Is Your Job Safe? The New Diamond-Shaped Career Path

Vit Lyoshin (00:01.084)
Welcome Tanya, thank you for joining me today.

Taniya Mishra (00:05.196)
Thank you for having me with you, Vit. I'm looking forward to our conversation.

Vit Lyoshin (00:10.396)
Sure. I wanted to start with something about AI literacy and many people talking about it. What does it actually mean other than just using chat.gpt that everybody's pretty much played with already?

Taniya Mishra (00:27.288)
That's a really, really good question because I think about it all the time. Teachers ask me about it, parents ask me about it, and kids ask me about it, right? so I think we're the stage at where we are that many, many people, especially young people like those in high school and college, frankly have enthusiastically adopted the use of AI tools. But I would wager that usage is not the same as literacy. So

If I had to talk about literacy, then I would say that knowing at least a broad overview of the foundational concepts of AI, like what is it under the hood? If you're using ChatGPT, you're using Claude, you're using Gemini, you are using even discriminative tools, well, what is happening under the hood? Having a broad understanding of that, knowing when to use AI and when 100% humans are better at it.

Than AI is, and other places where AI actually gives you great efficiency, knowing how to verify the output of AI, being able to spot when AI is using shallow reasoning, you know, pushing back on AI, right? Pushing back on AI tools, guiding the tools, like overall evaluating AI's progress on a task, especially if you think about agents.

And as well as evaluating its final output with a ethical lens, I think all of these things together would encompass AI literacy.

Vit Lyoshin (01:58.779)
Mm-hmm.

Vit Lyoshin (02:03.378)
Yeah, yeah, that makes sense. It's more than just usage. I totally agree with you. Knowing a little bit how things work, at least to a certain degree that's helpful. And then just to follow up really quick, what sometimes people get wrong, maybe that you're noticing or those questions come up in conversations, and they're getting wrong in terms of learning AI and what they should be learning about it.

Taniya Mishra (02:32.62)
Yeah, so I think I'll iterate the fact that this happens with people and this happens with AI at the same time. If somebody it speaks really confidently, you tend to believe what they are saying. You expect that you know what what might be their opinion, you might mistake it for fact. And AI, especially generative AI, the objective function, if you look under the hood, has been trained to mimic a very confident.

well spoken person. Like if you go back, you know, 15, 20 years, frankly, when I first got into artificial intelligence, that was in 2008, was my first job after my PhD. I used to build build language models. And what did we use for the training data? It was what we would call newsreader speech, right? So newsreaders, people who speak really clearly

confidently in complete sentences. And so over time, we have incorporated more data in how a lot of these language models are trained and they've become larger. They've gone from tiny language models to large language models. But the objective function is still trained to sound like a really confident person. So mistake people make that because it sounds so polished, people we tend to just believe the output

Of AI. And as you and I have seen and read about, there are so many mistakes that artificial intelligence can make, but it's almost because of how polished the output is, people tend to question this. So I would say that's a huge mistake that I think once again, going back to the question of literacy, right? That's a critical skill. How do you verify whether the output of AI is correct or credible?

Vit Lyoshin (04:19.42)
Mm-hmm.

Vit Lyoshin (04:28.37)
Yeah, yeah, I guess it was happening a lot more in the early days, like a couple years ago, three years ago, when all these tools just started showing up and people playing with them. I remember a lot of memes and just straight out lies that AI was telling people.

Now it got much better, but still sometimes I notice something weird and I say, are you sure about this? And then it responds back and says, you're right, I'm sorry, it's actually this and not that. I'm like, come on,

Taniya Mishra (04:51.182)
Absolutely.

Taniya Mishra (04:59.67)
Yes. You know, it's funny, it's become more subtle, but it it still extrapolates sometimes too far. So sometimes, you know, like I use it a lot of times to summarize research papers or like you know, white papers that are like twenty-five pages long. I want to get a quick summary and sometimes it will like produce, you know, a summary, but like there will be parts of it that almost seem too surprising or too

Good to be true, and I will ask it to show me data to back it up, and it will like produce basically data that you're like, A does not lead to B here. so I would say it's become more subtle, but I I think it still hallucinates through over-extrapolation.

Vit Lyoshin (05:39.046)
Mm-hmm. All right.

Vit Lyoshin (05:50.53)
Mm-hmm. Yeah, and I also wanted to touch a little bit about schools and what currently is going on with schools and Are they falling behind with AI? completely at this point

Taniya Mishra (06:04.814)
I mean, I think it depends on are we thinking about K12 or are we thinking about higher ed? I think it's it's very nuanced, right? So especially K-12, we have the most vulnerable amongst us on the receiving end of whatever decisions that adults make. So children, right? Any decisions that are made at a school.

Vit Lyoshin (06:20.23)
Mm-hmm.

Taniya Mishra (06:34.368)
At an institution level, at a leadership level, or even at an educator, individual educator level, has an immediate impact on students. So I think the usual approach within schools is to limit experimentation, to be very careful, to be very sure before you make a change. And that has been the approach that I would say K 12 has taken towards AI adoption.

Vit Lyoshin (06:53.276)
Mm-hmm.

Taniya Mishra (07:05.294)
it's been what since ChatGPD sort of burst onto the scene in November of twenty twenty two, I believe. so it's been about, you know, four years. I think my observation is that institutions have sort of gone through the stages of, you know, people freaking out about like what is this? Because there was a lot of myth around AI taking over all teaching jobs, which frankly has been pushed by, you know, the tech ecosystem.

Vit Lyoshin (07:30.15)
Mm-hmm.

Taniya Mishra (07:34.465)
I have heard people even quote Bloom's two sigma research and say, well, you know, Bloom showed that one on one a student is going to improve by two standard deviations over a corporate learning setting. And but they were using it for a AI tool versus versus a, you know, a teacher that was part of the study in Bloom's research. So I think there was like fear.

Vit Lyoshin (07:48.038)
Mm-hmm.

Taniya Mishra (08:00.079)
At this at the educator level, at the school level. Then there was like maybe it's a trend, we don't, you know, it's going like so many other trends that have come and gone. How how much do we need to pay attention to it? Then I would say schools started seeing the efficiencies it could bring to routine tasks and they started adopting it more at the workflow level. But it has been, I would say, in the last six to eight months.

That I'm seeing K-12 schools really think about how do we make our our students, you know, future ready, career ready, especially when faced with very fast changes in the workforce that are happening, right? Every single day. Like today, we just heard about Wix laying off so many people. We've heard of Meta, Oracle, and the list goes on, right? block. so I think as information.

Vit Lyoshin (08:46.353)
Mm-hmm.

Vit Lyoshin (08:53.488)
Mm-hmm.

Taniya Mishra (08:58.406)
On the immediate impact of AI, especially on the newer members of the workforce, students that are more recently graduating, as that is becoming, frankly, the lived reality for all of us, education is starting to pay attention and starting to think about, okay, this is not something that will go away.

We need to, you know, make sure our students are ready for this. So I think higher ed is definitely closer to the sort of employment question. So they are, you know, I would say more eagerly leaning in because students are by the time students get to them, they are adults and they are asking these questions. And at least in the United States, higher ed is so expensive. So when people are asking about you know return on investment.

Vit Lyoshin (09:48.146)
Yeah.

Taniya Mishra (09:50.891)
schools have to resp like you know, institutions have to respond or they have to face the reality of having to close down in a few years. So there has been a I would say sort of a jump jump up and do something response at the higher ed level, but higher ed, you know, is connected to high school. And so that means that high schools are now starting to think about, okay, in order

Like it's only f high school to getting your first job is just four years away. Right? That happens so quickly. So I definitely think I'm seeing more movement at the K twelve as well. there are regions of the world that are frankly leaning in further and faster. you know, we have worked with school chain in Asia for the last three and a half years bringing AI education to as kids.

Vit Lyoshin (10:22.277)
Yeah.

Taniya Mishra (10:46.996)
As young as in middle school and adding and layering on new courses as the same kids, you know, continue to go through you know higher grades. So I would say there's they seem to be leaning in a little bit faster and more. we're also hearing about that in the Middle East as because AI is such a large part of their economy. I would say Europe and

United States, there is now starting to be more movement around it because you know the employment issue is real for all of us, and it is not hard to see the line between high school and your first job. But taken together, I would say no one not nobody stands out in my mind as particularly ahead.

Vit Lyoshin (11:36.978)
Yeah.

Vit Lyoshin (11:46.215)
Mm-hmm.

Taniya Mishra (11:46.529)
you know, but roughly everyone is at the same starting block, you know, plus or minus, you know, a few months. but I what is encouraging is that I'm definitely in the last six to eight months, I am seeing a lot of forward movement in education across the board from K twelve to higher ed.

Vit Lyoshin (12:06.002)
Yeah.

Vit Lyoshin (12:09.562)
No, that's great to see because I think, yeah, people in school and high school specifically already preparing for the career and what subject they want to study more and become professional in that area. And I think even like learning AI tools, not necessarily how to use them or how to build them rather, but just how to use them in your profession is going to be really helpful.

Or maybe just general knowledge what it is like we used to use like biology and physics Not that it helps in everyday life to know what kind of plant it is But as a you know general education, it's great because then you have broader Like knowledge of things happen how world works I think that's that's good and and then I also had a follow-up for this for the like a career and future workforce development rather

what kind of AI native professional of the future I would try to look forward for and upskilling and things like that.

Taniya Mishra (13:17.227)
Yeah, so I think this is this is from a very recent report produced by Microsoft called the Microsoft Work Trends report from 2025, where they are already you know, predicting that in the near future a lot of teams are going to be AI and agent hybrids, which means humans are going to have to work with

Not just their human collaborators, but also AI agents. That's very interesting because it both requires two sets of skills. It requires, as we were talking about, like you know, tactical skills and knowledge around how to use AI, because employers, I think, in a World Economic Forum report, or probably in the same Microsoft report.

Vit Lyoshin (13:52.039)
Mm-hmm.

Taniya Mishra (14:11.763)
I read that over sixty percent of employers are expecting that there is going to be a thirty percent or more adoption of AI within their workforce in the next twelve to eighteen months. And along with it, a large percentage of decision makers are saying that if people don't have AI skills, they may not even get hired to a role where AI AI doesn't have to be central.

But it has to be a tool that you have to learn how to use. So I think, you know, young people, that means they have to develop tactical skills around how to use AI, but they also have to kind of build skills around analytical thinking. Like that's that's a skill that seven out of ten employers say is the most important skill. They have to build strong judgment going back to these questions. Like if you have an agent that you have to deploy some tasks to.

Well, you're gonna have to know what is the agent going to be better at and what am I going to be better at, right? So deploying it. If your job is to guardrail the, you know, the decision-making path that the agent is taking, then you are going to need sort of you know, repeated exercises in having to decide and having to make big decisions, predict potential outcomes, potential successes, potential failures.

And you're going to need to be able to exercise skills like that. So I would say tactical skills in technology, along with durable skills that our teachers and our schools and our parents have always wanted us to have, is going to be critical. So I think that's what I think we are going to see a lot of sharpening of some of these skills that.

People in the past called soft skills. I don't know why they have called it that, because they are it's so hard. Good decision making feels a lot harder to me than you know creating a Excel spreadsheet. Like, you know, that so I think the decisions you make in the spreadsheet are are challenging, but the process of creating a spreadsheet, you know.

Taniya Mishra (16:31.407)
tactically building macros, that that's a you know skill that you can learn at school and you just repeat it and test it and refine it, right? But decision making is hard because you are always having, it's not always the same problem constraints that you have to solve for. So I think that those skills are going to be important. Along with it, I I but I also see opportunity. Anytime there's a challenge, there's opportunity, right? If there are

Vit Lyoshin (16:39.312)
Right? Yeah.

Vit Lyoshin (16:49.755)
Yeah.

Taniya Mishra (17:01.069)
So Vit, we have we are all used to seeing the schematic of a work pyramid where you know the base is really wide and lots of new people come join that pyramid. You learn about, you know, you take sort of skills, classroom skills, and you translate them into workplace skills by repeatedly doing, you know, some

Vit Lyoshin (17:06.748)
Mm-hmm.

Taniya Mishra (17:28.661)
some actions or some processes that often a lot of the our junior workforce tend to do. But in the process you're also building what I would call like tacit knowledge or contextual knowledge about your company. But if the number of people at the bottom of the workforce changes, it goes from being a pyramid to kind of like a diamond. So now, so you might hear that and you be you're like, where's the opportunity?

Now there are fewer, it's become more competitive. There are fewer humans at the bottom of the pyramid because so much work has been done by AI. Well, the human capital sort of moves further up into the workforce. That means you actually have two pathways. You can join at the bottom of the workforce of that diamond, or you could be joining somewhere towards the middle of it, which will require a new set of skills. But actually, there are two pathways that are now opened up, not just.

Vit Lyoshin (18:06.672)
Mm-hmm.

Taniya Mishra (18:23.929)
The one that used to traditionally be available.

Vit Lyoshin (18:28.272)
Yeah, that's a very interesting idea. This is the first time I'm hearing about this. And I had a couple of people in the last couple of months on the podcast and we were talking about kind of two very important skills also, kind of like what you mentioned about decision making and things like that. And I think those matches...

with other two skills we were discussing. First one was entrepreneurship and another one was management. So those two, I think match exactly because that's what they do all day long, right? They take some data in, they process it in their mind and they make decisions what to do next. Both managers and entrepreneurs do that. And I think it matches if we prepare our graduate, I mean the students in schools and K-12 or whatever.

Taniya Mishra (18:52.655)
Yes. Yes.

Vit Lyoshin (19:14.668)
with those two skills that will be setting them up for success and joining that middle layer that you just explained. Now I have like a full picture in my head about this. I think this is becoming more clear now for people who are younger especially and trying to get into the into the job market. Yeah, interesting. Okay.

Taniya Mishra (19:36.675)
mean I think that these are you know, we're going through such a big transformation. in you know, bigger than I mean, I was reading about this, the like about all the transformations that the world has gone through, like, you know, starting with the wheel and you know, the plow and then the printing press and then eventually at you know, fast forward, I'm I'm sure I'm forgetting many big transformations, but then the tractor.

Vit Lyoshin (19:42.13)
Mm-hmm.

Taniya Mishra (20:05.869)
Right, and the impact it had. And each of these, and and you know, then of course everybody having basically everyone everyone in the Western world at least having access to a computer and internet and totally not taking away from the issues that still remain around connectivity in many parts of the United States and other other countries as well. But

These were big transformations, but and at each of the transformations, there was a lot of worry around job loss, and there were job losses, but they were actually replaced with new kinds of jobs and more jobs. And if you look at reports from economists, the numbers so far between 2022 and 2026 actually don't bear out our fears. So I was recently looking at

Vit Lyoshin (20:46.832)
Yes.

Taniya Mishra (21:04.255)
This study, I think I think it may have been a Federal Reserve study, and I was seeing that it was really interesting. So the total number of jobs has in areas that are exposed to disruption by AI versus the ones that are less exposed to disruption by AI, there has not actually been the much-feared shrinking in the total number of jobs.

But at the same time, we were just talking about young people not finding jobs. So what has happened is there has been a slowdown in the job market for that 20 to 22 to 25 or 28 year olds, right? So we are seeing some shrinkage of positions for at that entry level, but that has not actually had the same effect on roles that

where you need more of those cognitive skills versus the technical skills. So there has been like in fact there has been more growth there, which is why taken together, the total number of jobs has not changed very much. So I think there is a very nutrition, there is a disruption happening for sure. There's no denying that, but I think there is opportunity.

Vit Lyoshin (22:11.227)
Yeah.

Vit Lyoshin (22:22.226)
Mm-hmm.

Taniya Mishra (22:30.734)
in there as well.

Vit Lyoshin (22:31.28)
Yeah, so to just wrap up this section here, what would be your advice to somebody who's like, let's say 25 year old, maybe already have a degree or studying still, like what would be your advice to them to do right now really quick to kind of adopt to the situation that we have in the job market?

Taniya Mishra (22:52.749)
Yes, so I would say two main things. the first is to keep learning. Like d don't l we cannot stop learning. Learning to learn is going to be the most important skill of this decade and the next decade, right? So keep learning. F like enroll for a course, whether it is a online, asynchronous course that you do yourself, whether it is a course at your local college, whether it is a course offered through work.

Like keep finding ways to expand your skill set. And then that would be my first advice. And the second advice, which is not in prioritized order, it's like yes and do both. The second is build relationships. Get to know people. Attend, especially if you are young, maybe you have fewer family responsibilities. you know, attend events that are happening in your city, things that are happening at work, if there is like, you know, someone

Who is giving a talk at a local university, at a local library, become part of communities, become part of communities that are that you are already interested in, but also become part of communities that are totally new to you. Because what's going to, I expect will happen that we will see a lot more cross-pollination of ideas and a lot of interesting opportunities and pivots.

But that can't happen if you don't even know that, you know, let's say you are a technologist and but now you are part of a you know, business meetup. Maybe actually within that business meetup, you hear about opportunity that requires deep technical skills, but you're not gonna hear about it, or you may not even imagine it if you're not part of it, right? So I think building relationships.

Vit Lyoshin (24:41.008)
Right.

Mm-hmm. Yeah.

Taniya Mishra (24:49.357)
which in the business world is sometimes called networking, but none of us love that word. Get to know people, be invested in others, share with them what you know. Learn from them what they are sharing.

Vit Lyoshin (24:53.842)
you

Vit Lyoshin (25:00.306)
Yeah, no, that's great. Yeah, that makes total sense. And especially right now, connections and relationships matter a lot. So yeah, totally agree with that. So let's talk about your company, SureStart. And if you can tell us a little bit the background of it and also why did you start it?

Taniya Mishra (25:25.689)
Yes, for sure. So Sure Start is a New York City-based AI education company, and our mission really is AI fluency for youth globally. So I'm really glad to talk to you about it. I love that you started with AI literacy, AI fluency. And we we provide AI educational curriculum, teacher enablement resources, as well as support for K-12 schools in building.

their AI policies so that they can, so that AI adoption can go from fragmented use by students or a teacher occasionally to becoming something that is institutionally adopted and can be grounded in strong pedagogy. So that's really what we do at Shore Start. And our focus is currently just making sure as quickly as possible to bring AI fluency to as many young people as possible.

Vit Lyoshin (26:10.961)
Mm-hmm.

Taniya Mishra (26:23.309)
Because in about, you know, I said four years, right? So four, four years, ten years, these are the people who are going to be making all the all the big decisions that's going to impact the lives of people.

Vit Lyoshin (26:36.594)
Yeah, yeah, exactly. So just to outline this a little bit, what exactly was the problem in education that you're trying to solve with Sure Start? If we can maybe explain that a little bit more.

Taniya Mishra (26:51.459)
Yeah, so I think the the the issue that I noticed, I have to give you a little bit of background on this. I have after my PhD, I always thought I would be a professor, as most people who are getting their PhDs at least once in their lives think. but as luck would have it, I my first role was as an industrial AI researcher. I worked for ATT research, which used to be Bell Labs.

So it was a great industrial research lab. I was very lucky to have my first job be there. because I got to do research all day long, to think about big ideas actually in the area of machine learning. I told you my first project was on building language models, which back then was not considered as sexy. Nobody knew about it, nobody thought about it. So

Vit Lyoshin (27:29.19)
Mm-hmm.

Vit Lyoshin (27:39.973)
Yeah.

Vit Lyoshin (27:45.532)
Couldn't foresee 20 years.

Taniya Mishra (27:50.521)
But I got to do that in an industrial setting. And after that, my entire career has been in industry. So after ATT research, I worked for a best-in-class startup that was a spin-off from MIT Media Lab called Affictiva. There too I was the lead researcher and then head of research. But because my role even within industry was in research, I got the opportunity to always intersect with academia.

So I I was very lucky in having, in some ways, a viewpoint on what's happening in industry and what's happening in academia. And one of the things that I noticed, especially around technology, was that it was it often gets developed and used and moves just in general so much faster in industry compared to what's happening in academia, the rate at which young people are hearing about it. So the problem was the only young people.

Who were getting to learn about machine learning or artificial intelligence were students that went to certain really well-resourced schools that were within a tech ecosystem, let's say in Silicon Valley or in Boston, or in other parts of this country or other places that were inside the tech ecosystem. That means the students that went to colleges of that kind or even high schools.

Would get opportunities to be interns or apprentices or even educational programs that were built in collaboration with industry. That means it did two things that were suboptimal. First, a very small group of young people were learning about these technologies that frankly now impact millions and millions of us. So that means you're only getting the mind share of a small number of people. The second part was that.

Vit Lyoshin (29:43.687)
Mm-hmm.

Taniya Mishra (29:50.457)
For industry, it was really competitive to hire people. Like I was at a startup, you know, that was my second role after being at ATT research for six years, and it was very well known in the Boston ecosystem. It had, you know, very strong branding, it had strong relationships with the local universities. And even then, a well funded, you know.

Best in class startup was still competing with the FANG companies for the same group of, you know, s few hundred people. So it was very hard to hire. A single hire could easily take you six months. So how can for industry that means we are leaving money on the table because we cannot move as fast as we want to. So this was definitely, I saw it as a broken pipeline problem. And it was a problem on both sides. It was

Vit Lyoshin (30:24.806)
Mm-hmm.

Vit Lyoshin (30:29.874)
Mmm.

Vit Lyoshin (30:35.941)
Right.

Vit Lyoshin (30:40.187)
Mm-hmm.

Taniya Mishra (30:43.833)
We were not including as many young people as should be included in pathways that are towards the new economy, on one hand. On the other hand, for companies, they just it was super expensive and time consuming to hire. So I saw that broken pathway problem and I wanted to address it. So that was one of the reasons why I started Shure Start after you know, in 2020 after having been in industry for

Vit Lyoshin (30:52.08)
Mm-hmm.

Taniya Mishra (31:12.751)
About 12 years. And I also love the idea of teaching young people about things I know. I think it was the part of me that wanted to be an educator. Because one thing about young people, what I absolutely love, is that they're so bold in their vision. In some ways, I used to like to joke that if I want something actually done, I'm going to have to hire a bunch of interns because they don't know what they don't know. So if you tell them, go

try to do this, they're actually going to go do it. Whereas my seasoned team of researchers and engineers, if I ask them to do something, the first thing they say is, no, we can't this can't be done. So I think it was both of those, it was personal, in how much I enjoyed education, and just seeing young people learn, but also to solve for a real, very real issue that was in the tech ecosystem.

Vit Lyoshin (31:45.33)
You

Vit Lyoshin (31:52.53)
Right, yeah.

Vit Lyoshin (32:10.962)
Yeah, do you have a of success stories or just stories working with students and learning from them and maybe they build some cool projects or anything you can share?

Taniya Mishra (32:20.609)
so many. I could go on and we would be here all night. But I'll tell you I'll tell you the story of these two young women who were in the first summer cohort in 2021 that we collaborated with MIT on. And one was a high school student and one was a young college student. And we taught them about machine learning and artificial intelligence, and we showed them all the many applications.

All the many ways in which AI could be really, really useful in helping us helping humans identify patterns. And one of the projects that they built at that time was to do early stroke detection by looking at the facial asymmetry in our faces when we are experiencing a stroke. The left and the right side of our faces become much more asymmetrical.

Compared to a typical person who's not experiencing stroke. And because, you know, visual AI machine learning models are quite good at recognizing patterns or differences in patterns, they leverage that. And out of it came, you know, first a prototype. This was in 21. They won the award for MIT Future Makers, which was the program that they were in. And then

Vit Lyoshin (33:21.511)
Mm-hmm.

Taniya Mishra (33:45.815)
You know, fast forward about five years later, the students, one of them is you know, she's finished her from high school, she completed undergraduate, and now running this startup called Code Blue is her primary job. They have raised funding from Berkeley Accelerator as well as several other organizations. the other student, she is actually getting her PhD in artificial intelligence. Both of these

Vit Lyoshin (34:01.842)
Mmm.

Taniya Mishra (34:15.641)
Co-founders have built this amazing company called Code Blue. And Code Blue just completed a research study with over 1,000 patients in research hospitals across the West Coast. You know, kind of taking this idea from prototype of early stroke detection into now a you know quite a well-developed product that has the potential to save lives by solving, by detecting stroke.

Up to forty minutes before it happens.

Vit Lyoshin (34:46.578)
No, that's a great story. Yeah, and it's something helpful. It's young people who developed it. They just saw it as an example, as a cool project to work on, and then it turned out to be a business. And it's also very helpful for people. So that's an amazing example of how... Yeah.

Taniya Mishra (35:06.351)
And we have so many other kids who have, you know, done these projects. They've won, you know, national and international awards, including the Congressional Medal for Youth. We have other students who are now working with their state's education department to do AI literacy. Like having learned from sure start, they've taken those ideas back to their home states, and now they're working with the government to get.

Vit Lyoshin (35:13.243)
Ahem.

Taniya Mishra (35:34.795)
AI fluency and AI literacy into the hands of so many more of their peers. So there are just so many stories that if people go to our website and look at the impact stories page, like the list sort of goes on.

Vit Lyoshin (35:39.697)
Mm-hmm.

Vit Lyoshin (35:45.509)
Yeah.

Yeah, yeah. Okay, great. So can we talk about like curriculum and how the whole program works? Is it like part of the normal school education program or something extra? Can you tell us a little bit more about that?

Taniya Mishra (36:01.625)
So Short Start Short Starts courses, we have about six courses currently. They're a progression of AI courses that start with middle school level students, so sixth graders, and go all the way through high school. And we have several more courses in development as well. and the way we've set up these courses, they're extremely modular. Every we could have

Vit Lyoshin (36:20.145)
Mm-hmm.

Taniya Mishra (36:26.529)
a a course that could be as long as a entire semester, so 60 hours, or it could be done in 25 hours, or it could be it could be, you know, really deepened to 120 hours. And but the key thing there is that it's modular. So think of it as we have created the like it's mini lessons, think of them as Lego blocks that can be put together to create a course that fits

Vit Lyoshin (36:51.846)
Mm-hmm.

Taniya Mishra (36:56.259)
The number of classroom hours or extracurricular hours that an educational institution may have. And we designed it on purpose because when I started the company in 2020, or even now, very few schools have course coursework or classes that are dedicated to learning AI. So as schools are adopting

Vit Lyoshin (37:18.8)
Mm-hmm.

Taniya Mishra (37:20.907)
AI curriculum into their schools, we have to have the flexibility that this may be offered as a in-classroom course for within computer science, or it might be offered as a after-school enrichment, or it might be offered as a summer program that we that we basically run and implement in partnership with our educational partners, right? So we've purposely left that flexibility.

Vit Lyoshin (37:34.833)
Mm-hmm.

Vit Lyoshin (37:45.392)
Mm-hmm.

Taniya Mishra (37:48.089)
But what where we are headed towards is we would like to get our courses accredited by at the state level so that they can actually be offered in a classroom for credit. So currently our courses are offered in some in-classroom settings, but more of our courses are offered either as extracurricular or enrichment or summer classes.

Vit Lyoshin (38:15.184)
Yeah, I see. And then also, how do you keep up with the changes in the industry? This is going so fast. Like in December, nobody heard about AI agents or were dreaming about having one. Now everybody's running them. Not everybody, but like some people. How do you keep up with the change?

Taniya Mishra (38:31.641)
That's right.

Taniya Mishra (38:38.201)
That's that that's a secret sauce. we do it with again, you know, I remember I said it's I talked about community. Young people should build community. I would say my company has is only possible because of community. So little over five years ago when I started this company, it was just me. It was me. I, you know, sort of I left my previous job, had

Vit Lyoshin (38:39.218)
I

Vit Lyoshin (38:52.326)
Mm-hmm.

Taniya Mishra (39:02.989)
These big teams, all these people I got to work with. Of course, now we were also stuck in the middle of COVID, so now we are at home. But I started the company and it was just me. The way our courses have developed is actually through input and collaboration of my of many of my academic colleagues to start out with. Going back to my career, I said I always worked at the intersection of industry and academia.

Which means over the years I had built up strong relationships with many academic labs and you know, academics. And when I came up with this idea that we wanted that I wanted, you know, to teach AI, machine learning, and frankly, frontier technologies taken together to as many people as fast as we can.

Vit Lyoshin (39:28.496)
Mm-hmm.

Taniya Mishra (39:52.737)
I was able to reach out to many of my colleagues and say, Hey, I know you guys are really busy. You don't have time to, you know, build entire courses, but would you be willing to be advisors, curricular advisors to my company? And we will build the courses, but we need your input in terms of what are the latest ideas, what are the latest technologies, tools, concepts, frameworks, right? Whether it's, you know.

responsible AI frameworks, how do you incorporate that? Whether it is, you know, AI agents, prompt engineering, vibe coding, whatever is the new idea, what the things to watch out for. Like you know, when we when Anthropic put out the information about mythos, right? I actually heard about it from one of our advisors. Like it probably had only come out the news maybe like 20 minutes.

Somebody just sent it on our Slack, they're like, hey, read about this. This should become part of our ethical discussions question for our students. So using that community or network of academics as well as industry experts is the base. But what has continued to grow is as our students have gone through our programs, learned a lot, gone to university.

Vit Lyoshin (40:58.066)
you

Taniya Mishra (41:17.919)
And then moved on to graduate school. It's so fun being in year five because we've actually seen people who joined us when they were in high school now pursuing PhDs in artificial intelligence, right? And that community is really active. Our student community is extremely active. So what we've done is we have built up this sort of second layer of young people who are already.

learning this, studying this, researching this, and we have made them part of this ecosystem. We bring them on as curriculum, you know, assistant curriculum developers to support our core team, or we bring them on as technical mentors who work with students. So it's once again, the way we keep up is because we have built almost a two to three layered network of experts

Who live and breathe this every day. And we have given them a way to create really broad impact by working with us and impacting the lives of students who are, you know, tens of thousands of miles away. So it's it's kind of we've made it very this goes back to my days as a computer scientist. We've made everything very modular. Everyone has a small part to do, and but we have sort of

Vit Lyoshin (42:28.252)
Yeah.

Taniya Mishra (42:42.691)
built it into the system architecture where it's multiple layers of experts with information in different areas that we are able to you know work with them and learn from and bring it together into a curriculum that then you know impacts students in middle school through high school.

Vit Lyoshin (43:02.705)
Mm-hmm.

Vit Lyoshin (43:06.576)
Yeah, no, that's great. And then also for schools to adopt the system, what needs to happen for more schools to adopt it?

Taniya Mishra (43:16.751)
For more schools to adopt it, they need to reach out to us. Basically, we work very closely with them in order to, you know, understand from them. I think we cannot go for like if we think about we will have to wait for when the state says everybody has to learn AI and now you have you are now required to offer AI, that's gonna take too long. I think schools need to start now. They need to think about what is the amount of time that is available to us.

In a school year to bring AI literacy, then AI fluency, then AI, you know, mastery, AI innovations to our students. Different schools will have different amounts of time, and we will work with them in order to create something that moves their students from point A to point B along

The AI fluency ladder with this responsible AI framing. So I would say the easiest way is for schools to reach out to us and we would work with them to create a customized curriculum that fits their teacher capacity, the time that's available in the school year for them, and whatever their goals around AI readiness for students is.

Vit Lyoshin (44:34.034)
Yeah, I think that that would be great if more schools adopt something like that. At least it will give an opportunity to students to pick this class and learn about it and maybe, you know, build career like you already told us many cases about that. So that would be great. And then just looking a little bit in the future.

since you're working with all these experts and things like naturally happens in your environment and you see all these trends and where things are going, where do you think, like how should I say that, what are some like technological trends that are developing right now that you see in the nearest future will become like reality and we have to learn about them.

Taniya Mishra (45:22.937)
So I mean there is so much development happening, but there are some really interesting there are interesting areas that there is going to likely be a lot of development in, with you and I have been around enough to know that, you know, jobs don't happen overnight. Jobs happen in areas where challenges are being faced by community. Like something is a problem.

You will only solve the thing that's a problem. If something is not a problem, you're not going to solve it. So there has to be, it's like challenge resources that are available to you, and speculations or you know, sort of bets, big bets that we make. All three of these things have to come together in order to create opportunity. So challenges we face, the resources we have, and the speculations we make together will create those opportunities. And

Vit Lyoshin (46:07.899)
Mm-hmm.

Taniya Mishra (46:22.009)
Based on what I'm reading about, what I'm seeing and hearing in the tech space, I think some areas where we're going to see a lot of development is going to be in the area of authentication and like data authentication and security. So I think we've we generally associate blockchain with crypto or NFTs or what have you, but that's just one application. Authentication is going to be a big area.

And because as the internet and the world becomes flooded with AI generated data, the value of human-generated data is going to increase. That means it's going to need to be authenticated more. I expect that there's going to be quite a bit of development in the area of blockchain for the purposes of authentication. And then, of course, you know, if we're talking about mythos, I think

Vit Lyoshin (47:03.451)
Mm-hmm.

Vit Lyoshin (47:14.716)
Hmm.

Taniya Mishra (47:20.289)
Security is cybersecurity is going to be the more AI is used in the more AI develops as a technology, there's going to be amazing positive uses of AI, but there's also going to be malicious uses of AI, which means cybersecurity is has to become a growing field, and we're already seeing that happen. Totally switching tracks. I think the area of autonomous vehicles is still.

Vit Lyoshin (47:34.855)
Right.

Taniya Mishra (47:47.875)
There's a lot of work, a lot of headroom, lot of utilization that is left there. because, like, think about it. was it in 20, I don't know, eighteen, maybe? We were all thinking that every truck on the road by 2026 is going to be autonomous. We're not seeing that. We're not seeing truckers are you know still driving most of those long-haul trucks, except for certain cities where we are seeing self-driving vehicles. I really enjoyed.

Vit Lyoshin (48:06.385)
Mm-hmm.

Taniya Mishra (48:17.517)
riding a self-driving vehicle in San Francisco. So that was super fun. But when I look at New York City, I think we're seeing some of the I did see in New York some self-driving vehicles, but I felt like every time I saw one, I did see a like a driver like person in there. So it feels like there's more testing happening. So I expect that you know, there's going to be a lot of growth in the area of automotive.

Vit Lyoshin (48:37.072)
Yeah.

Taniya Mishra (48:46.803)
we are already hearing about air taxis, right? I was in California a few months ago, Archer. So there is a lot of interesting work that's happening in the area of automotive, but using three-dimensional space. I think applications of artificial intelligence or technology or data in general towards health tech is going to be a growing field. Again, the question of challenges and resources comes

And speculations, right? We're all living longer. so that I see that as an opportunity. You want to learn a lot, you want to, you know, do really well in life and build a lot of things, you know, be very wealthy, you have to live for a while. So, you know, we're all living longer, but the challenge is that we are healthcare is now going to become more expensive, and we need to take better care of our health if you are going to live very long. So that's a challenge.

Vit Lyoshin (49:17.618)
Mm-hmm.

Vit Lyoshin (49:29.425)
Mm-hmm.

Taniya Mishra (49:42.883)
But then the opportunity is that now there are so many interesting and new ways in which AI, because of its pattern matching power, can help us get a better understanding of what is happening within our bodies. Again, going back to the our students' example, not just minutes.

But years before it happens, right? So I'm I was reading a little bit about multiomic sequencing, so DNA, RNA, proteins, but all being examined together. And supposedly this has the potential to be able to identify not which cells are malignant, but which cells might be malignant in in some time in the future. Imagine if we can.

Vit Lyoshin (50:30.982)
Mmm.

Taniya Mishra (50:33.229)
If doctors can identify with that level of precision, like which cells might be malignant. We're down to the level of cells, not even organs, right? the positive impact it can have on our health. But that means there's going to be a great expansion in the area of healthcare and health tech. I think these are some of the areas that I'm pretty excited about. I want to learn more about it, you know.

Vit Lyoshin (50:43.569)
Yeah.

Vit Lyoshin (50:53.159)
Mm-hmm.

Vit Lyoshin (50:57.776)
Okay.

Taniya Mishra (51:00.153)
Who knows, maybe my next company is going to be in one of these areas. I'm excited about

Vit Lyoshin (51:03.698)
Yeah, yeah, maybe partnering with a bunch of your students, right? Or creating some sort of accelerator. I think we talked about this before with your offline accelerators and things like that. Okay. All right. So thanks for explaining all of this. This is really exciting. I hope people really take a note of this and look into AI education for their children. So that's really...

Taniya Mishra (51:08.995)
Yes, yes.

Vit Lyoshin (51:29.85)
something I'm looking forward to, even though my daughter is still too young, but still, you know, in like 10 years she'll be ready for this. At the end, I usually ask three questions. This is my innovation Q &A, so I'm curious to know the answers from you. So first question is, can you please define innovation in a few words?

Taniya Mishra (51:51.639)
Yes, I will use the definition that I learned at MIT Sloan. it's innovation is invention plus commercialization. So dreaming up something awesome and making and testing out how awesome your idea is by seeing is anyone willing to adopt it? Is anyone willing to buy it? And when I say buy, I think of it very generally, right? Buy is are they willing to put down money, but also are they willing to invest time.

Vit Lyoshin (52:13.296)
Mm-hmm.

Vit Lyoshin (52:22.566)
Yeah, that's a good one. Second question is, which innovation in the history you think changed the world the most?

Taniya Mishra (52:22.765)
So

Taniya Mishra (52:33.325)
I saw this question earlier and I was very excited about it. Okay, I'm gonna say the printing press. And I'll say the printing press because I love to read, but also I mean printing press was there were there were like, you know, s many thousand books in Europe at least, and I I've only read it in the context of Europe before the printing press happened. But after the print after you know, pr the printing press, it was like it went from few thousand to five million.

very, very quickly. And again, people were very worried about job losses because producing a single hand-created book used to involve so many different people, right? It involved writers, artists, calligraphers, like bookbinders. There were many jobs just around the work of producing a single book. But printing so people were worried about job losses. But once the printing press happened,

It did so many different things. Not only did we produce so many books, but it actually it it gave rise to schools. It brought about new pro because people were like learning more so they could be more innovative. We are talking about inventions. Like it allowed because there were more books, books became cheaper.

Which meant that more people could access books. And because books were everywhere, that at the same time, I think schools were starting to be a concept, but it kind of supercharged schools because books were more available. And once more people got educated, they thought of so many new inventions and ideas that then overall actually you know, led to the industrial age. So I would say

Vit Lyoshin (54:03.154)
Mm-hmm.

Vit Lyoshin (54:15.376)
Yeah, exactly.

Taniya Mishra (54:16.835)
book like the printing press for me is probably one of the most exciting inventions.

Vit Lyoshin (54:24.056)
Okay, great. And the last question is which tech thing like software tool or something like that that we use today that we will be laughing at 10 years from now?

Taniya Mishra (54:37.647)
I think Zoom video conferencing, it is still not a solved problem. Now, I mean, we have been really we've been using video conferencing. I want to say in my life, for basically the entire time that I have worked, maybe since 2010. I don't remember. There was probably an earlier version of it as well. but my gosh, we still we are still constantly reminding each other.

Vit Lyoshin (54:57.007)
Mm-hmm.

Taniya Mishra (55:07.033)
You're on mute. people like even this morning, someone said, you know, the Link didn't work for me. It is in some ways, when I compare it, it's super useful. We all use it all the time. We're using it right now. And maybe because it's so useful and it sort of gets the job done that we haven't felt the need to improve it quite as much. I feel like that's the one.

That we are all going to be like, remember when we all would be like, I can't hear you. Can you see me? Like, I couldn't find the link. Like, why did we spend so many years living with tech like that?

Vit Lyoshin (55:44.082)
Yeah, okay, great. Okay, then I'll take it. It's gonna be interesting to see what's gonna be the transition where this is gonna go. Maybe some agent will give us an idea and develop it.

Taniya Mishra (56:01.401)
Maybe it will. And I I mean that said, look, it is probably the tool I use the most running a remote company. So I feel it probably more as a pain or a challenge that I would love to see solved.

Vit Lyoshin (56:07.047)
Yeah.

Vit Lyoshin (56:14.898)
Yeah, okay. Sounds good. Okay, Tanya, thank you very much for your time. It's been a really good conversation. I enjoyed it very much. Thank you.

Taniya Mishra (56:24.985)
Thank you so much for having me and thank you for just putting together this great podcast and I really enjoyed watching the other shows. I I hope that everyone listens to more of the shows. it's been great. Thank you so much.

Vit Lyoshin (56:39.462)
Yeah, thank you very much. We'll stay in touch. Bye-bye.

Taniya Mishra (56:42.639)
Absolutely, you too bye.