Future of Work 2026: The Only Jobs That Will Survive the AI Era — Silicon Valley Girl Podcast

Marina Mogilko: Just this year, more than 100,000 tech workers worldwide have been laid off across companies like Amazon, Intel, Microsoft, Meta, IBM, and Salesforce. Amazon alone cut 14,000 corporate roles. Clariner reduced its staff by nearly 40% as it leaned into guess what? AI. Dualingo is phasing out human contractors in favor of automation. And this isn't limited to tech. In the UK, one in six employers now expect AI to reduce their workforce in the next year with junior roles hit first.

AI political turbulence, economic pressure. Together, they've created what some people are already calling apocalypse. And here's the paradox. Companies publicly say, "If we don't adopt AI, we won't exist in 15 years." And at the same time, they're hiring fewer juniors than ever. It really feels to me like this first step of the career ladder is cracking. And if that first step is gone, what does that mean for the future work and for the careers of recent graduates?

On my podcast, Silicon Valley Girl, I talk to CEOs, investors and founders who are actually hiring people and who are building the AI tools everyone is so anxious about. And you know, I'm a mom. I have a six-year-old and a four-year-old. I used to worry about my career. Now I'm worried about my daughter's future because it's so unpredictable. And that's one of the reasons why I do the podcast because I want to hear from those people. I want to ask my questions as a moment as an immigrant. And in this video, I want to bring their insights together and show you which jobs are actually at risk, which careers will grow because of AI, and what you can do right now to make your career as AI proof as possible.

Let's start with what's really happening to jobs today. When I talk to founders and CEOs, they all say the same thing. In five years, we will most likely have AGI and there will be massive unemployment. For decades, the life formula was simple. Go to school, get a degree, get a job. Now, the formula is breaking. Education prices keep going up. But graduate job openings in some countries are down by 40%. So, if the job market feels like a closed door, it's not because you're doing something wrong. The system is preparing people for a world that does not exist anymore.

And here's how Daniel Priestley, a British entrepreneur and founder, describes this gap.

a special guest: It's both. It's the easiest and the worst time. So is there's more money than ever before. There's more opportunities than ever before. You can reach global markets faster than ever before. So in theory, it should be the easiest time. The reason it's not the easiest time is because our schooling system is rooted in the industrial age and it's built around getting people ready for factories and offices that no longer exist really. So the reason that so many people are struggling is because they went through this arduous training day after day after day for 12, 15 years preparing them for an industrialized economy. And when they get out there all of these skills make them very functional. But now we have automation and outsourcing.

Marina Mogilko: Yeah. And it's like great, we trained you as a large language model that's not as good as the current version.

a special guest: Yeah. Teaching people to do functional work that can be automated or outsourced way faster, way cheaper, way easier. Especially in the west, you are not only in competition with the technology, you're also in competition with someone who's armed with the same technology in a country where you can live pretty large on half the price.

Marina Mogilko: Yeah. So the question isn't do I have a degree anymore? The real questions are, can I solve ambitious problems end to end employing those AI tools? Can AI actually 10x my output? Can I do something beyond what a model and a cheaper freelancer could do together?

And that leads us to the next part. Which jobs are actually in danger and why? When people ask which jobs will AI replace, they expect to hear coders, designers, maybe copywriters. But the reality is more nuanced and in some ways more scary. So I asked Perplexity to analyze my portfolio and I asked it whether I should fire my financial advisor and it was like yes you should do this immediately. Like that's the first time I saw something that definitive from AI.

a special guest: What's going to happen to these professions? Financial advisors, real estate brokers? Because Perplexity does it now and it created the whole strategy for me to rebalance and everything. Getting the listings on like Redfin or Zillow with like a comma or browser, or say you just have a recurring task that's running. Doesn't work yet but it's going to work pretty soon. Which is, you could just have a task that says, you know, every morning just look at all the new listings on Redfin. Have something like every time there's a house below a certain budget and that's within this neighborhood, make sure to like send me a push notification and submit an application on my behalf and schedule a meeting for a visit. You have access to my calendar, everything you can.

Marina Mogilko: So, if your agent only shows you listings on Redfin and Zillow, I think they're useless. But if your agent is doing off-market deals for you, they're still pretty useful because those things do not exist on the web.

a special guest: Okay. I feel like having the power of like intelligence and computer at your hands, it always comes back to that means you can push the existing industry to like work harder for you. Same thing with private wealth management or financial advisors. Like what are, if the job of the financial advisor is to tell you like what stocks to buy, then I don't think they're going to be smarter than Perplexity, which you can go and summon and ask it to go read all the analyst reports in every stock and like all the morning day news and like come back to you and tell you like the impact on your portfolio. What would Warren Buffett do if he had exactly your portfolio? Like it can answer questions like that that no financial advisor can.

But if your financial advisor does more stuff for you, like getting you some access to certain funds, like private equity or hedge funds, or access to like funds or Citadel or like some startups, venture capital, which you cannot get through just the public markets, then maybe they're useful, right?

Marina Mogilko: A clear pattern shows up. AI is not killing entire professions. It's killing the shallow version of those professions. A lawyer who just rewrites templates, that's easy to automate. A financial adviser who just picks a few mutual funds from a list, also easy to replace. You can already do that with Perplexity. A real estate agent who only sends you Zillow links, you don't need a human for that.

But a lawyer who negotiates, strategizes, and builds deep trust with clients, very valuable. An adviser who gets you into deals you can't Google. Oh my god. Yes, please. An agent who finds off-market properties and navigates messy human situations. Oh my god. Yes, I've been through that. I relied on my person.

I just talked to someone who runs a nonprofit helping students from low-income families apply to colleges. And she actually sees how AI is helping them because prior to AI, one tutor could only help a few students. Now one tutor is helping hundreds of students and because AI can answer a lot of generic questions. And she highlighted that they still need humans there to motivate people. And this is why students from those low-income families come to her nonprofit because they need that support. They need a human to tell them you can do it. You're worth it. You can apply to that college. And it was super important to me when I was applying to colleges when somebody from Education USA told me you can do it. And yes, I could Google a lot of things myself, but I can't Google motivation.

What I'm saying here is that AI isn't replacing law or finance or real estate as fields. It is replacing job descriptions that are too basic. And that's exactly why so many people decide to build their own thing instead of fighting for one of those shrinking roles.

So, let's look at the job loss problem at a different angle. Let's say you already have a pretty good job and you like it and it's interesting. You're inside the company. You see all these changes and you're thinking, "Okay, how do I not get replaced by the next wave of tools?" I asked my guests what they're doing with their own teams right now.

a special guest: There's still higher value work to do. So they're still in the companies. They're still in the companies and there's still work to be done. Like everything's elevating, but what we discovered is that there's this ability to pull the scalable element out and address a market that was never even being addressed. So it's not like you're replacing people, it's more of you're elevating them.

There's definitely an element of replacing people. And that is because there are always these jobs that are repetitive, functional, annoying, frustrating jobs that we can actually replace. There are some people who say, "I don't want to elevate up." And unfortunately, there's not much I can do if you don't want to elevate. If you don't want to play at the higher game, I'm moving fast. So you've got to either elevate towards that or find something else.

Marina Mogilko: Yeah, this is basically the new contract at work. AI takes the boring repeatable tasks. Human move up to higher value problems. If you refuse to move up, you eventually move out. And big tech CEOs are thinking the exact same way.

We see big companies put a stop on hiring and they say like, "Hey, to their employees, you need to figure out how to do this with AI first before we hire someone." What do you think about that?

a special guest: I think it's a reflection of you know a fast changing market and a lot of uncertainty, both you know in the political environment and in the tech environment of where things are going. And the natural tendency to do is to go slower a little bit. And you may might decide, you know, some people are no longer the right folks in my company for that kind of environment where things are moving incredibly fast, where you're almost forced to use AI to keep up with the competition.

Like the realization I think that many companies had in the last few months is that if we have employees that say we don't want to use AI, that ultimately means we as a company are no longer set up for success because our competitors are all using AI or they're mandating AI. And I think this is the transition phase we're going through. You know, things like Mark Zuckerberg getting the scale scale AI team. I think that shows where Mark's head is and where he believes the future is going to be. He's going, he's willing to invest into it.

Marina Mogilko: Yeah. Yeah. So, if you already have a job, your number one goal is very simple. Become the person who knows how to do your job with AI, not in spite of it. And if you're a manager and you're watching this, another meaningful thing I took away from a conversation with this lady who runs this nonprofit helping students apply to colleges. And when she was introducing this AI tool, she was talking to her team. She told them to focus on the problem that they're solving with this tool because that tool allowed her team to spend their limited amount of time on actually encouraging students to apply and motivating them versus answering generic questions.

So in order to become a person who knows how to do their job with AI, you can start with really easy practical exercise. Ask yourself what are the three most repetitive things I do every week? Is it writing emails, making reports, doing research, cleaning data? Then build a tiny AI system around each one. This can be prompts, small automations, agents, very basic, anything that saves time.

I really like Spaces and Perplexity. I feel like I have a space for my high cholesterol. I have a space for guests that I'm researching. And then you just notice how you save 30 to 50% of your time on that repetitive stuff. I don't type my emails anymore. I just talk to ChatGPT and it writes my emails. So keep asking myself, what higher level work can I move to? Where is this highest ROI? Where should I invest more time in? And where should I delegate to AI? That's how you move from replaceable task doer to irreplaceable operator.

That brings us to one of my favorite questions. My daughters are four and six and I always ask entrepreneurs, what skills should our kids learn for this new world? And honestly, the answer is very similar for them and for us.

a special guest: Generally speaking, AI don't suggest waiting because part of what you want to be doing, you know, just like any new technological revolution, whether when YouTube was happening, when the internet's happening, the folks who go and adopt and play with it early then have a differential edge in the change that it means in the industry, in their society. And so even though three years from now the coding tools will be and agents will be much better than they are now, the people who started playing with them now will probably be the people who know how to use them and deploy them much more comfortably early.

Marina Mogilko: So what do you think parents should be teaching their kids now?

a special guest: I think it's still important to be good at like learning knowledge from first principles yourself and not depending on the sort of AI tutor leading you through. Like I think one of the most important things is from school is the discipline of being able to teach yourself. That's a meta skill and that you know that that comes with friction. So I think as a parent you still have to introduce like discipline and friction into the process because if it comes all too slowly and it's always on tap you know then there's a risk that the child could just get used to having everything instantly available and doesn't learn from the hard work, you know, the benefits of hard work, which I think are important. So that's like something to think through now that everything is going to be so seamless.

Marina Mogilko: Then I asked the founder of Replit, Amjad, what he's teaching his own kids because he's an immigrant and his kids are the same age as mine.

a special guest: When I'm thinking about my kids and what we're going to do in the future, I think about this idea of being more of a polymath, right? Like if you think about, you know, even before the industrial revolution, the people that are most memorable, like Leonardo da Vinci, for example, did a lot of things. Was an engineer, was an artist, was all sorts of things, right? And the kind of elite education used to be about understanding a lot of things about spending a lot of time learning about everything. And I think this is where the education needs to be headed where the industrial revolution created a world where humans are treated like machines. If you think about corporations or factories, factories are one big machine and every individual person kind of doing the assembly of one thing is a part. And I think it was very dehumanizing and I think we're going to go back to a moment of time where there's a lot more opportunities for entrepreneurship. Even when you join a company, you're going to be judged by how much of a real business impact you're going to have as opposed to how task oriented you are.

Marina Mogilko: The new AI age wants you to be what researchers call a human epoch. Someone who brings the five abilities AI still can't replicate: empathy, presence, opinion or ethics, creativity, and hope slash leadership. And these aren't soft skills anymore.

Let me give you a simple example. Two people can both use ChatGPT to write a report, but only one of them can walk into a meeting and read the room, understand why a client is nervous, understand what could be a hesitation, reframe the problem when the model's answer isn't enough, make a judgment call when the data conflicts, inspire the team to move forward. That combination, human psychology plus AI fluency, is what companies are paying a premium for.

And then there is something most people still underestimate: personal brand.

a special guest: Personal brand is going to matter even more, a lot more, because personal brands get 20 times the cut through as business brands when you're trying to get attention. But it's going to be nearly impossible to build a personal brand. Imagine a scenario where there's an airport and there are planes that are on the ground and there are planes that are already up in the air and the fog comes rolling in and the air traffic control says if you're already on the ground it's too foggy you can't take off but if you're up in the air you can keep flying. That's what's going to happen to personal brands. So new personal brands are going to be harder and harder to get through the fog. Existing personal brands will be already up in the air. I think there's probably two to three years where you've still got time to build a personal brand. I think one of the greatest assets anyone can build right now is a dedicated following of two to 20,000 people who know who you are. They get you. Doesn't have to be millions, but if there's two to 20,000 people out there on your LinkedIn, on your Instagram, on your YouTube channel, whatever it is, they feel like they've met you or know you. They've got a parasocial relationship to you. If you've got two to 20,000 people out there who have that parasocial relationship with you, that is going to be one heck of an asset to have.

Marina Mogilko: In a world where AI can generate infinite content, people follow people. Your edge is a mix of AI fluency. You know how to use tools better than 90% of your peers. Polymath skills. You can connect dots across fields and ship real things. Personal brand. None of that requires permission from a recruiter, but it does require something old-fashioned: learning. And no, we're not all about retiring at 30, but how we work is changing fast.

Instagram co-founder Mike Krieger described it perfectly when he talked about Claude and AI agents.

a special guest: What do you think is going to happen in two or three years? How we're going to progress and advance? I think part of it, and I was having this conversation this morning even with some of our researchers, the progression or the dynamic that I see is, if last year, maybe the beginning of this year, these models, and I'll use Claude as the example, were really kind of assistants that were helping you with maybe a question at a time or maybe a task, right? This year they're moving more into collaborators where, especially if you watch somebody use Claude Code for example, they're actually delegating what would have taken them maybe 20, 30 minutes and Claude's going off and doing it and then you're checking in and you're more on the sort of validating or verifying work, right?

Going into next year, you're going to delegate even bigger chunks of time or even like pieces of the job out to that. So it's not just I have this very specific thing, please go do it. And it could be more sort of think of it, Claude, as something that's in the loop of your business. So, hey Claude, watch for any new user feedback and maybe propose a change based on that. And you can imagine evolving that. Don't just propose a change, write the code to make the change and I'll check if it's a good idea or not. And then the next step there is Claude actually being an entire sort of coworker where it has a discipline. So not just a project that happens to be a good thought partner for product management, but an actual product manager in your company.

Marina Mogilko: This for me is the blueprint of AI proof careers. You work with models that see patterns better than any human ever could, and you bring the things that absolutely can't be replicated: judgment, taste, ethics, lived experience, emotional support. In other words, you become the translator between messy human reality and superhuman AI systems.

With all these tools, it's natural to ask, do we even need formal education? I asked Perplexity CEO Aravind if he'd still do a PhD today and what he'd tell an 18-year-old starting from scratch.

a special guest: The fundamental thing you learn in a PhD is learning to learn. Like I did a lot of research in my PhD which doesn't matter today, but I got the ability to like go learn a new topic, dig deep, understand everything, gather my information, consult like whoever is the best expert, which by the way is not needed anymore because you have tools like Perplexity for subject expertise to go make decisions and like you know branch out. That is what you acquire. That skill, zoom out and think beyond materialistic goals like just foundationally as a person. You become a lot more grounded in like the willingness to seek truth, the relentless questioning, the Socratic method of learning and learning to learn. And I feel like these three qualities are like reflective of this proverb or phrase, right? Like give a man a fish, you feed him for a day. Teach a man to fish, you feed him for a lifetime. Like that's how I feel about PhD.

Marina Mogilko: So, no, you do not need a PhD to succeed in AI. But you do need the thing a good education was always supposed to give you: the ability to learn fast, the ability to ask better questions, to go deep when everyone else is just skimming. AI makes it easier than ever to access knowledge. It does not replace your responsibility to actually use it.

So, let's put this all together. Yes, entry-level jobs are disappearing. Yes, simple repeatable work is becoming less valuable even if it's intellectual. The people actually building this future keep saying the same thing: this is both the hardest and the best time to build your career.

If you want to be on the winning side of this shift, here's a simple plan you can start this month. Something real, something doable.

Step number one: learn to work with AI, not around it. Write down the tasks you repeat every week. Reports, research, emails, content, and keep iterating. Don't stop there. Build AI workflows for them using ChatGPT, Perplexity, Claude. Keep trying those new tools. Your goal is to cut the time in half for just three to five tasks in the next 30 days and put it into your CV or LinkedIn. Reduced X task by 50% using AI workflows. That's a language hiring managers understand.

Step number two: go deep in one area. Then expand. Pick a field and commit to one full year of uncomfortable depth. Courses, side projects, real work you can show. After that, add an adjacent skill. A marketer who codes, a doctor who understands AI, a designer who knows data. That's how you go from task doer to someone who actually moves the business.

And then step number three: build a small but real personal brand. We've hired some people recently and most of them came because my COO followed them on LinkedIn. She liked their way of thinking. She liked their experience. She reached out on LinkedIn. We were not chasing people with million followers, just a couple thousand people who know what you're good at. Post once or twice a week about what you're learning, building, and improving. Share experiments, share case studies, and numbers. Document the journey instead of waiting to feel ready.

So, to wrap this up, the future work isn't humans versus AI, it's humans plus AI. And the gap between those who adapt and those who don't is getting wider every month.