Stanford AI Expert: 71% of People Won't Survive the AI Shift — Here's the 30-Minute Fix | Kian Katanforoosh, CEO Workera

12:46Kian Katanforoosh:And so right now, I think historically we've had, I don't know, eight engineers, one product manager, one product designer. I think now it's getting way more efficient on the engineering side, where you can actually probably put the team together with two engineers, one product manager, one product designer. And the engineers are very empowered to perform, to build everything on their own almost with some input from the other parties. And so we are seeing at WorkCara a lot of smaller teams. A lot of, instead of having three big teams, we might have six, seven smaller teams that have more ownership of their surface area.

13:22Kian Katanforoosh:We have transcriptions of meetings, which is really helpful because I can remember what was the context. We use our own product in our interviewing. So there's an AI interviewer. Oh, wow. I think we just make all these tools accessible to our workforce and we make sure they adopt it very frequently.

13:41Marina Mogilko:Who does your calendar? Is it AI now?

13:44Kian Katanforoosh:Every morning I have a briefing. So my assistant built AI systems herself. And she has a little agent call it or workflow So that tracks my calendar and tracks what I know or what past conversations I've had. And every morning I get a briefing automatically in Slack that tells me this is where you need to be. And this is what you need to know. Nice. Pretty much. Which is really helpful, you know.

14:10Marina Mogilko:Yeah. Everything that you described, if I want the same in my company, do you think I need to hire someone who's more AI native or my team can just handle it? No, you should not. And we're all like creatives.

14:19Kian Katanforoosh:Yeah, I think you should start yourself. It all starts by yourself. So I think you should try it yourself and you will actually figure out that you can get a lot done by yourself. And you're already very proficient, so it will be easier probably for you. If you want to get in the technical realm, yeah, you will need someone more technical. You need someone who has coded in the past. You can get a lot more done.

14:41Marina Mogilko:But the basics like connecting documents and we should have done that. I think it's more about agency.

14:48Kian Katanforoosh:It's having agency to do that.

14:50Marina Mogilko:And that's agency. I'm glad that you mentioned it because I was thinking a lot being here in Davos, everyone's talking about AI. I was thinking about top three skills that everybody should be developing. And I think you mentioned that in one of your talks. There's some skills that die out really fast and some skills that just stay with you. They have more longevity. And I think agency is something that, you know, if we imagine AI as this bar, it's already telling some people what to do. Like they're kind of below AI. Like if you work in customer support, right? You just prompt something and you read it out loud.

15:23Marina Mogilko:Most of us are still beyond this line because we're using AI as helper. But this bar is rising. What do you think? And the way to stay beyond it and make AI work for you, not control you, is to have agency and maybe something else. What do you think?

15:39Kian Katanforoosh:I'd say 100 % agency is a durable skill. We feel it. Durable as in it will be useful even 10 years from now. It's very important. There's a lot more durable skill. critical thinking, problem solving, effective communication. I think AI literacy is a durable skill. People will need it for a long time. Coding, I think, is a very important durable skill.

16:00Marina Mogilko:Still, even for someone like me who's a podcaster.

16:03Kian Katanforoosh:I think so. I don't think you'll have to learn syntax. You don't need to know how to code manually. But if you can tell if the coding agent is, what is it doing, you have a significant advantage. You can catch the errors faster. You can iterate faster. it is hard to negligent that. And then to come to the top three skills, I think like I'd separate in three groups. So for technical folks, very technical folks, like foundational model level. Right now, companies are fighting for talent that can do reasoning, that can build reasoning loops and reasoning models. There's very few people in the world that can do it.

16:41Kian Katanforoosh:And they're very, very valuable. The second one that's underrated, forgotten sometimes is distributed computing. There's not that many people that can build clusters, that can train models on massive clusters. It is very complicated. It requires a combination of math skills, linear algebra, electrical engineering. It's very, very complicated. And those are, you know, hardcore engineers, very valuable. And then the third one is reinforcement learning. So in AI, when you look at a model, it usually goes through different phases of training, like pre-training and post-training. People that have, and at some point in the sometimes free training, sometimes post-training, there are certain techniques from the world of reinforcement learning.

17:21Kian Katanforoosh:That's why the idea is like AlphaGo or chess. Those games that you've seen AI play better, they're based on reinforcement learning methods.

17:31Marina Mogilko:When the machine learns by itself and tries different things.

17:34Kian Katanforoosh:It learns through experience, not through examples. Yeah. And that skill is also very valuable. So that's the technical tier. In the applied tier, I would say forward deployed engineering is very popular, meaning if you can also do business and be technical at the same time. That combination is very rare. And then for day-to-day life, I think identifying AI, being able to use it natively is the most popular skill for general awareness.

17:59Marina Mogilko:Kion just talked about how most people use AI every day, but their prompts are still super basic. Take my example. For months, I was struggling with AI writing. It just didn't sound like me, it used the wrong words, it used the wrong tone, it invented facts, and overall sounded like AI. So I decided to build a system. Three files that teach AI your real voice, real facts about your background, and even your phrases you'd never say. And this transformed my entire workflow because I can now write better LinkedIn posts, I can now write better emails, and come up with better ideas. All of these files are free for my newsletter subscribers.

18:36Marina Mogilko:There is a link in the description. Go ahead, download those files. And they come with an instruction on how to teach your AI to speak like you. The technology is amazing. Start using it in a proper way. The link is in the description. So do you see jobs market going down at all? Or what's your projection for the next five years?

18:56Kian Katanforoosh:So a few things. I would say, one, people say Gen Zs. There's no job for Gen Zs. We've heard that over the last couple of years. I think last year was definitely the hardest I've seen for university grads.

19:08Marina Mogilko:But was it about AI? Because a lot of people...

19:10Kian Katanforoosh:I don't think so. Yeah, overhiring during COVID. I think companies have overhired during COVID. And now they're saying AI is automating our stuff because it makes the stock go up. The truth is they're performance managing a lot. They're roster managing. They're exiting people. And maybe there's a little bit of that job is not as important as it used to be. But there's a lot of like, we want to keep our best people. And they hide it behind the AI lingual. So, you know, why would Meta exit people from their metaverse team if it was AI? You know, no, it's because they wanted to make more out of that team.

19:44Kian Katanforoosh:And he probably thinks they can get a lot more done keeping the best people and getting them to work hard. You know, otherwise you wouldn't have heard about the metaverse team exiting people. You would have heard of something else. So I think it's really performance management that is happening. And I think they don't find enough AI native talent. The reason Gen Z has struggled to find jobs in the last year is that there's just not enough AI native talent in the markets. There are still just pockets that are in hubs. And if you're in the hub as a Gen Z, actually, you can do fairly well today. There's good offers.

20:17Kian Katanforoosh:There's good opportunities. When you're outside of the hub, it's very hard. It's much more difficult. So long story short, what I think is going to happen is over time, companies are going to figure out how to update their workflows. So yes, you will see productivity go up and you will see a lot of movement internally. I think we're going to see more internal mobility than we've ever seen in our life. It will be very common for you to start in the marketing team and go to the sales team, start in the sales team and go to the HRVP team whenever you need to move. That's the movement inside the company is going to grow.

20:48Kian Katanforoosh:The company's total headcount, I think, is going to decrease. I think on average, companies are going to be slightly smaller, but it's not going to be a massive cut. It's going to be, you know, every year, maybe they don't backfill people who retire. They just don't hire more, you know. Or if someone leaves, they probably try to do a cultural refresh by bringing AI native talent that is coming out of universities. And at the same time, they invest in their talent to build AI native mindset inside the company.

21:18Marina Mogilko:Do you think university loses its value in the next 10 years?

21:23Kian Katanforoosh:Yeah, yeah, I think so. I think unless you're a top-tier university where you have brand defensibility, people don't join for the content. They join for the network, the brands, being surrounded by people that work hard, that are ambitious. Those will not lose their values. So when you think about the university, you think about a bundle. Like universities have content, mentorship, research, blah, blah, blah. And that bundle will for sure change. I think it's going to be a different offer. Maybe it's not going to be four-year bachelor's degree, two years master's. It's going to share. I think one of the weaknesses of universities today is the mismatch of the job market skills needed.

22:03Kian Katanforoosh:Like you have too many universities that still teach skills that you won't need. You know, I come from France and I recall when I was a student, we had double the amount of physical educator being trained and the amount of jobs available after they graduate. You don't want a society that has that. You want a society that has a zero skills gap. At all points, the people that are joining a job market have the exact skills that the market needs. It's not an easy problem, but I think universities could be better at it.

22:30Marina Mogilko:Yeah, and it's really hard for universities to do that, right? Super hard. Because you have a program that's established.

22:35Kian Katanforoosh:One model is universities focus on durable skills. And then companies build the capabilities to teach perishable skills. So, for example, the problem is reasoning. Reasoning, the people who know reasoning, they're PhD students from the top AI labs in the world. That's where they come from. So it is coming from universities, generally. Ideally, you would want all universities to give you AI-native talents. Everyone who graduates has amazing AI skills. They're not specialized in a specific area, but they have great durable skills. Join the company, and the company has somehow a stack, an HR and learning stack, that can take on board an employee, and instead of them becoming a partner at a consulting firm in seven years, they become in six months.

23:16Marina Mogilko:Yeah.

23:17Kian Katanforoosh:And that would be ideal, I think.

23:18Marina Mogilko:And that's what you do at Workera, right?

23:19Kian Katanforoosh:Yeah, we help a lot of companies do that. We do part of this problem. But the general idea is durable skills taught at school, perishable skills taught at the company.

23:28Marina Mogilko:I love that. This is exactly how universities should be working, right? Not only now, but also like 20 years ago, because skills keep changing. I think in WorkCara, you have AI agents, right, that work in production, and a lot of companies are failing to build those AI agents. Also, we tried in my company. We have a media company. We're not that technical. But from what I see, agents sound great. But then in real world, it's still like a set of steps that they're following. And you still need a lot of human work. Can you tell me why in your company they're working and they're not working for a lot of other companies?

24:03Kian Katanforoosh:Yeah, for sure. I think it is very, very hard to put an agent in production. People don't realize that. A demo is not a production agent. You have demos are so easy to do now. You see so many of them. If you can tell the difference between a demo and a production system, then you know how hard it is. And that's why MIT's study said only 5 % of agents work in production. So I'll give you some examples. The reason I think, so we've done large deployments. One of the companies that is here, Bill McDermott, the CEO of ServiceNow, is here. ServiceNow uses WorkAra enterprise-wide. So everybody is being measured, mentored, skills gap identified, and they get sort of an AI driving license, essentially, a certificate for the year.

24:47Kian Katanforoosh:That agent has been deployed very large scale. For this to happen, there's so many things that can go wrong. OpenAI can fail. What do you do? We have a model routing layer that allows us to route immediately to the next best model. Translation, people have different languages. It's not as easy as just saying, oh, do the assessment in Japanese. It's not at all as easy. If a Japanese person looks at that, they would say it has a lot of cultural gaps. It is not culturally intelligent. So it's so much hard work in there. The agent has to be connected to the UI and somehow the agent misses a button.

25:26Kian Katanforoosh:It just doesn't see it and then you're stuck. Oh, the agent actually scored you very unfairly. Your score should have been 200 and you got 150 and you don't agree with it. Well, we have a feature that allows the person to say, I think the agent was wrong. And then you send a human expert in the loop that's review within four business days and respond to the person. We've upgraded your score and we've corrected the agent. And when you do that across thousands and thousands of people, well, of course, the agent gets better over time. And yeah, the first deployment is a mess. The second one is a little bit less of a mess.

25:59Kian Katanforoosh:And, you know, at some point, you just build that muscle of looking between the lines and in the details because that's what matters. In a lot of cases, we even removed AI. We realized that we started, we were like, everything has to be stochastic, meaning sort of non-deterministic. And then we got some feedback and users said, no, actually, I really like when part of the experience is deterministic, where I don't need to be real-time talking to the AI interviewer because it stresses me out. I want to take my pause and I want to be able to look at the multiple choice question and take my time to check A.

26:34Kian Katanforoosh:That's not, you know, doesn't need like agentic AI. And so we had to decide where do we do deterministic and where do we do stochastic? Because stochastic allows you to understand the reasoning of the person. You have a live conversation with an agent, you can dig deeper in their thoughts, but it's not always the right solution.

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27:29Marina Mogilko:It's not a battle. So glad the Saja boys could take breakfast and give our meal the rest of the day. It is an honor to share. No, it's our honor. It is our larger honor. No, really. Stop. You can really feel the respect in this battle. Pick a meal to pick a side.

27:48Kian Katanforoosh:And participate in McDonald's while supplies last.

27:50Marina Mogilko:Wow. So from what you're describing, it feels like in order to deploy an AI agent in your company, you need a very technical person who can do the right reasoning and ask and like pave the right path for that agent.

28:01Kian Katanforoosh:I think it's like, so companies now have these agent marketplaces. Like you can go on their internal platform and create an agent with a prompt. That is very different than building an agency company where the bar is just super high. So for example, if you want to create a bot on Slack that reads a channel and summarizes it for you every day, you don't need a team that is technical. You now can have someone go on the marketplace of agents, hook it, connect it to Slack and tell it what to do. It will do it. But we're building an AI agent that is supposed to be the best in the world at measuring someone's skills to give them feedback.

28:39Kian Katanforoosh:That's a different problem. You can't get it wrong. The bar is extremely high. And there you need a research team. You need an applied team. You need a product team.

28:46Marina Mogilko:And talking about jobs, I feel like we need more and more people these days because of all of the tools, all of the opportunities that open up. But do you think there will be more companies? because it's easier to start a company now.

28:56Kian Katanforoosh:Yeah, I think there will be more companies.

28:57Marina Mogilko:Is it going to help even out the market?

29:00Kian Katanforoosh:Yes, I think so. I think there will be more entrepreneurship. There will be more small businesses. You know, last year I saw on X some of these Vibe coding tools. I'm not going to say which one. People would know. Did a marketing campaign saying, oh, one of our users rebuilt Calendly and rebuilt DocuSign in six hours. In six hours. Where is that product? Who has used it? Nobody has ever used that product. Nobody has ever seen it. It's probably not even maintained anymore because what makes Calendly and DocuSign, by the way, opened a new office in San Francisco and they're growing, you know. So what's interesting is if you don't have the best product, if you're not significantly better than DocuSign, why would I change to your product?

29:45Kian Katanforoosh:The bar is high. Yes, it's easy to build a simple signature tool or calendar scheduling, but Calendly is very actually powerful. It has so many features. And so the only way to replace that is if actually you build a product, the product is not only as good, but actually maybe 50 % better for the cost of switching to be worth it for a user. 50 % better. And on top of that, you will have to make sure it keeps being 50 % better.

30:09Marina Mogilko:Yeah, and you do the right marketing as well.

30:10Kian Katanforoosh:So I don't buy this idea of personal software. I don't buy that people are going to build their Calendly and they're going to build blah, blah, blah. I think some company will build a Calendly that is 50 % better than Calendly that is AI native. and everybody will use that agent. And because you don't want to, you don't have the time, we don't have the time to build our personal software and maintain it, you know? So I don't know. I think it's just marketing campaigns.

30:35Marina Mogilko:Yes, totally makes sense. In the next five years, we just don't know what's going to happen in 10 years when AI is so good and it just gets all the knowledge. Like, I don't know, I'm thinking about the lawyers who are using AI. Like AI, an AI tool has all the legal knowledge. It's just so much better than anything.

30:51Kian Katanforoosh:For sure. I agree it will be an AI agenting tool. I just don't think there will be hundreds of them. I think people will use the best.

30:57Marina Mogilko:Yeah, yeah, yeah.

30:58Kian Katanforoosh:So I don't buy that there will be...

30:59Marina Mogilko:But it will be one major company, don't you think? It will be, it will be. It will probably be one of the top three or four.

31:06Kian Katanforoosh:I don't know. But you look like, Calendly has built an amazing business. There is a feature that is the exact replica of Calendly in Google. Exactly. So how did they build that business? Because there's still a need for like innovation in that niche, you know. I don't think we will be using thousands of agents in the future, like you and I. I think we will be using a smaller number that are specialized and the teams behind it make them consistently better, continuously better. Not only it will have the ability to teach itself, but there will be a user feedback loop so that they get the UI right, they get the UX right, they get the lingo right.

31:42Kian Katanforoosh:These things are very important at the end of the day.

31:45Marina Mogilko:Yeah, it sounds very positive for entrepreneurship because sometimes as an entrepreneur, when I think about AI, if AI can identify the problem, like when it comes to Amazon Marketplace, for example, identify the product where demand is more than supply, just ship it from China automatically and just sell it. It makes me a little sad. But from what you said, because it takes a human to constantly improve something and think about the details and innovate.

32:10Kian Katanforoosh:And the defensibility is not the software. It's not going to be the code because that's easy. It's the expertise that it put into it.

32:17Marina Mogilko:And the founder energy.

32:19Kian Katanforoosh:The user feedback, the agency of the founding team, things like that matter more. And that's what makes them win.

32:25Marina Mogilko:I love it. Okay, for everyone who is listening, our audience is 25 to 40 years old. They all want to become better in the age of AI, build something. What are the three moves that they should make in 2026?

32:38Kian Katanforoosh:Learn the foundations of AI. Assess yourself to make sure you're ready. Build the habits of learning. like every every day when you wake up take five minutes read the x posts of the people that you trust in the space and it turns out you know you you won't feel better after a week but you will feel a lot better after a year you'll feel like you're at the you're probably at the cutting edge you know some some someone said i saw like you know if you focus on one thing for a day you probably are already in the top you know x percent of the world in that thing if you focus on it for a week non-stop you're in the top 10 percent focus on a month you're in the top one percent but to be in the top 0.1 percent you will have to build that habit and follow it for five ten years and you might be the top 0.1 percent at what you're trying to do i love that i also like

33:29Marina Mogilko:your point about joining a hub because this helps you evaluate yourself yeah uh against other people like compare notes and learn from each other maybe start locally and then you know change groups

33:41Kian Katanforoosh:Yeah, I think especially if you're early in your career, today hubs have significant advantages because, so, you know, AI started in the Silicon Valley, pretty much the, I guess, the new wave of AI agents. So companies came. So there was more opportunities. So more people came. Because more people came, more companies came. And now if you're in San Francisco, you don't even need to put an effort to learn what's happening in AI. I go out at the dinner. We talk about voice AI. somehow. People talk about Tesla autonomous autopilots. You just learn constantly because you're in the hub. I think in the next few years, it will be like that.

34:19Kian Katanforoosh:The hubs are way advanced compared to the rest. But I think that in the next five, 10 years horizon, people will get slightly older. They would want to build families. They will leave the hubs, a lot of them. They will take that knowledge with them. They will probably start building somewhere else.

34:33Marina Mogilko:Local hubs.

34:33Kian Katanforoosh:Exactly. And that's what happened in the dot-com when software engineering was concentrated. And a few years later, actually it became democratized because of online learning, because of access to information, but also because a lot of these experts moved elsewhere. And I think the same thing will happen in 10 years. Even outside the hubs, you will find great AI native micro hubs or local communities.

34:55Marina Mogilko:Yeah, that's amazing. Thank you so much for this conversation. I love podcasts. After the podcast, I'm going to just text my team. We're going to build the cloud thing. We're going to make sure we have all the documents, everything synced. Thank you so much. Love this feeling. Let's get to work. Thank you. Kian is the reason why I came back home from Davos and started implementing CLOT across everything that I do. We set up multiple CLOT projects for all the social media that we're running. And honestly, it's been so transformational. Another conversation that's been really transformational was my conversation that I recorded at Davos with Ryan Roslansky.

35:31Marina Mogilko:So if you're all about AI, if you're interested, what's happening to jobs and how you can get a battery job by posting on LinkedIn. Watch that episode. It's live on my channel and I'll see you very soon. Bye.