Conversations #103: Nitya Narasimhan, Senior AI Advocate at Microsoft
Written by Women Who Code
This article has been adapted from our recording of WWCode Conversations #103.
Manda Frederick, the Program Communication Manager of Women Who Code, chats with Nitya Narasimhan, Senior AI Advocate at Microsoft. With over 25 years of software research and development experience across various domains, including mobile, web, cloud, and AI, Nitya brings a wealth of expertise to the discussion. Nitya’s insights into the tech industry are invaluable as a Ph.D. holder, a dedicated parent, and a polyglot. Currently serving on Microsoft’s AI advocacy team, Nitya focuses on guiding developers in crafting the next wave of AI-driven solutions responsibly, particularly with AI on Azure.
Nitya Narasimhan: Thank you so much for having me. I’m so excited. I love your community.
Manda Frederick: The Women Who Code members are excited to hear from you because AI, ethics, and responsible development are at the top of many people’s minds now. It is also helpful to learn more about what you do in your role, which helps us understand your function at Microsoft. So, as a member of the AI advocacy team, what are some of your key responsibilities, especially in helping developers build AI-driven experiences in Azure?
NN: There are two words: technology and community. Those are the two things that matter to us. And when I look at it in terms of my role, we are sitting at the intersection of three things. We are looking at the product team on one side, we are looking at the community on the other, and then we are looking at partners who might be in this space. They could be building tools, or they could be building services. And so, as an AI advocate, I’m developer zero for the product team. For example, when we build a new product, they come to us and say, “Hey, we are trying this out. Do you want to try it out and tell us what’s happening? Is it working the way you think? What do you think your community wants to see out of it?” So I’m developer zero.
From the community perspective, we all know this: We feel so overwhelmed these days like there’s new stuff every day. From the community perspective from an advocacy perspective, we want to skill people up in AI the right way. And you mentioned responsibility, and we’ll get to talk about that. So, in that sense, we want to go out into the community and tell you, “Hey, here are some resources. Let me run a workshop. Let me tell you what the terminology is,” and then take you from the point where you’re aware of it to where you can do something actionable with it. We all know this: Women Who Code knows this, Microsoft knows this, and OpenAI knows this. We can’t go it alone. We all need to work together to make this thing diverse and inclusive and ensure everyone participates in the ecosystem. So when about a collaborative partnership, there are two kinds, collaborative partnerships with product or technology in mind. So, for example, I love Hugging Face, and I’m working to see how we can use some of their models and some of the demos I’m doing. Then, some partnerships are community-focused, like Women Who Code. And we’re like, “This is so great.” How do we make sure that that community also skillfully skills up on these technologies?
MF: When you’re working with partners, communities, and developers in your role, how do you advocate for responsible AI practices? What sort of initiatives or programs are you involved in?
NN: I’m going to set the stage for those who need to become more familiar with what responsible AI means because we all hear about responsible AI, and it could mean different things to different people at a very high level. We want to ensure that whoever’s using AI is ethically doing this and that the data models, the datasets you use, and the models you build are fair. And that anyone is, because let’s see that AI will be making decisions, taking, like building content. Are we making sure that that content is safe? Are we making sure that those decisions it’s making are correct? So, when I look at responsible AI practices, we look at them as a continuum. First, we need to teach people the principles. So Microsoft has these six principles for responsible AI, and we should share some resources with you later, but it’s things like fairness, transparency, and accountability.
So we want to educate you on the principles, but we need more. You need to know how to put them into practice. And so when you look at that, there are two audiences. And I know a lot of Women Who Code members are data scientists, but they’re also developers. Data scientists are very immersed in this space, so my team has been looking at what responsible AI means for the developer. How can I get you skilling resources? How can I do a workshop that teaches you how to debug your model with this tool? So we have something called the responsible AI dashboard, where if you have built a model, you can plug it in, and it’ll give you insights into how well your model is performing. Is it fair? Is it reliable? Where are the errors? Etcetera. And then, on the other side, we also want to make sure that once you’ve built your stuff, like all of these things, you can try out as a data scientist, but someday you’ve got to operationalize it, you’ve got to make it a product. And so the same tools, how do you integrate in Azure? So, we do the open-source on one side and then Azure integration on the other.
MF: So let’s say someone is an AI developer or a data scientist, but they don’t have an advocate on their team. They don’t have someone like you. What can they do? What resources or tools can they access? What could they do to develop more responsibly?
NN: We have a resource called the Responsible AI Hub for Developers, where some of these workshops are available. There’s also an open-source repo called the Responsible AI Toolbox, built by Microsoft Research. So, all you need to know is Python and Jupyter Notebooks, and you can get going with that. Last but not least, I have to give the shameless plug to Microsoft. Microsoft has a resource called Microsoft Learn. And if you go in there, like the workshop I told you about, you can do it in the open-source space. Now, if you want to do that with Azure, you usually have to have an Azure account. And that means that there might be costs, etc. But if you go through Microsoft Learn, we have that module available where they give you a sandbox with Azure in it. So, if you are somebody in a team and want to understand responsible AI practices, I suggest three things. First, go to that site to learn the terminology for responsible AI on Microsoft. Understand what it is that you need to be communicating about and how it relates to your organization.
Because responsible AI in retail might mean something different from responsible AI in medicine, the second thing is, then, once you’ve understood that, take that module and skill yourself up. There are even certifications, badges, and things you can put that say, “I have the credential; I’ve done the training in this.” So do that. Then, the third thing is, once you’ve got that, do a project. Take something in your team that you think, because of what you’ve learned, and apply it.
Because we have found that when you try to apply what you’ve learned, you start seeing where the gaps in your knowledge are, and you’re like, “I didn’t quite get that.” And, in that context, shameless plugs are abounding today. But we do have an AI Discord, and we all hang out there. So, if you have issues or want to chat, please get in touch with us. We’ll send the link to you later. But you can also find it on learn.microsoft.com/ai. It’ll tell you what the community discord is. If you’re in New York, visit my meetup. We meet every month; we cover a lot of this. We are going to be doing a responsible AI-themed meetup in March — so it’s perfect timing.
MF: You talked a bit about upskilling and certifications. More specifically, what core technical skills does someone need for your position? And how do you keep up with all of that continuous learning and upskilling?
NN: I’m going to break that into two questions. Because one is like, what technical skills do you need to be in my role? And then the second one, which is fascinating and important for us, regardless of what role you’re in, is how you keep pace with the change in the ecosystem today so that you are not being overwhelmed. Still, you always know enough to skill yourself up for the changes. So first, let me talk about advocacy. When you think about advocacy, three skills are super important as an advocate. First, you need to communicate well about the things you’re doing in a way that matches diverse audiences. Second, you need to be conversant on the tech platform. You need to know something. So, if I’m an AI advocate, you need to know at least one AI provider, one AI model, and one programming language like Python. Make sure you have depth in one thing to use as a frame of reference for knowledge transfer. Third, you must know one cloud provider again, so please try Azure.
But it could be GCP, it could be AWS. I want to emphasize that you don’t need to know everything. Pick one thing and know it well: one language, one cloud platform, one AI tool or provider. And then you’ll find that you can transfer that knowledge to someone else. So if you worked with Azure and then you’re like, “Hey, I need to use GCP.” it’ll make sense. I used app service here; I need to move it over to, I don’t know, app venture and there. So I can make that leap. The last thing I would say, and I’m biased in this a little bit, is that the fastest way for you to keep up, and I want to talk about various ways in which you can keep up with what’s going on, but the fastest way to keep up is to leverage the community around you. If you are thinking of a career change or want to grow your career and pivot it away from where you are towards more AI stuff, find people you think are who you want to be. It doesn’t mean you have to be them tomorrow. Meaning that they inspire you. You’re like, “That looks like something cool. I want to do that.”
Follow them on social media. Don’t ping them. Follow them because you want to get insights from two levels. One, you want to get the big picture. Are the folks like Yalacon the ones who are giving you these big pictures of where AI is headed? What are the challenges for the ecosystem? And you want to understand that. Then, you want to follow a few local people in your community. Because you’re like, “Hey, that person seems to have the same interest as me.” Because then you can collaborate, meet up, and find a small posse of people who want to study together and do something together. And you might find that your journey is not alone anymore. Does that help?
MF: We’re taught that you should get a mentor. Sometimes, it can be hard because of time constraints or distance. I love that you’re saying this sort of mentorship by shadowing and following people you think are doing smart and interesting things you want to model. that’s a really good middle ground for getting insights from people without necessarily having to do that—the full-out mentorship experience.
NN: I know. And it’s also a nice lazy hack. You know that they’re going to filter out all the bad stuff. Someone who’s at that level is going to be talking about only some of the tiny things. So, I’m overwhelmed with the amount of innovation going on. If I want to know what this one thing is that, across the industry, everyone needs to know, I listen to three people, for example. And if they say it on their busy day, they take time to put a tweet or write a post; it’s important. And I’ve also found I love some of these online courses. Microsoft’s, of course, but we’ve got an open-source curriculum. If anyone is interested in skilling up on AI, the link is like aka.ms/genAI-beginners. But what I’m trying to get at is that there is this community of people learning together, whether you find them locally, whether you find them online, or whether you find them via these like, “Hey, we’re all doing the same course together.”
If you are a person on these community forums who helps others, tomorrow, they may hire you to do that full-time. It is like if you are a person who loves helping people, and you are on this forum because you have questions, but then someone else asks the same question, and you hop up and say, I had the question; I want to help you. For some time, they take notice. This happened to a friend who used to be on the forum because he was doing the certification. And then they said, “Wow, you seem to know all the answers, and you’ve done all of this. Do you want to do this full-time?” And they hired him. So, you start shadowing people for the insights they give you, and then the next action is to start sharing your own. And before you know it, people are following you. and you formed a cycle.MF: You really can’t underestimate contributing. We talk a lot about building your portfolio. And that could be these sorts of contributions you’re talking about or speaking at events or publishing articles and things like that. start showing your demonstration of knowledge. And I want to ask you a little bit more about soft skills to partner with technical skills. Do you have any concrete tips for people to find other diverse technologists like you to follow? It’s easy for us to say, “Go find people and follow them.” But do you have any questions? How can our members find more diverse technologists in this field? How would you recommend they go about doing that?
NN: I’m going to say three things. And I always use the number three because it’s as many ideas as the human brain can hold. But, the number one, I’ll reiterate again, is physical community meetups, especially for diversity. I’m going to give a shout-out to Data Umbrella, run by a friend of mine in New York. It’s really for diverse, underrepresented people. Hi Reshama. One of the things she has done, which I loved, is run open-source sprints for women. And like they, when you go there, not only are you learning something, but you’re literally contributing to a well-maintained thing. So my point is, first, there are groups, such as Pie Ladies, Our Ladies, or Women Who Code.
Like, look at what your specialization is. React ladies, like every framework, every tool has a community. So go out to one of those, you might go to a few of them and then find people that resonate with you, and then you can move it offline, follow them on Twitter, you follow each other, join a discord, have conversations, so that thing. So that’s like a very loosey-goosey, “Hey, I don’t know what I’m looking for, so let me go find that out.” So that’s one thing.
NN: The second thing, and this, is that it’s a double-edged sword, but LinkedIn. LinkedIn has a bunch of groups. So, there are AI-related groups. One of the things I have found valuable is that everyone is doing newsletters these days. It’s not that I want to subscribe to them, but I have found it useful that people will periodically go live on LinkedIn and have these conversations with others. So the ability to be in a conversation with somebody you admire at a very close, like they’re saying, “Here’s my philosophy.” And you’re like, “Hey, I’m right here, let’s connect up.” The LinkedIn value for me is that it shortens the time between you talking to someone and then connecting with them in a professional capacity. As you connect to them, you’re not connected to their network. And then, last but not least, definitely look out for large-scale conferences. And I have to give a shout-out again. We are running a Microsoft AI tour right now. Women Who Code is worldwide, so I’ll use it, aka.ms/msAItour. It’s going around the world. It’s going to be in Tokyo on the 20th; then it’s headed to, it, it was in Bangalore, I believe. Then there’s Sao Paulo, there’s Berlin, there’s Paris.
So these are giant conferences. They’re free. Never say no to free. Because they’re giant conferences, they’re skilling. Go in there and go in there with your professional credentials. Like you’ll take a workshop exchange card and say, “Hey, this was cool. How can I contribute? Can I write a blog post?” Do the smallest thing you can. But those are the three ways because diversity is a loaded word. We put people into buckets of “That you are… ” No, it could mean I’m neurotypical. In my current context, I belong to a very small population because of my intersectionality across various criteria. And the more of these events you go to, the more of these communities you encounter, the more likely you are to find your tribe.
MF: You unpacked a bit of some of the technical skills that someone could hone. You recommended a Cloud platform, one AI provider, and getting good at one language. You also mentioned communication, which is more of a soft skill. And I wondered, besides communication, are there other soft skills that someone could benefit from gaining to do your role or generally in this industry?
NN: Yes. Soft skills are very underrated. We need to understand how important they are. And calling it a soft skill tends to make us compartmentalize it, but they’re not. I call them communication skills because they take multiple ways. One, there’s public speaking. We’re all terrified of public speaking, but public speaking puts you on the map. There are resources like Global Diversity and CFP Day. There are Write/Speak/Code used to be around. But the simplest thing to do is find a meetup and offer to do a lightning talk. And if you’re afraid, this is my hack for everyone afraid, do your first talk; what you’re going to do is you’re going to go watch somebody else’s talk. Many of us, including people like me, post our talks with our slides on GitHub or YouTube. You’re going to say, “Hey, can I summarize your talk in a lightning talk for my community?” Grab the video, and grab the slides. You already have slides. You don’t have to make them. You know what it is Because you heard me talk about it. Summarize it in five minutes and say, “This was an interesting talk I heard. I wanted to tell you why.”
That will break the ice. You’ll have done your first talk. You didn’t have to prepare for it, you didn’t have to worry, you didn’t know the material, it was all there. There are tons of ways to go. So do public speaking. Now, that’ll take you to the next thing. There needs to be more than technical writing and speaking. You need to write something. Now, writing is a lot of work. And yes, I’m not saying all of you have to do it. I have procrastinated on it for ten years, and I’m trying to get into a habit now. But what I’ll say is be intentional. Try to do one blog post a month or once a week; whatever is up to you. But make it about you. Try to use that to amplify what you learned or what you did because it’s SEO. When people search for your name, they need to find your name coupled with these blog posts and all these words. And that’ll raise your profile in the community. So write, and not only that, when you write, you realize how difficult it is to take something complex and write it down in a very simple way. You’ll learn a skill. Last, I’m biased, but visual storytelling. If you follow me on Twitter or see me, I love Sketchnote. And the tip I’ll give you here is that Sketchnoting has two value propositions.
If you are a learner like me, if you’re a visual learner, you will find that the art of writing things down reinforces ideas in your head, and the visual creates patterns. So even if you never remember the words, I’d remember the picture I drew and what I was talking about. So, it improves your recall. That’s one. Two, if you are watching another speaker, you sketch a note, and then you post it on social media, they’re going to retweet it. Lo and behold, suddenly, everybody is seeing your profile. And in a sea of tweets all taking screenshots of the same slide, there is this really weird colored thing in there. It does not have to be perfect, but it will be unique. So, pick that up as a skill. We have resources for that, too. The thing that was hardest for me, and that’s hardest for a lot of women, is that we are very afraid to raise our hands. And because we’re like, we know we’re going to be judged, and we’re like, “, we need to be 100% perfect.” because we are carrying this burden of like, “Hey, already I’m behind the thing.” So, you’ve got to be fearless. You have to cultivate strategies where the thing that you’re afraid of is your superpower. Be fearless, but be very curious. Don’t be fearless for the sake of being fearless. Be fearless about learning.
NN: If you did something that was spectacularly bad, you learned you were spectacularly bad. Write a blog post. Say, “Man, I was so spectacularly bad.” and it’s still good, and move on. I will also say that open source is your friend, especially now, especially in this ecosystem. People are shifting jobs like crazy. The environment is moving. Put your things out in the open. Because if you are doing stuff in your company, in your work, and nobody else knows, then when you need to leave and change jobs, nobody knows what you did. So daily or monthly basis, put stuff out there and contribute to open source, because it’s always there. People will look at it and say, “I’m looking at this person’s profile. And it looks like they contribute to three different repos that have to do with AI and Python.” And it could be small documentation. Take your technical writing skills and apply that writing documentation. If you read somebody’s docs and you didn’t understand them, fix them. They will appreciate you for it because it means that someone else wouldn’t if you didn’t understand it. So, long story short, really, really work on communication skills. Think about telling stories. People remember visuals, they remember anecdotal conversations, they remember metaphors. Cultivate those and contribute to open source because you will find your profile on that page, and you, in turn, would’ve helped someone else.
MF: How did you arrive at your current role as a senior AI advocate at Microsoft? You started in software research and development, and then you journeyed here. Could you tell us more about that journey?
NN: It took me 15 years to realize that there was a common thread across all of them. It doesn’t look apparent initially, but the common thread ended up being that what I really, really loved was that I like to be aware of things, and then I like to translate that knowledge into something I have to make something. It could be a project, it could be a drawing. I have to make something out of it. It turned out that when I started, I did my undergrad in electronics engineering. And when I graduated, this tiny company called Infosys was in a garage in India. No, it’s a multi-billion dollar. I was one of the earliest employees. And I remember my mom said, they’re never going to go anywhere, so you need to go do grad school. So I did. So thanks, mom. But the bigger picture is that the first action in my journey was having parents who told me to educate myself, be independent, and then take this lesson down the road of engineering. So, my first action was to do a graduate degree. I bring this up because I earned a graduate degree and a Ph.D. in distributed systems research.
I was very lucky because my advisors took that into a startup. So very early on, I got the sense of, “We’re not building stuff. We can create companies and products out of it.” And getting that ground floor look at the amount of effort was really useful in shaping how I looked at that ecosystem. But then I said, “I’ve been doing this thing for about six years. I love everything, but I need to do something different.” So, I joined Motorola. I was also in Motorola research for about over a decade. And I bring that up because at that time, that was the mobile revolution, that was the razor, that was the Linux phones, that was Android. And then there was the iPhone. So we lived in the middle. Right now, that’s the reason why I want to connect where we are now because of that remarkable thing where you feel like I’m on the cusp of this thing that is changing lives. I don’t know how many people here will remember the rotary phone where you have to dial, and here you are, Android. So, one of my earliest memories in Motorola research was that we literally had duct-taped wireless cards to the back of these boards, which had the chipset and were programmed to them. That was the phone like we were trying out WiFi.
But what I meant is that, when you’re in the middle of these revolutions, you seriously feel like, “Hey, I’m the first to try something. I can’t go wrong. Whatever I do, I’m teaching someone something.” So, I started in research, which gave me this lifelong love for tinkering. I want to break things down, understand how they work, and then like you might see patterns and stuff. The whole thing with the research is you want to see how that applies when you want to productize it. So that brought me to my next stage; after about a decade in research, I was like, “.” I’m also a parent. And this is like a note to all the parents out there. It’s never too late to change careers. In my case, very late parent. So I was like, “. I’m going to scale back a bit, going to bring up my, I’m going to be there for him.” And so I started working remotely. I’ve been working remotely now for 14 years. 15. He’s 15. , 14. There we go. So, at that point, I decided I had to do something that would allow me to be an entrepreneur in my own right. Research requires support, open source, web development, and working with local startups, and consulting does not.
So I started doing that. But what I was missing was people. You can’t have water cooler conversations. You can’t brainstorm an idea and say, “Am I doing this right? That’s when I discovered meetups, and I was going to New York City, and that got me into the community. So my story went from my real-life research, where I was doing innovation, all this stuff, having a great time, and then I’m like, “I need to start doing something on my own. What will it be?” But now I miss the people, so I must go to the community. When I started working in the community space, I became an organizer. I love teaching people. And I realized, man, if only there was a job where they would pay me to do this all day, and it was, and it’s called Developer Relations and Advocacy. So here we are. The lesson I will tell you is, yes, you should plan your career path, but don’t discount the detours. Sometimes, the path you think you should follow may not necessarily be right. You may need to take a detour to determine if that path is where you want to be. And if you really, really wanted to be on that original path, your detour will… You’ll find a way back.
But if the detour took you off the scenic route, you’re like, “You know what? I never wanted that freeway anyway.” Now you’ve discovered a new world you wouldn’t have seen otherwise. So, in my case, you have to have something that guides you on this path. In my case, I love telling people how technology works and helping them build things. And that ends up being true in research. It’s true in development. For example, in research, I was like, “Hey, something new. Let me tell you how you can build stuff with it.” As a consultant, I said, “Hey, I know how this works. Let me help you build your first prototype.” And I’m in advocacy, like, “I’m at scale now. We have this new technology. Let me tell you how to use it in your product.” So, you need something that motivates you all the way through.
MF: We talk about the whole technologist and find a career that nourishes you. And that, what you’re saying speaks to that. It’s also doing what you’re good at and what your heart calls you to. That’s how I came to Women Who Code. I had a good communications job, but I needed a mission like how you were missing people. I needed something meaningful and nourishing to apply my skills to. And that sometimes we talk ourselves out of following our heart, but as you’re showing the possibilities of what you could find if you do follow, that is so much more. And so what you’re saying is that there are a lot of stages to a career, so I wanted to know if you had more specific advice for people at different levels in their careers. We may have students, career changers, or professional developers. Do you have advice for different stages of your career?
NN: So I’m going to use this analogy. Those three criteria exist, and I’ve used this analogy before when I talk about community growth, but it will be the same for career growth. And I’m going to use a gardening analogy. So, when you’re a student, think that you are a student; you’re starting. So, I’ve lived in three locations. I’ve lived in Africa, India, and the US. In Africa, there’s this tree called the Baobab. It stores its water because it’s in a drought area. You have to be like that as a student. What you want to do is focus on one thing. Because you’ve got loans to pay, you’ve got, you are like starting. You have nothing to show what you know. So focus on one thing: create a LinkedIn and GitHub profile and contribute to other things, such as network, network, network. But build one brand or build one skill. Only try to do some things. Because then people will need to learn what you’re good at. They’ll say, “We don’t know who you are.” So, use one thing and reinforce that in everything you do so that when people look for that one thing, you will pop up. It could be like you decide: I will be the Python expert who builds DALL-E-based images for fashion. That’s your tagline.
Make sure everything you do in your blog post is tied to fashion. So, we have talked about this before, but you need to have one domain of interest outside of tech. It could be fashion. So point everything to it, but try to make that, that as a student, one skill, build deep, connect on LinkedIn, make sure you have those profiles, populate them. When it comes to career change. So, in India, there is this tree called the banyan. The banyan tree is like a huge trunk. It’ll spread out, and every branch will drop roots on the ground. So it can cover miles, a single tree. The value of that banyan tree that I want you to take away as a career changer is in a banyan tree. If you hack the trunk once that thing is mature, it will not die because it has put so many roots everywhere that it will survive. So, as a career changer, you want to have that mentality. Yes, you are; the trunk is what got you into whatever career you are, but keep dropping roots all the time. Going to different communities, building a skill, dropping a root. Should anything happen to that main thing that you were, you’re not going to, like, chopping that off will be fine. You can pivot to something else.
As a career changer, you want to think about how to take the things you know and transfer them to a new domain. In other words, I have this trunk; how do I create a new branch using what I know but adding it to a different domain? So keep that in mind. Constantly spreading out and dropping branches. If you’re a professional developer, I live in the Hudson Valley, New York state. My metaphor is it’s like fall. Every year in fall, all the leaves go; come spring, they renew. You’ve got to be like that. Every year, you must shed light on things that are irrelevant to your career. And you had better pick up new skills that will refresh you for the new year. So what does that mean? It means if you are in a particular place and are still in the same job or line of work, you get certifications. Keep them fresh. The certification will say that this person knows this, but three new things came up last year, and they know that, too. So do that. And then, if you are trying to pivot into something like AI but are still in an old role where it’s not AI-related, Build and share projects in AI, and you’ll still be able to see regrowth. And that, in fact, you’re refreshing your profile across all three, which is a really strong skill for employers because they’re looking out for people who can be resilient to change.
We all know, no one really stays in the role that they were hired for. The most successful people will keep pivoting within that org to like meet whatever the needs are. So the stronger you are at showing your ability to make these shifts the better for you.
MF: It’s interesting what you’re saying because we often hear messaging like diversify your skills. It is easy to confuse that with learning a ton of languages or platforms. And I love what you’re saying. It’s about truly diversifying your skills meaningfully in a way that supports your core interest, passion, or skillset. And that’s a really important distinction. Because it seems tiring, you can’t learn all the languages.
NN: Exactly. And it gets very stressful. You put about six months of your time into getting this, and then the next day, you wake up, and you’re like, that’s no longer relevant; here’s something else. So if you didn’t have a reason or a strategy behind why you did something, you did it because everyone was going towards the same cliff, and then you’re another lemming. So you shouldn’t do that. But strategically pick up skills. And that’s the other thing we talked about some other time: picking up skills to fill gaps. Don’t take the same skill and build it again and again. Try to compliment it. Try to get something that’s a little bit away from what you already know. So you’re growing your skills.
MF: In addition to the skills, you have gestured toward some of the character qualities in your career journey. You mentioned, say, fearlessness, and you were gesturing toward resilience and things like that. So, in terms of pushing yourself to grow in your career, what are some of the strategies that you employ to foster fearlessness, experimentation, embracing failure, and advocating for yourself? What advice could you give to our members?
NN: So I’ll start with the first one: you should find allies on your site. And I’m going to tell you two anecdotes. One is that there have been giant conferences. Google I/O is a great one. I used to go to all the Google I/O conferences a long time ago. In many of these, I used to feel overwhelmed. If you’ve ever been to these conferences, there are a lot of men and very few women. And you’re like, I don’t know anybody. And I’m here, and it’s like, “.” So I used to get all anxious. That’s when I started Sketchnoting, by the way. But what happened is that it also made me connect with other people who were like me. There would be a whole line of folks who would be sketchnoting. And so we started meeting up. There would be groups that would go together. So when you have allies, somebody watching your back, who knows you, you’ve built up a relationship over time. So when you do that, you don’t feel alone; even in a crowd where you are not the same as 90% of the audience, you still feel like, ” I know one person.” By the same token, if you are an ally and someone you know is doing a talk, do them a favor: sit in the front row so they have one face they can look at that they know; we all say this. However, the other side of the allies is also closer to home. The truth is that everyone moves, and everyone changes things, but there will be people at home who know you inside out.
So, in that case, ensure you cement your relationship with them so they are aware. I’m going a little bit off track, but like, one of the advice I’ve always gotten from home is, I’ll be like, “My God, this thing happened again.” and this, like, they’re not listening to, and the advice I’ll get is, look, you can tell people something, but you can’t make them do it. So you will only beat yourself up if they tell you you didn’t do it, but you can’t. So you got to figure out allies closer to home who know you, then play the long game. We all beat ourselves up because we try something, and it doesn’t work, and you’re like, “My God, I must be terrible.” And it’s very, very hard to pick yourself up again and again. There are so many microaggressions that you can’t do. But if you think to yourself, “This is a long game. , this is all fine.” In a year from now, I expect X, and then you are like, “If I didn’t reach that, that’s different.” But then you can ignore the paper cuts and keep your eye on them, “These are all like annoyances.” So, play the long game. And you mentioned failure, so I will talk about this differently.
I’m also culturally brought up in a household where you have to be perfect, not be perfect, but don’t show weakness. Don’t say, because there are enough people to tell you you are terrible. You don’t need to give them ammunition. But what I started thinking of was different; I was like, instead of not embracing failure, what if I scheduled my failures? What if I said, “I’m going to do this thing.” I know 100% that I’m going to fail on it; I know it. I’m going to take this risk. I know I will hate it, but I will do it as my personal dare. I will check it off my list and write about it, but I can psych myself up because I scheduled it. I can, like, so when you think of it, then when a real failure happens that you didn’t anticipate, you’ll be like,” I don’t need to schedule one this week.” Task done. Resolution, I need to do three schedule fails, done. But the bigger picture is we must de-risk this notion of failure. We think about failure as us looking less than perfect. Instead, we need to think about failure as we took risks others didn’t, so we moved further. And so what if other people didn’t? As long as you told yourself that I expected that. I was smart, I anticipated it, and I had a plan B to get around it, so you won’t be afraid.
So, schedule your failures and keep track of them. Keep yourself a little brag board, like, “Hey, I failed ten times this week. That’s a personal record. Good for me.” Anyway, it’s great. Failures are growth. I tell my son this, and that’s one of the reasons why I said parent as well. When you start having to tell other people what to do, you realize half the things you tell yourself are not what you tell them, and you better take your own advice.
MF: And interesting is this idea of, like, imagining the person you love most, how you would take care of them, and what you would say to them. And then apply that to yourself, and it’s a harder thing to do. And I love what you’re saying because, I mean, all the data shows us that sort of fear keeps women from doing things, like applying for a job they don’t feel fully qualified for, or asking for their raise, or in what you’re saying like maybe developing a certain skill or public speaking. And it’s, but if you can practice this muscle, which is what you’re saying if you can practice this muscle.
NN: No, no, no, I hear you. you’re 100% right. I like the idea of like a muscle. Yes, it’s muscle memory.
MF: You’ve given so many good concrete tips to our members, and we’re wrapping up the conversation here. And before we head out if you have a pro tip for our community or pro tips. If you want to share, are there any final pieces of advice that you would give them?
NN: I’m going to say, if you are going in AI right now, if you’re entering AI, the first pro tip I will have is to make sure you have a GitHub profile and a Hugging face profile and do one job in open source. Get your name in some repo with AI or Python on it. And once you do that, that first action is the hardest. And someone will say, “My God, thank you for this tiny little change you made.” And that’ll reinforce. So, as the number one tip, I’ll act back and say this more strongly. The number one tip I have for you is your career is your brand. It does not belong to the company you work for; it does not belong to the community. You’ve got to nurture it. So make sure you take those actions to nurture your career by putting that profile and committing to one visible task: an AI. Pro-tip number one: advocate relentlessly for yourself. Advocate for yourself. Write those blogs, write those… Because you are your strongest advocate. You are the only one who knows what you did to get there. So, advocate strongly for yourself, but do it in a way visible in the communities you care about. LinkedIn for professional communities, like Hugging Face for machine learning communities, and everything else, like physical meetups, is up to you.
MF: Regarding digital communities, how can people find you? If people want to learn more about you or connect with you after this episode, how can they do that?
NN: That’s easy. I’ve been around too long that I own my first name on all this. I’m Nitya on GitHub, and I’m Nitya on Twitter. I’m Nitya N on LinkedIn, and I’m Nitya N on Hugging Face. I would love it if you would follow me on Hugging Face Because I will spend the next month writing posts about AI. And if you want to get started on something and you want to write something with me, hit me up. Let’s work on something together. I’ll be planning out a learn-in-public style series. So it should be fun.
Hugging Face is this community for AI enthusiasts. But it started mainly as research folks. People would build models and publish them. So, they have an open-source platform where you can get machine learning models built by the community, such as open-source models. They also have tools, such as these libraries called Transformers, which are the core of machine learning. But here’s the nice thing: they also have courses on the site that teach you how to use them. The community folks there are genuinely nice. They have something where you can literally deploy and show off your projects right there. Most importantly, one of my favorite features is that it’s a very research-friendly community; you’ll see people sharing the latest projects. They’re sharing the latest papers and the advances that are discussed. GitHub is where you want to be because you’re developing stuff. You want to productize things and have the profile of a company you work for. Hugging face is if you want to start diving into machine learning and AI and follow a few people doing interesting things, start there—same deal. Create a profile, follow interesting people there, see what they’re doing, and write a blog post. Try something they’ve put and check it out there on the spaces.
MF: Nitya, thank you for speaking with us today in the Women Who Code conversations and for your insights. We appreciate your time. And to everyone who tuned in to the Women Who Code podcast today, stay tuned for more inspiring conversations and insights from tech industry leaders. Be sure to subscribe to the podcast for updates as we release new episodes to inspire you to thrive in your tech careers. Thank you so much, Nitya.