at scale is through AI. And so what do we do? We connect people. When someone shows up on LinkedIn and they want to learn about what's going on in the world, we connect them to other people, to knowledge, to jobs, to learning, to skills, to companies, et cetera. All of that forever has been essentially AI powering what LinkedIn does.

(Mohak (LinkedIn employee/engineer) at 00:01:53) And so, over the last two years as the world changed radically with this emergence of this new technology, with Gen AI and incredibly powerful models, these large language models, it sort of led to this moment of us asking the question of what does this mean both for LinkedIn as well as really what we do on a daily basis in terms of how we manifest the value we deliver in the world of work. I think one thing became really clear. Yes, we can continue to deliver, you know, connect people to opportunity at massive scale. We can use this technology to do so better every single day. We can make our UX more human, more easily accessible. We can make it more intelligent, more interactive.

(Mohak (LinkedIn employee/engineer) at 00:02:32) For sure, we can do all of that. But something else became really apparent—that there's a moment coming where these large language models are going to lead to the ability for a lot of what people do from a work perspective to start to actually be automated, to be done by agents. And it led to us asking the question of, as LinkedIn continues to want to be or continues to be the thing professionals look to to make them more productive and successful every single day, how do we do that in the world of agents? Right? So all these companies, everybody out there, a lot of people are thinking about agents as essentially replacing people in the world of work.

(Mohak (LinkedIn employee/engineer) at 00:03:12) It's like, what things can these agents do that'll be cheaper or faster or better, whatever it is. And I'm sitting here at LinkedIn going, hold on. We have as a core value, and have for the better part of a decade and a half had as a core value at this company, the idea that we are members first. We put the needs of our members, the ability to make our members more productive and successful at the forefront of everything we do. And so it's like, how do we take this agentic technology, these large language models applied to autonomous agents, to things that have the ability to make decisions on my behalf, to do work on my behalf, and how do we make them more human centric?

(Mohak (LinkedIn employee/engineer) at 00:03:53) How do we ensure that as that agentic shift is occurring, it's occurring in a way that puts professionals at the center of opportunity rather than displaces them? What if we could build agents that actually take all the stuff I don't want to do and do that in the way that I want them to do it, but let me continue to do those things I really want to do? It's almost like an injection of increasing my agency, enabling me to do more of what I love while the agents go and do the things that I don't necessarily want to be doing so I can do the things I got into the job for. So a really good example of this—we just recently launched a recruiting agent.

(Mohak (LinkedIn employee/engineer) at 00:04:33) And so when you look at our recruiting agent, we call it the LinkedIn Hiring Assistant. And so when you look at the assistant, the hiring assistant, it's actually really interesting. What we did was we went and spoke to recruiters. Obviously we recruit a bunch ourselves, and we reached out to a bunch of our customer recruiters and asked them, when you go and talk to a recruiter about what they do, there's this large list of things. There's a lot of time that they spend searching for candidates on LinkedIn, a bunch of time they spend kind of filtering those candidates, working collaboratively with the engineering leaders or the leaders who they're hiring for to figure out whether or not these are the right candidates.

(Mohak (LinkedIn employee/engineer) at 00:05:07) Then they reach out to those candidates to get them interested. And then some number of those people will respond to them and say, "I'm interested." And then they engage with those individuals now where they're like, "All right, ready. Now that you've responded, now I can engage and actually do the thing I became a recruiter to do," which is interact with people, talk to candidates, get you really excited about the job, help explain and shepherd you through the process, and ensure that ultimately I'm helping to build a remarkably high-quality team at the company. But there's all this really important work that happens initially or in parallel that I have to do as well.

(Mohak (LinkedIn employee/engineer) at 00:05:42) But that's not why I became a recruiter. Nobody took a job so they can run Google searches all day or LinkedIn searches all day, right? You took the job so that you could actually do this very human thing, the thing you are best suited to do in the world. And so we built the LinkedIn Hiring Assistant with this very specific goal of how can we help recruiters take this stuff that is, frankly, highly algorithmic.

(Mohak (LinkedIn employee/engineer) at 00:06:05) So I... I mean, I think it's probably very similar to everybody else. About two years ago, just over two years ago, I had the opportunity to look at GPT and play with it. And I remember one of the first things I did was, you know, I've seen intelligent AI before and I've seen it be able to answer questions. You ask it a question about what is X, Y, and Z, and it gives you an answer. I'm like, that's not that great. It's a slight improvement over search.

(Mohak (LinkedIn employee/engineer) at 00:06:34) I asked it to write me a poem. I asked it to write me a poem about LinkedIn. And I said, "Hey, here's this thing." Here's some random prompt—I forget what the exact prompt was, but it was like, "Here's this random prompt, write me a poem about LinkedIn." I remember reading the thing going, this is pretty good. It's not amazing. It's not going to be in some textbook years from now talking about great poetry, but it was pretty good.

(Mohak (LinkedIn employee/engineer) at 00:06:54) And I remember thinking to myself, this is better than I could write and I've got no creative talent. I can't write a poem to save my life. But I remember looking at it and thinking, this is extraordinary—that very soon every single person on earth will have access to technology with this creative ability. And so what was really special for me about this technology wasn't just that it was able to answer questions. I think that tech has existed before. It was two things.

(Mohak (LinkedIn employee/engineer) at 00:07:20) One, it was the fact that it had this creative angle to it. It could seem to be doing things in a way that was more human centric, where it was more relatable to me. And second was actually the interaction model.

(Mohak (LinkedIn employee/engineer) at 00:07:34) What had happened with ChatGPT was it had made AI super accessible. It went from being technology that was built into very large applications and products to something I could just talk to in a very natural way. But there's something novel about what we're seeing now where it's not just data extraction. I think we see that we think of that as tedious. We think of that as a utility. This feels like it's so much more than a utility now. It feels like it has responsiveness. It has reaction to the things we want. It feels far more personalized. And I think that's actually probably the thing that's most magical about it—that level of personalization.

(Mohak (LinkedIn employee/engineer) at 00:08:14) It feels like, and again, at the end of the day, it's just a bunch of code. It's clearly not thinking, but it feels like it understands me.

(Joel Beasley at 00:08:24) Have you heard the GPT voice thing?

(Mohak (LinkedIn employee/engineer) at 00:08:27) Yes, absolutely.

(Joel Beasley at 00:08:28) Have you talked to her? Yes. It's a "her" for me. Okay. So I used this morning. Maybe I'm going to try to use it right now just to show you what I did real world. So I woke up this morning, and we're getting a fence installed. I'll actually tell her while we're doing it. All right. So I woke up this morning and we're getting a fence installed.

(Joel Beasley at 00:08:48) And the guys who are out installing the fence don't speak English. They speak Spanish. I do not speak Spanish. The gate is currently 13 feet wide. It's supposed to be 20 feet wide.

(Joel Beasley at 00:08:59) Can you tell them in Spanish that I need the gate to be 20 feet wide, not 13 feet wide? Sure. You can tell them...

(Mohak (LinkedIn employee/engineer) at 00:09:17) That... That's in...

(Joel Beasley at 00:09:19) This is the... There was no additional app to install. There was no training. There was no setup and registration and fee. It was just, "Can you do this?" Yeah.

(Mohak (LinkedIn employee/engineer) at 00:09:27) And so I envision this future where the way you put humans at the center of this is by having the equivalent of a chief of staff but in a digital sense. You need this digital concept that manages, that organizes all of them. So, you know, I'm going to harken back to my early days as an engineer. I was a huge Emacs user. So my first internship in college, I end up with a mentor who got me on the Emacs train.

(Mohak (LinkedIn employee/engineer) at 00:09:54) I'd been all vi prior to that, and he got me on the Emacs train. And I created that... Doing that internship, I created a dot Emacs file. And I carried that dot Emacs file from task to task, job to job, thing to thing constantly. And what was great about it is that everything, every new thing I picked up, it still felt familiar. My shortcuts were the same, my key bindings were the same, my autocorrect was the same. It knew not to stick a W in my name every time I tried to autocorrect to Mohawk—M-O-H-A-W-K, M-O-H-A-W-K.

(Mohak (LinkedIn employee/engineer) at 00:10:27) And so I'm like, stop doing that. And so it had all of that. And then one day I stopped using Emacs because it was no longer cool and I was no longer an engineer. But then I lost that, and since then every tool I've used, every new tool I pick up wants to insist that it wants to relearn everything about me, and it starts off being really clunky and hard to use, and that sucks. Now just imagine that in the world of agents. This thing is going to try to send out emails on my behalf.

(Mohak (LinkedIn employee/engineer) at 00:10:54) This thing is going to try to search the way I... it thinks I want to search. This thing is going to try and write text the way it thinks I write. And if every single one of these agents has to be retrained and retaught and remanaged and re re re re, it's like massive cognitive overload. And so we envision a world where you have the equivalent of a digital chief of staff.

(Mohak (LinkedIn employee/engineer) at 00:11:17) I mean, I think, you know, it's early days. What I love about this period is, I mean, doesn't this just feel like a playground right now? We're all...

(Joel Beasley at 00:11:23) It does.

(Mohak (LinkedIn employee/engineer) at 00:11:24) We're all witnessing some remarkable technology being born and some remarkable use cases built on top of the technology. I feel like the moment we're in is kind of akin to the birth of the internet in the sense of... TCP/IP exists, right? Everyone thinks that's a big deal, but it kind of isn't, right? The big deal was the browser.

(Mohak (LinkedIn employee/engineer) at 00:11:47) That's the thing that suddenly... HTML and the browser and the massive level of accessibility that was created around, oh, people can build web pages and host them on servers, and all of a sudden this huge explosion of value occurs. I think we're at that point. What we've seen right now is the baseline technology, the ground technology that will power a lot of the incredible value that will come. I had the opportunity to sit down with a very junior engineer recently and just watch as she worked, just because I wanted to get a sense for what it's like to be a new engineer, not just at LinkedIn, but in the world. And dude, it was such an interesting experience.

(Mohak (LinkedIn employee/engineer) at 00:12:27) All the things that I remember doing, she was just breezing through because of Copilot. She was in GitHub using GitHub Copilot, and it was like, "Hey, Copilot, what is the UNIX command for this? Hey, Copilot, how do I do this? Hey, Copilot..." And I was just like, whoa, that would have been a question to some senior engineer that took me six hours because they were too busy to respond or it would have been me standing up and... It was just nonstop, unimpeded productivity. And it's really magical. And so to your point, workflows are already changing.

(Mohak (LinkedIn employee/engineer) at 00:12:57) People are already starting to adapt and productivity is just, you know, exploding. It's really kind of special.

(Joel Beasley at 00:13:03) Hiring a team. Yeah. It's like I'm delegating the edits to Josh, hoping that we have an aligned vision and looking at his track record and having enough trust to say, "Okay." And nothing's perfect. You have to balance everything with that.

(Joel Beasley at 00:13:16) When I was making the decision about the LLMs for the outreach and I was doing batches of hundreds and then reviewing them and then tweaking the prompt and all of that. And I got it dialed in to where I know one in seventy-five is going to be not the best way that I could have said it if I were doing it, but the time benefit cost analysis says run. Run with it because now I can do 10,000 a day, and it's just happening.

(Mohak (LinkedIn employee/engineer) at 00:13:44) You know? And so I think this is important. The thing I would say to everybody who's playing with agents is there's... Nature has real, what's the word, real lessons for us, right? The way we work with each other should be highly informative to how we think about how we want agents to work with us.

(Mohak (LinkedIn employee/engineer) at 00:14:10) So I want an agent that does... that works with me the way Josh likely works with you. As you scaled your relationship, as you sort of ramped up on the relationship, initially it's highly collaborative. He's like, "Hey, Joel, I've got this question. I want to make sure we're aligned. You're okay, this looks good." Lots more communication.

(Mohak (LinkedIn employee/engineer) at 00:14:31) As the trust builds, you delegate more. He feels more independent. He's escalating less as the trust builds. And over time, the level of actual escalation and the level of collaboration reduces because now he's able to drive a lot of this stuff solo.

(Joel Beasley at 00:14:45) As far as engineering leaders, how are they thinking about the future of AI agents? What's one piece of advice that you'd give all engineering leaders?

(Mohak (LinkedIn employee/engineer) at 00:14:53) Yeah. Well, can I do two?

(Joel Beasley at 00:14:55) Yeah, you can do two.

(Mohak (LinkedIn employee/engineer) at 00:14:55) Alright, I'll do two. So two pieces of advice. One is, I think—well, actually I'm gonna cheat into three, just rule of three, it's important. Alright, first is, I think the most important thing is to optimize for flexibility and optionality.

(Mohak (LinkedIn employee/engineer) at 00:15:09) Things are gonna change. Your conviction is fantastic and building against conviction is important. That's kind of how you invent the future. But at the same time, what's actually also really important is, like, create the optionality that allows you to—as things become more clear, either for yourself or from the world at large, as you see things being invented or built that's getting traction or that's like there's an interesting idea, sort of a modicum of value there—you can double down on it. And so build for optionality is sort of thing number one.

(Mohak (LinkedIn employee/engineer) at 00:15:39) Thing number two is, you know, this piece of wisdom I heard from Kevin Scott, actually, which was that in moments like this, it's always really natural for us to lean on doing the thing that we feel like we understand and sort of making it incrementally better. It's like, I can do this thing that I've done for years and make it 20% better, 30% better, 40% better. But the real magic is in doing the thing that was impossible before, right? Like, this technology makes possible things that previously were truly impossible or impractical. And that's where real innovation is and that's where real value gets created. And so that's the second thing: really push on—way back when we last chatted, I talked about complaining as like—

(Joel Beasley at 00:16:23) Yeah.

(Mohak (LinkedIn employee/engineer) at 00:16:23) Accord engineers. Like, I think about, in the modern—in this manifestation—complaining as a path to pushing on, like, what are the things I cannot stand about the state of tooling or the world or technology that for once, finally, maybe not perfectly but finally, can be solved. I think there's this massive upside and massive value, innovative value, in that. And then the last thing I'll say is really focusing on human centricity.

(Mohak (LinkedIn employee/engineer) at 00:16:56) Like, I think it's easy with tech like this to just get geeked out as, like, tech for the sake of tech and technology for the sake of technology. And I think that real value ultimately has to tie back to ways that it helps all of us feel more productive, more successful, more effective, more able to do the things we love, more able to be happy and feel joy. And it's something that we—like, all three of these are things that we try to bring every day to the work we do at LinkedIn, to AI, to just everything we do. And I would just love for every engineering leader to think about that as kind of the core of how they bring technology to life, especially in this moment.

(Joel Beasley at 00:17:38) Thank you so much for listening. And if you found this episode useful, please share it with a friend or a colleague who you think would get value from it. And if you have topics that you'd like to hear discussed on the podcast, either add me on LinkedIn or send me an email: [email protected]. Every time I get an email or LinkedIn message, it absolutely makes my day and inspires me to keep going.