How To Get Started With Building Agentic AI Solutions/Applications - w/ Meri

As unreal as it feels to say this, it is now August 2025 and generative AI is somehow not the most cuttingedge tech currently. Yes, that's right. Move aside generative AI because Agentic AI is where the collective future of the AI world is headed. So here's a promise. By the end of this video, you'll have a strong knowledge of what Agentic AI is, how to get started with developing as well as learning about Agentic AI apps and also how to upskill to break into jobs in this field even without any prior SVE or machine learning experience. experience. My hot take is Python is not the language for applied AI engineering and is actually TypeScript. For somebody that's just trying to get started with developing for agentic AI, what would be some of the resources that you can recommend or a decent first couple steps?

steps? Honestly, genite is a thing of the past just for me personally. What you just said is probably the hottest take of them all. I'm Naman Pande. This is the Ready Set Do podcast. And in this episode, my guest is Mary Nova. Mary is one of the biggest MLAI engineer creators on LinkedIn in the world and through her content has helped hundreds if not thousands of aspirants land their dream roles. With her company break into data, she is now laser focused on coaching for Agent AI whose flagship boot camp has already has two successful graduating cohorts with a third one starting this August. There's literally dozens of success stories out here and I think it might behoove you to check it out for yourself. With coding agents again you can build things so much faster. You

can build things so much faster. You just need to have this framework of how to build. So that's what we give. Where does it stop? It stop at your imagination. imagination. Versel's AI SDK that's the most popular in production besides just Langraph 2. If you focus on building with those two libraries then I'm sure you can lend some interviews. In line with our theme of learning from high agency individuals who are just a few steps ahead. My goal with this episode is to help anyone looking to break into Agentic AI roles or folks who would like to build solutions or companies using Agentic AI. Subscribe on YouTube and any of your favorite podcast apps for weekly episodes featuring high agency individuals as well as daily clips from those episodes on YouTube and Instagram. And now without any further ado, here's Mary.

ado, here's Mary. Welcome to the only podcast in the world featuring stories of high agency individuals who are just a few steps ahead of us. Mary, welcome. Hi, thank you for having me. Nan, you've been so vocal for so many years now about AI development and I know you've helped hundreds if not thousands of people break into AI and you know just so involved with all of the coaching that you do on LinkedIn. when you're involved so deeply with a certain topic or field, you naturally begin to develop what um what just comes from disagreeability, right? Just hot takes around a certain topic where you're like, "Yeah, most people think this is true, but you can just kind of disagree." And as is now tradition on this show, I would love to open with what is your hot take on development, especially around AI that you really,

especially around AI that you really, you know, feel super strongly about? Yeah, I love how you're starting strong with the great question. So I guess uh the first thing that comes to my mind is you know how the entire AI engineering community thinks that Python is the main language especially coming from like machine learning background and people just uh training models with Python that's just became ingrained in us. But just recently after I guess uh I wouldn't say when Tajikup TV released but like earlier this year when we started our AI engineering boot camp I realized that there's a big gap between um real world AI engineering and what we see on social media like on LinkedIn especially with demo projects and on YouTube. So my hot take is uh Python is

YouTube. So my hot take is uh Python is not the language for applied AI engineering. it is actually typescript and uh you have and coming from a data science background in the beginning I was like I don't want to learn another language I just want to python is so simple and great it's h I didn't want to accept that either but after talking with the real world engineers especially living in the area and looking at open source projects and where things are headed it's basically it's all going to web applications and web applications are built on top of Typescript. So TypeScript TypeScript I think that's uh that would be my hot take. take. Fascinating. So just to double click on the piece that you said about the

the piece that you said about the difference between what the pet projects are right that are that go viral on YouTube or on LinkedIn and just the difference between them and real world projects. Could you share a little bit more about in what ways these differ for our listeners that might be curious? Yeah, sure. Um, you know, it's uh it's funny, but uh just like looking at new coding agents and like new co coding AI assistants, I feel like it's become so much easier to build not only demos, but really actual applications and u things that worked two years ago, 3 years ago are are just so behind right now because we have so many tools like AI assisted coding tools that can um 10x our entire workflow and make us build things. So coming from that I would say before you know how especially going back to Python

know how especially going back to Python everybody just like build things and use streamllet to show it but nowadays it's uh yeah you got to understand that majority of the web applications are are built on not on Python um and uh I would say the difference between them is just it's a lot it's actually it's a lot of just infrastructure it's a lot of uh backend stuff that demos don't have and that's what we actually teach. So for people who do not have full stack engineering experience I think it's the best time to learn that. So that's the difference. difference. Amazing. And obviously I know a huge chunk of our um agenda today is obviously to talk about agentic AI right agent engineering when it comes to AI.

agent engineering when it comes to AI. So um just as somebody that is semi involved in this space right I'm not as hands-on as you know some of your peers might be or that you obviously are and I know a lot of my listeners also kind of are on that fence a little bit where they have a decent understanding of what it entails but when you ask them to elaborate on some things that's when you know like the cracks start to appear so I'm curious to pick your brain to kind of um lead us into this this water which is uh And really the question here is um how how would you describe agentic engineering or agentic AI to a person that's maybe you know they understand

that's maybe you know they understand how machine learning algorithms work they understand like the basic statistics foundational models and all of that but yeah could you kind of intro for lack of a better word agentic AI to us and maybe you could also touch on why this is so important and why this is the future towards which we are headed.

future towards which we are headed. Yeah 100% uh it's a great question. So you can look at agents from so many perspective but I want to share from my own which comes from the open- source field and also startups because again because of my close proximity to the YC here and just the early stage startups here I uh I was naturally just exposed to the evolution of Genai especially when Chad came out things became um very different and I remember just going back in uh 200 22 late early 2023 there were so many hackathons back then and nobody would talk about agentic AI it was all about genai it was all about creating those ch uh chatd rappers there's just like the chat UI and that's it but um but few of those hackathons especially like very uh uh like applied applied ML oriented

uh like applied applied ML oriented there were people that are trying to create agents early on and people think 2025 is the year of agents but honestly all the engineers years that were into LLMs, they were already uh I would say prototyping and coming up with ways how we can allow LMS interact with the web. So I remember having like seen projects that uh where people built like browser agents where they it would do things for you. Of course, it wouldn't work all the time. And uh I I I still remember those projects actually that are now bigger that how how they look like in the inception. But going back to your question on agentic AI, it's basically an evolution from genai where it's passive generation of tokens but nowadays it's uh acting upon them. So that's why whatever somebody describes

that's why whatever somebody describes agents they usually have things like tools and memory and um context which is which is a big thing now. There's a context engineering set of prompt engineering. Uh so yeah I think that's uh that's uh very important to understand because 80% of investments that go into AI nowadays it's u agents it's all around agentic AI not so much genai so yeah that's super helpful from what I've gathered and from like the conversations that I've had it can be super overwhelming to figure out like how do you get into this right cuz as soon as you try to build something there's a new model there's a new thing and suddenly you're somehow 6 months behind Right.

you're somehow 6 months behind Right. So, um, for somebody that's, you know, just trying to get started with developing for Agent Tech AI, what would be some of maybe the resources that you can recommend or yeah, what can that you can recommend or yeah, what are like a a decent first couple steps according to you for somebody that's looking to get into this domain now in as of recording this in July 2025? Sure. I I guess uh it's important to differentiate between like getting started and breaking into the field because those two are completely different. So getting getting started could be just playing around with the frameworks. That's why I only um recommend this if you want to play around and not really uh but if you're like serious about getting into the field, I would always suggest just again going back to the TypeScript field uh

going back to the TypeScript field uh where you use things like Verscell's AI SDK. that's that's the most popular in production beside just lang graph 2. Lang graph is another popular production um agentic framework and uh those two if you focus on building with those uh two libraries then I'm sure you can land some interviews but if you want to just play around and understand how agents work um in your terminal then probably just using open AI agent SDK is a great start they have uh very simple abstractions that you can build with. Mhm. Mhm. Yeah, I guess that would be makes sense. And then but the recommendation is still that if you're trying to get those interviews, you have to have good solid projects on your resume, right? That showcase that you actually have built something and just

actually have built something and just knowing theory isn't enough. Would you? Yeah, 1,000%. Would you agree with you know I actually um like before when I was writing on LinkedIn only a year ago, I would be like okay study linear algebra, study neural networks. That was my go-to like road map for AI. But then after launching the boot camp and uh launching the company where we help people uh get jobs in applied engineering, I realized oh my gosh this advice is so outdated and uh we have people who are joining like after master's program they do have uh their data science masters or or computer science masters and and they're learning all of those things at school but they're not landing any interviews. And I thought and I and then I'm like okay I have to stop advising people learning

have to stop advising people learning theory because it's not getting you anywhere. Uh instead what worked for our students is actually building projects. So our entire boot camp is all about delivering this capstone project on top of smaller projects that you do on a weekly basis. But the final thing that we require you to like get a certificate is um creating the end to end capstone project that uses all the tech stack that we recommend. That's really incredible. So yeah, I I I would love to double click on the boot camp piece and kind of what it entails.

camp piece and kind of what it entails. But before we do that, I'm also curious to um have you shared a little bit about break into data, right? That's obviously your company. Really just looking for just kind of what kind of work you've been doing. any success stories cuz I love you know listening to those just makes me really happy. So yeah just kind of curious about what you can share about you know the work that you've been doing with break into data.

doing with break into data. Yeah thank you for asking that question. Uh actually just two days ago we had a graduation day on our second cohort. Okay. Okay. Yeah. And uh just looking at at the graduation day, what we do is just we uh demo all of their projects and and that's when I feel most proud of our team because I we have an instructor also uh his name is Hi and uh we have few TAs that have been incredible.

few TAs that have been incredible. They're also helping students and just looking at the that we okay here's the thing I I just remembered we have few people that have zero coding experience and zero yeah zero software engineering experience not even data science so they're just joining because they want to build things but using things like bold or lowable is just not enough it's not going to cut it if you are serious about getting a job in the field so looking at their projects oh my gosh I even have a screenshot in front of from the graduation but uh looking at their project project and feel free to share that if you'd like if at all that's something you could that would be great but sorry please continue did mean to I'll share it with you and you could put

I'll share it with you and you could put it on top yeah that works that works as well yep please continue yeah yeah but um I looked at their projects and people were sharing like oh my god I now have more confidence in building things end to end because even though we have these AI coding assistants you still need those fundamentals of like what what a web application consists of.

what what a web application consists of. What do you need so that it works consistently with your users and that's uh that's a lot of components and that's what we do at the boot camp every single day there's like a live coding session instead of a lecture every day we have live coding session. Yes. And our instructor just shares his screen and builds things from scratch. And he also talks out loud as he builds things. So like people can understand what behind the I guess the senior engineer screen. you know that's uh that's what we thought uh would make the most impact and it did because people are now not afraid because people think oh my gosh I have to know everything and uh if I don't know what this error means

uh if I don't know what this error means or if I don't know how to do this thing then I cannot move forward which is such a blocker because with coding agents again you can build things so much faster you just need to have this um framework of how to build so that's what we give and after that all I hear is okay. I'm ready to build. I I want to build so many more projects cuz I know I I can understand and can follow through and it just it just makes my heart full honestly. But yes, sounds incredible. Wow. I'm I'm honestly a little tempted to, you know, check it out and, you know, go go back to some of my coding roots that I have, so to

my coding roots that I have, so to speak, abandoned even though that's I'm just being hyperbolic for no reason. Um but I am curious about something that you said that kind of you know I I want to double click on which is that you said tools like bolt and lovable just projects built off of them are not going to be enough. Do you mind sharing why you think that? I understand like the probably the core basis of that which is that if you're building something really intricate that works with a lot of models and such, it's probably not just not even being it's it it won't even be able to do all of that configuration for you. Right. So that's what I'm getting at or that's what I'm picking up. Is that accurate or do you have a separate reason why you said that?

reason why you said that? Yeah, that uh that too. But also when I think about lovable and bold and uh those are for me it's um they're generating they're helping you generate your personal tools or helping you generate uh simple um websites and right like boilerplate stuff. Yes like like yeah boiler plate and and they are there's levels right there's levels to AI coding assistance. I was uh thinking actually the other day when I was at the gym, how can I describe the different levels of AI coding assistance? And I think the closest thing that I came up with was there are three levels. You know how um in the engineering team there's usually like a junior engineer, there is a mid-level

junior engineer, there is a mid-level engineer, there's a senior engineer and uh all of them have different scopes of what they can do. And same goes with the coding assistance that is uh on the same level as like lovable and bolt and then there is cursor and then there's quad code for the the reason why I describe it is lovable is like a junior engineer you can allow it to build like a few pages like a simple website simple UI connect it with the database that's it deploy it awesome um that's what uh junior engineer can do and then the mid engineer is like cursor it can work on a more complicated things it can even deliver features on its own and things like that. And then the third one is

like that. And then the third one is like cloud code that has um context of the entire codebase how it interacts with each other each other and what are the main components and uh the architecture and everything. So um the reason why I said lowable is not enough is because um if you want to advance in this career then I'd rather you use things like cursor and cloud code because that's when you can um learn more actually if you don't have any experience then it's the best way to learn through building with those tools. That makes a lot of sense and I'm really glad I asked because I was very close to bucketing all of Bolt lovable cursor and plot code under the same umbrella which obviously is wrong and that's not what you were implying at all. So yeah, I'm actually really glad I

all. So yeah, I'm actually really glad I clarified that because you know that would have been a head scratcher for a few people. And I guess just to close the loop on that, um, so you're saying if somebody I guess firstly has enough money and also has the interest to spin up like a a more complex agentic project using claw code, is that something you would recommend or would your recommendation still be that no build it yourself, right? Actually try to learn rather than just trying to hack to the final product. Does that make sense?

final product. Does that make sense? Yeah. Um yeah it's I think this question relates to engineering approach. So So you know how like again many people come to uh break into data with the zero full stack engineering experience and they don't really know how to ship in a way that engineering teams do and what we realized worked for us is teaching people how to ship in slices. It's the I think the I forgot the name of the company that first came up with this approach but it's not agile. It's not waterfall but it uh it's its own thing slices where you build things uh not just like let's say just front end piece of it that works on its own and and then

of it that works on its own and and then you build back end but more like a cake where you have the both front end and back end and then you just have a slice of it delivered. So that's really cool. Um and then in terms of the boot camp intensiveness I guess um for those who are considering joining that um what can you share about like how intensive is it like how many hours roughly how long the do the cohorts last and yeah I guess just in terms of time investment how are we looking looking yeah so our cohort lasts 6 weeks on average and uh we meet every day so uh we have two phases that's we've been experimenting on what works the best so far so are uh we realized that we need

far so are uh we realized that we need to upfront all the theory so that people have a better understanding of what technology is capable of like what is what are agents how how to create rag agents how to create memory how to create all those main components in the beginning and that's in phase one and then phase two starts uh in two weeks so like it lasts four weeks and that's when you build and that's when we have um live coding sessions daily where you join um the the the the instructor secret engineer. Yeah.

secret engineer. Yeah. Yeah. And then you just watch uh him do it and then you build it by yourself as well. So that's it. And also on um on the other day I mean on Monday and Wednesday on Friday what we have is Monday is like the lecture of the week and then Wednesday is like um usually we have uh real world uh expert who can uh help you understand even deeper and how they do things. So we had actually founders YC founders join us. We have people from enterprise join us and on Friday we have um demo days or that's uh but it it it changes too. So depending on what's going on in the industry so yeah yeah no absolutely I think that's it's clear

no absolutely I think that's it's clear how much time and effort you've spent into planning all of this right and you know just the incredible results that you're getting. Um, however, when I put myself in in the shoes of a listener, I think something that would really, you know, benefit them figuring out exactly what it is and if it's right for them is maybe if you can give an example of like a flagship project or I mean it doesn't even have to be flagship, but really any project that came out of that, I think that would really help uh contextualize exactly what you get out of the boot camp. camp. Yeah. Yeah. that we have uh actually we need to compile it together but um we have 100 students who've graduated so

have 100 students who've graduated so far and uh yeah congrats congrats thank you thank you and uh we I think we have at least those not everybody finishes of course but yeah but we have around 60 or 70 projects that uh we uh we will put on the wall so yeah we're planning to share it but oh I just remembered you asked about the wins right Few of our graduates already got jobs, landed jobs and uh they were able to show the projects and talk about the boot camp as well and the interviews and because there's such a huge demand for people who work with agents, I think this is just uh perfect for their job search too. So definitely agree with that last piece. I feel like honestly anywhere I look at this point, I think it's Yeah, I know

this point, I think it's Yeah, I know you said that it's not actually a 2025 thing. this has been quietly simmering in the shadows for a while now. But from my perspective, right, which is very much that of an outsider, it does really feel like it's really picking up steam right about now. So, yeah, I think your point on right now being a good time to dive in, you know, definitely holds true. Um, continuing, I am curious to kind of pick your brain around all of the mentorship work that you do, right?

the mentorship work that you do, right? All of the coaching that you do personally. Um I know most of it is related to break into data but some of it is not and you've been doing this for such a long time now that um one of like the most commonly asked questions that my audience requests is especially from people like you that have mentored thousands of students. What are some um common pitfalls that you see again and again? You know it's they're like most of them are kind of easily avoidable but you still see a huge chunk of the population face. be it just you know aspirants into agentic AI or we can even think more broadly just from you know breaking into data type domain as well.

breaking into data type domain as well. So any patterns that you've seen emerge around lowhanging fruits that can be well poisonous fruits I guess that can be avoided but that most people are unable to avoid. So interesting for some reason when you asked that question the first thing came to my mind is confidence. Wow. Um, the reason why I say it is because when I would talk to uh people from my community, especially like for some reason we have so many master graduates and I guess makes sense because they're all trying to get jobs and they have all the credentials but for some reason nothing is going on and partly it was because of the job market but um the reason why I said confidence is because many people just don't believe in themselves enough to uh reach out to people and to network because

out to people and to network because networking can is it's probably the only way to to land your first position honestly honestly and uh many people might disagree because yes cold calling I mean cold applying would work too these days but um if you want to work at startups let's say because that's what we specialize in and that's what I always recommend people who do not have experience in US is start working with startups because it they don't have the rigorous um like interview rounds that enterprise has and and they also mostly think uh through like your projects and like how you can actually solve problems and looking at your portfolio. So that's uh what I always recommend uh newcomers to focus on just your own confidence and so that you can start networking with people and

you can start networking with people and um yeah I think that I mean few examples is for instance I I when I was uh in Indonesia the last year I was networking also and some people said I just landed a full stack engineering position with zero experience and zero knowledge. in software engineering. I was like, "How how did you even like why what are you doing exactly? What's going on here?" Yeah.

exactly? What's going on here?" Yeah. Are you lying or what? Yeah. And and then he's like, "No, because I believe uh that learning happens when you get paid when you have something to lose, you know." And I'm like, "Okay, that's that's very bold and interesting." And uh I wish like we all more of us had this mindset of okay, you can learn on the job. It's just matter of getting the job and having having confidence in yourself that they can do it.

yourself that they can do it. But like did you also ask them how they got the job in the first place without any experience? Cuz does that work? Yeah. I'm curious. I think they just like again outreach on LinkedIn. They were just like talking to like hundreds of people online. Dang it. Yeah. No, that I mean that's such a good call out because it really shows just how far one can get right just off of the backs of um directed um intentional networking I think is probably the right way to put it instead of just you know this spray and pray approach with yeah it does work sometimes but I think your point is well taken on yeah just be more

point is well taken on yeah just be more intentional right have a plan stick to a plan and hopefully good things will follow um upex I think it I would be remiss to not bring up just generative AI engineering given how much we've talked about agentic AI. I know you mentioned at the beginning of this conversation that um one kind of started off from the other like agentic AI is almost the next step to generative AI engineering. So, but for those people that are more just concerned about trying to build for Gen AI, um what are maybe some core principles? Do most of the um approaches still track or is that kind of a different road map when it comes to Gen AI engineering?

comes to Gen AI engineering? Wow. I mean the these days like for me honestly Gen AI just like uh is a thing of the past just for me personally. Really? Really? Yeah. But it doesn't mean it's the same for everyone else cuz uh don't get me wrong, there are so many people that are going to pay lots of money for you to build the great rag pipelines, you know, that it's still it's still very much in high demand. It's just I like to honestly follow whatever is the latest thing and I think agentic is just very exciting because even in the open source community, we have new protocols like MCP, we have new tools uh that are coming out that are agentic and I think

coming out that are agentic and I think it's just exciting to see that. But genai is still there. Um, but it's just I think yeah, I don't I don't I'd much rather talk about traditional machine learning than than JAI. I guess I respect it. No, I respect it. And it's so fascinating for me to listen to that to what you just said, right? As somebody that, as I said, is a little bit more on the periphery of these things and is not as deeply involved or as hands-on. Um, yeah, I think that's just and I would probably guess that for most of the general population, what you just said is probably the hottest take of them all. Right. So, yeah. No, that's very very Why do you say that? I'm curious what wh why?

why? I just think Yeah, I think it's a simple answer, right? I just think that um developments in AI lag people that are actually in AI by and I'm just coming up with this number out of thin air but at least 6 months is what I've seen like even when Bolt and Lovable first became a thing and I was weirdly like still early on those trains like I I actually built stuff at a time where none of like my peers were and again this is important to highlight my peers or my peer circle or professional circle is very different from yours cuz we are more you know it is what it is oh great there's a new article there's a new

there's a new article there's a new model good to know right life goes on versus you who's like okay now let's use this to build something right let's tinker with it let's figure out what it's good at what it's not as good as so on so forth right and yeah I just think because of that lag really for most people I think by the time they even get um up to date with the latest development that development is now 6 weeks too late and like there's like five new things and they're just like it's not even worth my while to you know follow this actually. So that's just why I say that because I still feel like for

I say that because I still feel like for most of the I don't know normies I guess Gen AI is still very much the um cutting edge, right? Oh, it can talk to me. Oh, it can generate images. It does Gibli art. Cool, right? Let's go crazy. So again, I might be off there, but that's just been my anecdotal experience with my social circles and such. So which is why I think it's so interesting what you said that you're like, "Nope, don't care. It's it's a thing of the past. It's a fossil. It's a dinosaur.

past. It's a fossil. It's a dinosaur. I mean, now that you say it, actually, it just it makes sense because we have like multimodality is exciting. And it's just because I'm not in that space, I I whenever when I saw V3, I think that's the name, I was like, "Oh my god, this is insane." And even on social media, you can see all these generated um AI generated videos. And uh funny enough actually one of my friends founders he uh had a B2B SAS before all this Genai hype and now what he does is he created an agentic uh sales uh platform and he also built um like a persona online and uh on Tik Tok and he

persona online and uh on Tik Tok and he was generating videos with AI for like a year now and he has I think over 250,000 followers on Tik Tok and he never filmed himself ever. It was just hist generating with AI. And guess what? He's using this channel to promote his agent. Yep. Stuff. So that's insane where we're headed. I think I'm definitely underestimating. Uh probably I need to get into that, too.

probably I need to get into that, too. No, no, I think you're good cuz you're at the peak, right? Like why would you scale back down and you know I mean content it's great for content. Well, that's true. That's true, I guess. But also on the flip side of the content piece as well, if you're early with content on agenti at a time where no one else is doing that, I think there is very much such thing as early movers advantage when it comes to content as well. For sure. So yeah, no, I think your approach makes total sense. And going off of the story you shared about the founder, I think yeah, it's crazy how that's become like now the playbook, right? Clo does it. I know cli probably has I think it was 8 million or something that's just dedicated towards

something that's just dedicated towards Tik Tok, right? Nothing else. They're just literally burning millions of dollars just just to get yeah funnel views through. They have I think like 30 different accounts and all of them kind of do different things. Yeah, there was like a whole case study on this which was yeah very interesting. I'll link that below for our listeners. But yeah, apparently this is just the norm now which is yeah pretty incredible. And as you were saying that also I think once you start to marry concepts of agentic AI with multimodal engineering I think that's just the portal to a new universe pretty much right like there's where does it stop you know it stops at your imagination so yeah exactly it's the best playground of our lifetime indeed and and it's just still such

indeed and and it's just still such fertile soil still right to you know for somebody that's looking to get into this somebody that's looking to you know make a name for themselves or start a company. And yeah, I just truly, you know, I feel so blessed um being able to have conversations like these, pick the brains of smart people such as yourself, and yeah, hopefully I can use this as an opportunity to probably start getting a little bit more involved. Um, truth be told, I'll definitely be checking out the boot camp. That is definitely something that has piqu my curiosity. I I do think there might be something there for me. So, I'll keep you posted on, you know, how that goes or what I

on, you know, how that goes or what I find, but don't be surprised, I guess, if if you find a new member on your next cohort. cohort. Oh my god. Yes, let me let me know. We'll hook you up with some discounts. Okay, awesome. I appreciate that. Thank you. Yeah, I appreciate that. Um, and yeah, really, I think that's what that was pretty much everything I wanted to cover here today.

everything I wanted to cover here today. any final pieces of advice or any, you know, anything you want to put out there in the ether for anybody listening that you would want to share. Honestly, it can be anything. It doesn't even have to be about AI. Yeah. Yeah. No, this was uh I just want to say Nan, you have a knack for podcasts. This is this has been such a pleasure. Thank you for having me. But um and like for the last thing that I wanted to say when you were talking about the playground and all the excitement around this field, I I just I I have these like conversations in my own head naturally where I think about how these days um this one one characteristics can actually define your career your next 10 years and especially

career your next 10 years and especially it's important nowadays is basically having adaptability. So when I say adaptability is um you're not really so let's say if you're just a newcomer to the field because this field is still very much young you have such a great advantage to just become very adaptable to whatever is going on now. And by adaptable I mean trying out tools that come out just now just yesterday and writing about this and uh maybe just like uh exploring exploring and building new different projects implementing things that nobody has implemented and and it's very much doable too. It's not hard anymore like people got used to like the things that it's actually you need to like sweat it out. You need to

need to like sweat it out. You need to like yes there's the components of like debugging and just being persistent at things but things become easier things are becoming so much easier and now the moat is to become adaptable. So how however fast you can adapt that's that's um that that could define your nearest future. So I think that's what people need to do is to become more adaptable to change. I love that call out especially because uh you know just an anecdotal story that comes to mind. So one of my peers or one of my mentees actually that I helped he was really struggling with getting he granted he was in into product management. So he was really looking for core you know like I don't know what's like the right term but traditional PM jobs I suppose would be the right way to

jobs I suppose would be the right way to say it and he did that for about 3 4 months wasn't really getting anywhere and I was just like have you considered that there is now an entire new domain for AI PMs right like product managers that understand how AI works how machine learning algorithms work and he did have a background in tech so I was like is that something that you might consider and he was like I don't know I've never thought about that but sure let's do that and yeah like you know in a couple weeks he he was able to find an AIPM position. Wow. And really I I and he called me to like

And really I I and he called me to like thank me and such and I was like, you know, well, you're welcome. But I don't think that was anything like groundbreaking. But yeah, I I think I love what you said because just having an open mind, right? Just being adaptable, kind of figuring out where the wind's going, where the benefits are, where the utilities are, and then just going that way. It feels super obvious to say, but actually to do it is not as obvious. So yeah, I love that you said that and definitely needs to be said way way way more. So but yeah, um thank you so much for taking the time here today. Thank you so much for adding so much value in so many lives over on

so much value in so many lives over on LinkedIn and I know it's just been crazy following your journey and now with your uh with your company, Break into Data and such. I'm really excited to see, you know, what else you you're up to and yeah, it's been such a pleasure following your journey and yeah, hopefully we'll remain connected and hopefully you'll come back with one of your new boot camps. I know you'll be like right at the knife's edge of this stuff. So, I know I can trust you to, you know, open the doors for the normies, as I like to say.

normies, as I like to say. Yeah, 100%. Now one just uh let me know and uh I would love to share whatever we have especially for the community if they want to join. We're going to offer um special discounts for you. Amazing. Amazing. Yeah. But um I was uh I had a pleasure today actually. I think I think you're on to something. Keep doing this. I'm excited to come back too.

excited to come back too. Appreciate it. That brings us to the end of that fascinating episode with Mary Nova. Thank you all for sharing these conversations with those that continue to benefit from them. If you would like to support me, the easiest way to do that is by subscribing on YouTube and leaving me up to a fivestar rating on Spotify or any of your favorite podcast apps. Something that really moves the needle for me is if you share these episodes with a friend or family or anybody that might listen or by word of mouth, tell them about your new favorite podcast. Catch you all in the next one.

podcast. Catch you all in the next one. New episodes every Wednesday.