Always-On Mentorship: How AI Levels the Playing Field

Tim O’Connor:

Well, Hi, everybody, and welcome back to Kindrel Commons, where we believe AI is for everyone. And the way we try to help is to show you real people around the world and how they’re using AI to make their life easier, smarter, and sometimes a little more fun. I’m Tim O’Connor, and sitting virtually next to me is my partner, who has an amazing ability to look at things like AI and explain this to us in really basic, common sense ways.

That’s Dr. Adam Pah. Hi there, Adam.

Adam Pah:

Hey, Tim. How are you doing? I’m just glad to be here with you.

Tim O’Connor:

Well, good to have you, as always. It’s always a lot of fun to do these together with you, Adam, and with the incredible guests that we have. And I want to tee this up about our guest before we introduce her.

And one of the things we found, Adam and myself, everyone, is when we talk to people about AI, we learn how much they sometimes struggle with the ability to interact with it. The whole notion about conversation. Those people that we bring on as guests have a great knack of really getting into AI and conversing with it, making the AI literally a tool sitting next to them, like a person sitting next to them who’s an expert.

There’s an interesting concept that we all probably have to deal with throughout our lives is the notion of getting expertise and thought from others. Sometimes we call that mentoring, that mentoring can be business-related, it could be work-related, it could be personal-related, and on and on. So, it’s a mentor, an expert who can help you, guide you through some topics.

And the person we’re going to introduce to you in a second, Vivian Ly, is an amazing person. I’ve known her for several years, worked with her, and we were talking about how she uses AI, and she mentioned how she was using it for mentoring. And so, Adam and I light bulb went off and we said, we need to get Vivian on the show.

And so, everybody, I’d like to introduce Vivian Ly and tell us a little bit about yourself.

Vivian Ly:

Yeah, absolutely. I’m so happy to be here. For a little bit of context, every conversation I have with Tim always leaves me pondering and a little bit more excited about the next chapter of the world.

So, when he asked me to hop on this podcast, I was more than excited to join. So, just for a little bit of context, I know Tim more so through our personal and working relationship. Tim is a client of mine at a company called MasterCard Dynamic Yields.

We do web personalization, which means that we help make websites much more customized to people like you and I. Some of us think of Amazonifying a typical website. So, if we were to custom build it based off of everything we know about you, it’s as personal as possible to make it easier for you to shop, to look for items, and to ultimately connect with the brand.

And that’s how Tim and I first got acquainted, but our conversations have really delved into other facets of life as well, diving into everything from psychology to history to travel. And the topic of mentorship is one that’s particularly special to me, both in how I see Tim operating with his team, just be able to observe that from a third-party perspective, and the role it’s played in my career as well.

Tim O’Connor:

Vivian, before AI, what did mentoring mean to you? And just give a little baseline, if you will, that we can then talk about how AI has elevated that whole role of mentoring.

Vivian Ly:

Yeah, absolutely. So, mentorship is something I’ve been particularly passionate about just because I’ve seen how much it can help somebody progress in such a short span of time. And if we’re being honest, I’ve always wanted that for myself.

And growing up to a middle-class household, that wasn’t necessarily the easiest thing to find. So, as a kid, I was always somebody finding mentorship in books, for the most part, that I can get my hands on. I grew up in a household where curiosity was abundant.

And our bookshelves, like, I remember the living room of my parents’ home was filled with three massive floor-to-ceiling bookshelves of all the different things. So, I grew up with that mentality that you can find most answers in a book if you’re willing to read them. But I think when I looked at some of the other kids, I’m like, man, like Johnny is getting talked, walked into this internship because his dad is the CEO or friends with this person.

I don’t have that. You begin to see that knowledge gap and perhaps that relationship gap and how it impacts you. So, while you can’t necessarily change your circumstance, I think there’s a really unique opportunity to find mentorship in other capacities.

And with the advent of LinkedIn, of being able to connect to digitally on social, that’s been something I’ve really capitalized in my career, being really proactive in finding mentors by seeking them out online. I think historically, prior to LinkedIn, you would maybe hope that you end up at a company with strong mentors. You would seek out the strongest people.

But nowadays, you could actually talk to the top of the top people by reaching out to them and taking it a step further where we’re going. And I don’t know if you guys want to ask me this question, but I think with the advent of AI, AI helps in a few different ways. One, it actually replaces some of those baseline questions you would ask for a mentor to establish more of the infrastructure of what you would want to know about a particular role or industry.

You can find that out online. But I actually think AI allows you to have a deeper conversation than you could have innately if you did not use AI to prep for a conversation with a prospective mentor. And I think that is a really compelling application for a lot of young people or people that are out there seeking mentorship or seeking to gain deeper industry expertise, using AI as a research layer to understand what are the bare bones of a particular topic and how do you apply that to this person’s expertise and how do you tie those together to ask better questions, to have better conversations, to get you to where you need to be.

Adam Pah:

That’s such a beautiful way you just laid out the roadmaps of mentorship right there. It really resonated with me because I was also a very bookish child with a salesman as a father who kept saying that the entirety of networking, right, that networking the human interaction, that is the progress of the way you make progress. And those are really your two options, or historically were.

And you talked, you mentioned how LinkedIn, the internet allows us to connect to whoever, wherever across the world. And so it seems like you have everything that you could possibly need even without AI, but what made you actually try it in this way? What made you say, let me give this a go?

Where was that first kind of moment?

Vivian Ly:

This is going to be a long-winded answer, but I think with any type of technology, when it’s forced on you, it’s just not going to stick, right? If somebody says use AI because you need to use AI and robots are going to take your job and eat you alive, that comes from a place of fear. I’m sure that works for some people, but that’s not necessarily how I think the average person should be pooled and moved through life.

I think life gets a lot more colorful and vibrant when you’re pooled by curiosity. And so for me, it actually started out in a really fun way that you’re not going to expect this conversation to go in. Maybe a year and a half ago, we were heckling one of my friends who were trying to get her onto a dating show, a live dating show.

We were building her application packet because she is such a character. She’s hilarious. She has great banter.

So we were pulling together all these different facets of her personality. And we’re like, I think we just got carried away at this girl’s dinner. And we were like, okay, maybe we’ll turn this into a rap.

Maybe we’ll make it more poetic. And we started playing around with Chat GPT and it became a full-fledged roast of all the ways that we could harass our friend and get her submitted into this dating show. So that was probably the first touch point.

But the reason that I start there is because that’s something that’s so fun and whimsical and playful that it shows your brain, okay, these are some of the ways that you can connect with AI in your day-to-day life. That might seem trivial, but that, hey, it gets you a step further. You’re a little bit more effective at coming up with a compelling pitch, one that’s fun, that’s going to get some attention.

You’re improving your communication skills and your storytelling skills in some capacity. So while that seems perhaps stupid.

Adam Pah:

No, I mean, using technology to harass your friends is a foundational part of technology.

Vivian Ly:

I think that was a really interesting bridge in how to leverage AI on a personal note. So fast forward, again, back to mentorship. I previously lived in California and I lived in a really beautiful beach town called Newport Beach.

And that’s fantastic to perhaps retire in, but it’s not necessarily the most networking friendly place. When I moved to New York City, I did that with the intention of increasing my surface area for luck and proximity to mentors and the type of conversation that I wanted to be in. So what that allowed me to do is it’s put me in different rooms I just wouldn’t have been in.

And in one of those conversations, I was talking to a founder and this was a really critical juncture of my relationship with AI because what he told me is he was using AI to create different mentors in different dimensions of his life. So what he had put together is a mentor for his business, a mentor for his finances, a mentor for his health, a mentor for, and you could even divide this into subcategories and kind of stick it into bigger and broader buckets to help you compartmentalize. And the reason that’s so powerful is because with Chat GPT and these custom agents, you’re able to program them to have a particular view or lens to give you the proper advice.

And I am a huge advocate of never asking or taking advice from somebody whose life you would not want or somebody whose values you don’t respect because that often doesn’t lead to the outcomes you want. So what I really love about that aspect of programming Chat GPT is you can get better advice that’s tailored towards you, who you are as a person, your values, and where you’re looking to go, and some of the dimensions you need a little bit more strength and guidance around. So I thought that was a really smart way to establish a stronger baseline in different areas of my life.

And then from there, I was able to get a little bit more specific with what some of those subtopics were and where I needed to divvy that out to be a little bit more granular and nuanced, but that at least allowed me to build some baseline infrastructure.

Tim O’Connor:

I just find this absolutely fascinating listening to you at this. There’s so much we can dive into. I want to dive a little bit back into the notion of this different mentors, if you will, or the accessibility to the mentors.

There has always been this challenge of mentorship. And, you know, heck, you can go back to the Knights of the Round Table, right? You know, having access to Arthur.

And people at different ages and economics, et cetera, have access to things. As you mentioned, somebody, their dad knew a CEO when they get a job, right? Most people don’t have that.

And they have the situation where mentorship comes up almost to some degree, random chance. Yours had happened, actually, because, but you did some things to improve the likelihood of interacting with people. When you started doing this, and you think about people out there, not just yourself, but you think about people there, to what degree does using GPT, Claude, et cetera, help to level more the playing field for those people who don’t have access to things that other people have?

Vivian Ly:

So the first thing I think of is actually informational interviews. So they tell you in college, have informational interviews, explore different industries, get different perspectives, get a tactical understanding of what it really looks like to be in an industry, what their day-to-day looks like. And if you could see yourself there, what skills gaps do you have?

And I would say I spent a lot of my early 20s having those conversations, but needing to go out and hunt down those conversations, whether it be through LinkedIn, which was the most precise way to do it, or through hoping that, like, I love my mom, she would always try to help, and say, this person’s tangentially maybe related, and within the field of business, if you want to talk to them. So basically something that was not relevant, she would try to make relevant. But my point being is all those conversations, when I think back on them, I was only able to get that information because I talked to people on a regular basis.

Content was also less prevalent back then, where people weren’t openly talking about their experience, where nowadays, I think a lot of those early stage coffee chats that you have to get baseline information about how an industry works, what type of work you would be doing on a day-to-day basis, where your skills lack perhaps some of the immediate needs of that particular function, how you could make it up, you can outsource to a conversation with Chat GPT. And so I’m not against still making those conversations, but what this does is it streamlines that.

So you have that conversation Chat GPT, and as opposed to starting at level 101, you enter the conversation at level 202, and even in your initial outreach, that’s going to be a lot more thoughtful of a conversation, a message that, say, somebody like you, Tim, if you get a ton of inbound every day, you’re not going to respond to everybody. If somebody says, Tim, let me pick your brain over a coffee, you’re going to say, sorry, I have better things to do, like talk to Vivian and Adam. But if they send you a thoughtful message after doing some of their research, and it’s a little bit more tailored towards you, and it sounds more intentional, you’re more likely to even answer that message in today’s day and age.

So it does two things. One, it allows you to get a stronger baseline of information faster without having to manually talk to all these people, do all this outreach, therefore saving you time. But two, it also increases your likelihood to talk to somebody and to have a deep enough conversation where they might even want to be your mentor or help you out.

Tim O’Connor:

You know, with that, let me ask a follow-up then, because you just brought in a notion like sales people could use. Why do you think people are reluctant to do what you just described? Because I’ve talked to a number of companies and people and their sales teams do exactly what you just said.

They say, sales people do this, or I’ve interviewed people, you know, to companies to come in to our job. And you say, what did you do? And they didn’t use GPT, et cetera.

What’s the barrier, do you think? Because it’s so aha moment when you just described what you described.

Vivian Ly:

I think the barrier is the same barrier that prevents people from having good conversations. It is a, they, they lack the ability to ask the right questions. And what Chat GPT does is it provides a little bit more of the structure of the bones that give you at least something to bounce off of to ask better questions.

So even with Chat GPT and that concept of building out different GPTs, that’s something where maybe I could have figured that out at some point, right? It’s not so crazy of an idea, but it’s just not something I thought of immediately. Like somebody else needed to tell me to do that.

Like not explicitly, I saw it and I thought it was a great idea and then I did it, but somebody else needed to create that linkage in my mind. And then from there, I was able to run with it. So I think even in education, I think about working with customers, there’s often this small linkage between how you operate and a big idea.

And so he needs to make those small connections for something to click. And once it clicks, you can go. But I think what we’re missing at this stage is those small linkages and conversations like this help jumpstart the usage we need.

Adam Pah:

Yeah. That’s what we always talk about in science, right? Where it’s the, the adjacent unknown, right?

And starting to explore that leads to these aha or novel moments. It’s not, it’s not that it, it’s this massive surprise at the end, but when you, when the light’s not on underneath where you’re looking, everything seems far more difficult.

Vivian Ly:

Yeah. It’s almost like, when your muscles aren’t firing, you almost need to jumpstart it. The muscle’s always been there and it can be strengthened, but you need to zap it.

Adam Pah:

So I think, I’m just really curious, right? What is one of these mentors? What kind of advice, what’s a concrete moment that you can talk about?

You know, cause a lot of this gets into the question of like, when you’re getting advice, how, how are you going to validate it? Right? This is a computer program in, at its core with data telling you something.

So how do you build the trust, right? That this is good advice that you’re getting.

Vivian Ly:

So some of it is through prompting. I would say prompting it with the right background and then also using it as your biggest critic. So for example, if you want to, let’s say you’re trying to build a fashion company and you don’t know anything about business or a business plan, you can ask Chat GPT to begin with.

Or you would say, imagine you are a BCG consultant who’s had over 20 years of experience analyzing what makes companies work or fail mixed with being a retail executives who started their own organization. Maybe you reference a few executives that you admire. So you’re curating the background of this person.

And let’s say you have zero dollars to start with. What would it take to build a fashion brand? What are the main categories of things I need to do?

And what are the main aspects of the business plan? You’re not just going to take that business plan verbatim and hijack it. But from there, at least you have the structure or the bones of the things you need to figure out.

And from there, it becomes a lot more manageable to figure out in small chunks, knowing that you have each of these dimensions versus saying, Oh, I think I need to figure out the revenue model. I think I need to figure out like what it is I should sell. I think you at least have something that’s a little bit more comprehensive to start with.

So that’s one, getting an assessment of what the bare bones look like. In the past, you know how much reading you would need to do and how many people you would need to talk to and how much you would need to cross-validate if their feedback makes sense based on their background or where they’re at. That’s so much work.

This at least creates more of that bare bones infrastructure for you to begin with. It’s not perfect, but it’s a much stronger starting point. It’s able to aggregate not only all this data you’re seeing online, but because it’s ingesting from social and we’re seeing a massive uptick and so many people sharing their experience on social, you also do have the mastery and the inputs of leaders that are out there sharing their voices on LinkedIn, on Instagram, on TikTok ingested in there.

So it’s a really strong starting point as a baseline. And then from there, this really interesting advice I got from an ex-Amazon product leader, she said, I also have AI roast my ideas. I give it an idea and I say, what are all the ways that this would fail?

What are the breaking points in this idea? And I really like that. I hadn’t thought of thinking about it that way, but it’s a nice way to see your blind spots and all the areas you might need to mitigate for.

And so I kind of use it in those two different dimensions. One to establish that baseline where as opposed to a mentor or 20 mentors would need to talk to you to aggregate at least what is that baseline or the 20 books I would need to read to try to stitch together what that looks like. I’m able to get that from AI where it is pulling in some of those resources it’s ingesting.

It’s also pulling in from people talking on the internet in real time to give me something to work with. And then from there, I need to be discerning and thoughtful about how do I take those chunks and maybe bring those to mentors? Or how do I use AI to learn a little bit more individually about each of those chunks?

And then if there’s things where I have ideas and I’m not sure about them, how do I try to stress test them through AI and to continue to refine that process? So I wouldn’t say it’s the end all be all, but it’s a nice feedback loop and it’s a nice thought partner if you don’t have one.

Tim O’Connor:

So when you’re doing that and you’re, let’s just use the example of books, right? And that’s a list. You go, you get a list, you get a list of books.

Or you talk about social media, social media, people put things down there, but it tends to be a one-dimensional that they’re putting something out. How do you take those scenarios and then make them conversational? Because you mentioned how important that is.

Vivian Ly:

I think that’s taken a lot of practice. I would say for me, I think I’m just more of a systems thinker by nature. It’s how I learn best.

And so for example, when I was younger, I never understood the sequence of just reading history texts and memorizing everything. It just never made sense in my brain. I always needed to zoom out.

And something I wish I had was more of what is the art, like what has happened? What are the big moments that happened in history and how do they tie to one another? And that’s how I’ve always personally learned.

And so that’s how I structure more of my questions. What are the relationships between two things? That’s more so what I’m looking to learn with AI.

Do things interact with one another? So it almost needs to be more of a concrete example to explore that a little further.

Tim O’Connor:

Okay. So you use the example, a list of books. So AI comes back and gives you a list of, here’s 10 books that would be important for you to read, knowledgeable about for this particular topic.

What would you then do?

Vivian Ly:

If the topic was building a business plan, I would say aggregate, take the best of each of these books. And based on the prompt I gave you about the business and building, the constraints I have, show me the core things that I would need to figure out to build this business.

Tim O’Connor:

So then it comes back and gives that to you. So you’re talking about the mentoring. A great mentor knows you and can start telling you some things and may ask you questions.

But this is not that person. This is a computer, which to a large degree is deferring to you as to how do you want it to work with you? So maybe I’m getting at, what can you tell, or what have you told the AI that you use in terms of how to be a mentor to you so that it acts and performs a certain way in its conversations with you?

Vivian Ly:

So there almost seems like there’s two questions at play. The first one I want to tackle, you mentioned, if you don’t have the language to ask the right questions, what can you do? The simple answer is you could ask Chat GPT, what questions should I be asking in this?

Tim O’Connor:

Nice.

Vivian Ly:

Step one, which sounds so simple, like what should I be asking? Because that helps train your brain to think, oh, okay, these are the types of questions I should be asking. Or what did I not ask that I should be asking?

What have I not thought of that I should be thinking of? And so the more you ask that, the more questions you’ll get in your brain will begin to make those connections. So that’s one.

And then going back to programming it, I think if it’s like, for example, if we talk about finances, the financial advice that you give somebody who can day trade and you can sit at their computer all day long and make trades is going to be very different than somebody who wants to set it and forget it. And so those are constraints that you want to program into your AI. One, I have the ability to sit by my computer and day trade, or two, I want to set it and forget it, and I’m just looking to save for retirement.

Depending on your age too, it’s also like, what is your risk appetite? How long can things go awry or not? When do you need that cash liquid?

So more so in bringing up these examples, it’s meant to add a little bit more color to your situation, your headspace, your values, and to add that context so that AI is able to give you better advice that’s custom-tailored to you versus something that’s generic and for the masses that should give you as a default.

Adam Pah:

That first point is actually a really fundamental one that I think extends out of this, but really makes the point clear. I always thought that the best interview, as an interviewee, the best question during question time is, what do you know that I don’t know that I should know? When they ask you, do you have any questions?

The question you want to ask is, well, what questions should I have? And that fundamentally changes the relationship with information here. You are now actually not just being able to grab and consume, but you’re able to interact and say, what do I not know?

What do I need to ask you about to get to the point that I have some idea of what questions I should be asking? And that really does change the nature of this relationship beyond just, I ask a question, it gives me back an answer, I read it. And so, has there been anything that you can fall back on, on where that’s really unlocked a big step in your knowledge journey, is going through that, like, well, what don’t I know, and trying to jump off from there, and it’s taken you in a different direction than you thought you would have gone?

Vivian Ly:

I can’t think of, I guess, maybe a specific scenario, but for me, as somebody that’s working in a large organization, working on web personalization, where we span everything from retail, to B2B, to financial institutions, to QSR, and that industry set continuing to expand, you do need to learn a lot about different business models, and the changing nature of those industries over time. So, for me, I more so use it if I’m really diving into an industry, and getting deeper, and deeper, and deeper through that questioning loop. So, it’s not necessarily one thing, but I take, I understand what the bare bones are, and then I’ll break it up into almost course curriculum.

There’s certain areas that I inherently understand that make sense to me. There’s some areas I feel a little less confident in, and then I’ll use AI, and I’ll go through that loop over, and over again, until it makes sense.

Tim O’Connor:

The way you’re thinking about this, and what to do, and how to do is brilliant. Now, let’s tap on one question about, you know, you relying upon AI for mentoring, and you gave some great examples. If you had a real person who was mentoring their XYZ in a particular job, they give you advice, you can have a pretty good chance that the advice they’re giving you is based upon their experience.

It may or may not be the best experience, but it’s their experience, right? Now, you have this wonder machine AI that’s taking in all kinds of information that it’s gathered over time, and now it’s trying to answer something to you. How do you know when the answer seems like it’s BS, or it’s not actually a good answer?

Vivian Ly:

So, Chat GPT, I guess that’s a really good question to address. At first, when I started using it, I was like, man, I am the smartest person in the world. It agrees with everything I say.

I feel validated and understood in a way I’ve never felt. This is crazy, and then I think it actually makes you a little conceited at first. You’re like, everything about me is perfect, and I should be CEO for the planet.

And you do reach that point where it just seems shocking that it affirms you so much that you’re like, there’s something wrong here. And so, I did ask at some point, hey, are you just validating everything I’m saying? And it said, yes.

Tim O’Connor:

Thanks for the honesty on that one. It’s a great ad.

Vivian Ly:

And then from there, I was like, okay, if that’s the case, I need to get a lot more tight with where it’s coming from, and what are my constraints, or what are my criteria? So, as opposed to, let’s say, talking to somebody who’s been at BCG leading a particular sector for the last 20 years, I can just say, imagine you are, and I could even pull in some referent people. I could pull in their research.

I can pull in some books, and I can mastercraft my ideal mentor. So, when you even think about manifestation, and you’re gathering all these facets from these different people, you can basically do that with AI and create your perfect mentor based on what you’re looking to learn, what their value set is, how they teach information. I think that’s another actually really interesting piece, too, how you learn and how I learn might be different.

And so, having a good understanding of what is your learning style, what makes information resonate, even training AI to teach you in a way that you understand best is important. And how you do that is, you could even say, hey, based on how I’ve asked you questions and our dialogue over the last year, how do you think I learned best? To recognize patterns even in yourself that you haven’t had the right words to describe is particularly important, and that’s why I’m a huge linguistics nerd, because if you can’t describe these aspects, it’s very hard to, it’s like hard, like even with emotions, if you can’t, if you can’t describe the word for emotion, it’s hard to actually feel it at its very core.

And I could say the same thing about like learning styles. There might be a very particular learning style that’s unique to you, and there might be a whole body of research on it that would make your life 20 times easier to be integrated into how you consume information, but you would never be able to connect the dots if you didn’t know what that was called. So, I think maybe like a concluding point is because it has so much raw unstructured data on you, everything from how you interact, how you ask questions, the cadence, the things you’re zoning in on, it’s a really good way to aggregate some of those trends and how you behave, how you operate, what your blind spots are, how you could evolve, what works for you, what doesn’t, just spit back something that helps in a lot of facets of your life.

Tim O’Connor:

Well, I tell you what, Vivian and Adam, I think we could do a part two on this at some point in the future, but I see we are at time. So, what we’d like to do just to conclude as we kind of close down is tell something, Vivian, if you’re meeting with somebody, you’re that person that was the startup person now, and you are meeting somebody who was like you, if you will, what would you tell them? What would your summary advice be in the area of mentoring and getting advice from an AI model?

Vivian Ly:

I would say that you can’t get good advice from people whose lives you don’t want and whose values you don’t admire or respect. And so, if you are having a conversation with AI, you need to apply those same principles and make sure you’re talking to the right person. So, it’s going to be critical to program that into your Chat GPT before you just basically are taking advice from Joe Schmo off the streets.

Tim O’Connor:

Wonderful. And Adam, how about you? Any advice to people when it comes to like, what would you do then, like the first thing you do?

So, she says, here’s what you do now. What do they do as a first step maybe?

Adam Pah:

I think what I hope everyone takes from this is just go right now, think about someone that you don’t have access to, but you would love to get advice from about your life, about anything, and go to Chat GPT and try to create that person and get that advice from them. Just see where it takes you.

Vivian Ly:

Yeah, because that’s a free version right now. They’re actually building that out. Big creators and public figures are working to create essentially deep fakes of themselves based off of their expertise that you could pay to have access to.

That is the next version of the world that’s being built right here in New York City.

Tim O’Connor:

Vivian, all I can say is thank you so much for joining us today and sharing your wisdom because it is real. You have a lot to share in this area, and I think it’s going to help out a lot of people. So, thank you for joining us today.

Vivian Ly:

Of course. Thanks, Tim. Thanks, Adam.

Adam Pah:

Thank you, Vivian. It’s been great.

Tim O’Connor:

And Adam, my partner, always appreciate you and thank you for us together on this journey and trying to help people. Thank you all so much. And to everybody who has joined us today, we thank you for joining.

We hope it’s been helpful because, again, here at Kindrel Commons, we believe that AI is for everyone, and our intent is to show you real people like Vivian who are using it in ways to make her life better, easier, and a little more fun.