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Built This Week is a weekly podcast where real builders share what they're shipping, the AI tools they're trying, and the tech news that actually matters. Hosted by Sam and Jordan from Ryz Labs, the show offers a raw, inside look at building products in the AI era—no fluff, no performative hype, just honest takes and practical insights from the front lines.
What we built is a system we call Ryz Score. It takes the input of their application as well as their resume, and we actually score it.
Samuel Nadler:I've basically been using ChatGPT as a nutritionist. A lunch of 460 calories, Claude for financial services.
Jordan Metzner:This might totally change the way Wall Street stock market financial services are being used today.
Samuel Nadler:Companion with NSFW mode, how AI feel much more to some users like a emotional relationship.
BTW Theme Song:Built this week, breaking it down. Built this week, we show you how. A fresh idea, a clever tweak, you locked in. You built this week.
Samuel Nadler:Hey, everyone, and welcome to another episode of Built this Week, the podcast where we share what we're building, how we're building it, and what it means for the world of AI and startups. I'm Sam Nadler, cofounder and cohost here at Ryz Labs and Built This Week, and I'm joined by my friend, cohost, business partner, Jordan Metzner. How you doing today, Jordan?
Jordan Metzner:Hey, Sam. Great to be here. Excited for episode four.
Samuel Nadler:Yeah. I'm really excited about presenting what we've built recently. It's a tool called Ryz Score, and the reason I'm excited is because it's actually one of those tools that's had a huge impact on a large member of our, team. It's really accelerated their workflow and, you know, made us way, way, way more efficient. That's one of the biggest, topics we're gonna cover today.
Samuel Nadler:We're also gonna explore some maybe unusual ways we both use ChatGPT. It's not a new tool people haven't heard of, but it is, you know we I think we we use it in some ways that, you know, most people haven't even thought of. And then lastly, we've got, as always, every new week is is almost a crazy news week. So we got some some big AI headlines to cover this week. Anything top of mind before we bump jump into the tool?
Jordan Metzner:No. Just excited to chat about what we got to show today.
Samuel Nadler:Okay. Great. To to kick us off, let's go into Ryz Score. I'd love, you know, as always, for you to give me a quick product demo.
Jordan Metzner:Yeah. So let's talk about what Ryz Score is maybe before I just jump into it. But, you know, here at Rise Labs, we we have a staffing company, and we provide high quality developers and other technical roles to US based tech companies. And as part of that, we use an applicant tracking system. We use LinkedIn.
Jordan Metzner:We use a lot of different tools. But the problem we are faced is that when we post a new job, especially a job that's in a popular area, like maybe something like a software engineer or a marketing manager, we will get, you know, not five or 10 applications, but sometimes hundreds of applications. You know, to read each resume, you know, it's common that, you know, recruiters spend less than sixty seconds on a resume. You know, if you have a hundred hundred or 200 applicants, you could be spending two, three hundred minutes. Right?
Jordan Metzner:So, you know, it could take hours and hours just to review the resumes. You know, you have a human going through them. They start to get tired, lazy, or they miss some opportunity. And so what you have is someone who's basically kind of trying to find something in a large in a large haystack kinda thing. You know, they just don't do a great job of finding what are the best ones.
Jordan Metzner:And so, you know, what we realized was that AI is a great way to score resumes. And not just score resumes, but score resumes based on the job description. And so what we built was a thing we call Ryz Score. I'll jump into that now. You know, the UI is maybe not perfect, but maybe it it might be easier to see here in the white version.
Jordan Metzner:Basically, what you can see here is we have a bunch of jobs, all within the Ryz system. This is a data product manager. And for each of these jobs, we have a different number of candidates. Here, you can see personal assistant. We have a 112 applicants.
Jordan Metzner:And as we go down for each job, we have a different number of applicants just depending on where the job is, etcetera. Mhmm.
Samuel Nadler:Many of them over a 100 applicants. So, you know, that's a lot to process, especially if you're looking to move fast.
Jordan Metzner:Yeah. One you know, 53 here, one twelve here, 18 here, one fifteen here, 100 here, 55 here, fourteen, forty seven, you know, 43, 66, 69. So one fifty two. Right? A 152 Ruby on Rails developers.
Jordan Metzner:It becomes very difficult to understand, you know, who's highly qualified of these developers. And so, what we built is a system we call Ryz Score. So what Ryz Score does is it takes the input of their application as well as their resume, and we actually score it based on skills match, experience match, education match, and cultural fit. We bring all of these together, and we get an overall score of 90. Usually here, you can you can go directly to the resume or see any additional notes about the candidate.
Jordan Metzner:In this case, this candidate's in Las Vegas. This one is in Allen, Texas, and we can keep going down the list. If we were only looking for candidates that were, let's say, you know, in Austin, Texas or only in a certain area, then we could easily filter here, or we could type in a a specific location. We could also filter here by scores so we could get rid of the lower scores. You know?
Jordan Metzner:But, if we look at these candidates, you can see they've got from 80 all the way down. But as we start to score, you know, you hear we can see candidates who got maybe a 78 and then kinda keeps going all the way down the list till we have candidates with, you know, zeros and and even twenties and 30 fives who most likely probably won't be a good fit for that job. And if we dive deeper into each of these candidates, you know, we'd most likely see why, but it it most likely has to do with their resume and and the the resume's application to the job description at hand. What's really cool about all of this product is that most of our recruiters don't even use the Ryz Score application. What they actually use is our our applicant tracking system.
Jordan Metzner:And inside the applicant tracking system, we actually post all of these scores right back in for our recruiters. And so really simply, they can, they can go down the list and find the candidates who'd be most appropriate for the job. And then they can score them and reach out to them and save themselves a bunch of time and and basically send, you know, people in these lower scores kind of messages saying thank you, but, you know, you're you're not qualified for this role type of thing.
Samuel Nadler:Yeah. And that's really important because it's, like, kind of an elegant solution for our recruiters, not having to leave and go look at another tool to see who were the who which candidates have the the best resumes. It's all integrated. They see the score directly in our applicant tracking system and then can immediately move, you know, those those top candidates directly onto the next step. And we did a lot of testing to verify, you know, does a 92 or a 90 feel like a 92 and a 90 before, like, you know, put putting more trust into the system.
Samuel Nadler:And but for the most part, like, they can you know, it it doesn't feel like we're missing candidates as much. Feels like, you know, we're truly moving the top cohort through onto the next step. And, you know, in many ways, it's it's a while they don't see this, it's a better experience for the candidates too. Because, you know, if you get hundreds of applicants and, you know, a recruiter's manually checking every resume, you know, they could just move, you know, what they get to in that day forward versus, you know, there could be a rock star candidate who's the very last on the list. And it just you know, by that by the time we get to them, you know, maybe the process is towards the the ending stages for that that kind of first cohort.
Samuel Nadler:So it's been a huge accelerant to our recruiting process in in in the top top of funnel and just getting candidates to the next step quickly.
Jordan Metzner:Yeah. Absolutely. And here you can see inside our applicant tracking system, you know, this candidate has a 90, and you can see the candidate demonstrates strong alignment with personal assistant role. And they have extensive experience in relationship management, travel planning, gift research, personal support in remote and dynamic environments, bilingual fluency, high attention to detail, empathetic communication skills. So, you know, many many of these factors here just make it really easy for recruiter to jump in here.
Jordan Metzner:And then, of course, they could click on the Ryz Score link and and and get right back to this page as well.
Samuel Nadler:Amazing. How was it built? Like, what tools are you using?
Jordan Metzner:You know, front end is built in, Vite, React, Tailwind, Shade CN. That's kind of what we use all the time around here. But I think I built most of this in Cursor. I mostly used Cursor. I used Supabase, actually, for authentication and authorization, and all of this data is stored inside of Supabase.
Jordan Metzner:And then we use Supabase edge functions to check whether or not we have a new candidate in the pipeline. And then from those from those edge functions, we then send that data into ChatGPT with a scoring matrix as well as the job description and their resume and full application. Then we get the score back, and we post that into our application. And then, all the way into, our applicant tracking system, just like I mentioned.
Samuel Nadler:Great. Great. Okay. I love it. Our team loves it.
Samuel Nadler:It's had a huge impact, on on their day to day and just moving faster and speeds, you know, always important.
Jordan Metzner:It it's almost surprising to me that we haven't seen more integration of AI resume scoring, especially in areas or places like LinkedIn or inside the applicant tracking system that we use or others yet. I do think this will become more and more commonplace, the scoring, of course, will get better. But it seems almost inevitable that every resume will get scored almost immediately for almost any job you apply to in the future. It seems like that time is pretty imminent.
Samuel Nadler:Alright. Let's move on to our next segment where we typically cover a tool of the week, and it's, you know, usually a lesser known tool that that maybe people are unaware of. But this week, we're covering, ChatGPT, but we're covering maybe less common use cases for ChatGPT. And, you know, for me, I'll jump into how I have a a less common use case, and and I've started it fairly recently for the, like, the last couple weeks, and it's actually had a pretty positive impact on me. I've basically been using ChatGPT as a nutritionist, and I've gone through phases of using different mobile apps to track calories or track macros.
Samuel Nadler:And, you know, historically speaking, I'll do it for a period of time and then, you know, kind of stop and then do it again and then stop. One of the apps I've used the most is MyFitnessPal just to track calories, and, you know, it's for the most part, does its job. It took a while to kind of input exactly 1.5 cups of rice, you know, what I think is five ounces of grilled chicken. So it's it's a little bit more you know, it wasn't horrible, a bit more cumbersome. But, you know, since the July, I've basically been using a thread on OpenAI to to track my calorie intake and macros, and it's been super simple.
Samuel Nadler:I just voice noted in every time I eat something, or I just take a picture of the product. Doesn't even have to be the barcode. It pulls up the exact calorie count, the exact amount of proteins, carbs, fats, whatever. But it also will give me tips on what I can eat later in the day if I'm trying to hit my calorie and macro account. So, yeah, I mean, several times, it's just been as easy to upload a picture, give it a little bit of context in a voice note, and it will, you know, to say, hey.
Samuel Nadler:Roughly, this is a lunch of 460 calories, you know, 42 grams of protein, 57 grams of carbs, which is largely the rice, eight grams. You know, I've done just normal. Here's my final update for Thursday, July 10. It gives me all kind of a summary. Calories, I had a big deficit that day.
Samuel Nadler:Net calories was strong. Protein, I could've always, always, always could eat more protein. Fat was low. This is one of my better days. I've had some worse
Jordan Metzner:things where I
Samuel Nadler:had, you know, takeout
Jordan Metzner:Some ice cream. Some
Samuel Nadler:ice cream, pineapple dessert here. This was I I wanted to eat dessert, I think, here, and it said, you know, some smart dessert options, you know, whey protein mousse, ratio yogurt plus berries. This is all things I have too. It began to learn things that I, like, usually I'm eating and suggesting it. And, you know, I asked a stupid question.
Samuel Nadler:Can I eat some pineapple for dessert? Yes. Of course. You know, one thing I have noticed, it will
Jordan Metzner:it will May I have may I have some pineapple, please?
Samuel Nadler:It will and here's another picture of of dinner I had with just with a quick voice note. And, you know, for the most part, I think it captures everything. You know? Here's from the picture, zucchini, carrots, red onion, mushrooms, broccoli. You know?
Samuel Nadler:And, a, it's pretty easy just to do this on mobile. I don't have to pay anything for the for the macro counter. And, you know, one thing I have noticed that I think is pretty funny, it will never tell me no even when I'm like, yeah. I kinda want some ice cream. It's like, well, you know, you can eat some ice cream.
Jordan Metzner:Yeah. You probably shouldn't, but go for it.
Samuel Nadler:But I think, you know, if you know, obviously, MyFitnessPal is has been really impactful for some people to count their calories. And I there are times when I I'm more fitness or or dietary focused, I do wanna count my calories. I do wanna track my macros. There are times when I'm not, but it's just one use case that I thought was pretty impressive. Could you take this out of ChatGPT?
Samuel Nadler:Probably. I just don't see the need to. Could you build your, like, your own custom little Personal
Jordan Metzner:nutritionist. Yeah.
Samuel Nadler:Yeah. But, you know, I keep it within a project. It, like, knows my history, and, you know, that I don't really see any need to. I'm not looking to, like, commercialize it.
Jordan Metzner:I mean, that's interesting because it makes, like, you know, One ChatGPT conversation is like a mini application. Right? And now it's not a conversation to you anymore. It's actually like a full on end to end application. It just sits inside a conversation layer, which I think is, you know, really interesting because now you kinda wanna pull it out.
Jordan Metzner:And Chatzpedi can maybe figure out that you're kind of using it as an application and maybe wrap some some nicer UI around it or maybe better accessibility, like a website link or something.
Samuel Nadler:Exact yeah. That could be interesting. Could I could I pull out the conversation to be a direct link on my phone? I mean, it's usually one of the top projects, top conversations in my thread just because I've been updating it a lot. But yeah.
Samuel Nadler:And then one other use case that I thought was kind of interesting, I had two plants, same type of plants. One was dying, one was not on my patio. Couple pictures of the the plant that was struggling. ChatGPT gave me some quick fixes. I did those, and, you know, a lot of it one, a lot of it had to do with kind of sunlight, watering, frequency, how much water, etcetera.
Samuel Nadler:But the the the challenge for me was I had two exact plans that were about 10 feet apart. One was thriving. One was struggling. I thought I was kind of, you know, taking care of them in a very similar way, but with few changes, some pictures, and knew obviously knew exactly what the plant was. It, you know, seemed to identify what the problem was, adjusted those.
Samuel Nadler:And, you know, about a week later, both plants seem to be thriving. So it's another kind of interesting use case.
Jordan Metzner:Awesome. Yeah. I have a few, like, interesting ones. Just the other day, I was at my cousin's restaurant. We wanted to make a digital menu, and I just took some pictures of the menu and then, like, the available food they had.
Jordan Metzner:And they had some menus on the wall for specials and the chalkboard, and I just threw it all into ChatGPT, and it built me, like, a digital menu that I could then serve up to him. So
Samuel Nadler:Very cool. Okay. Let's jump into the news. I think there is a few articles we wanted to cover today, starting with Claude for financial services. I know you're passionate about this one.
Samuel Nadler:Hey. What does it mean? I haven't even read this yet. I know it came out yesterday, I believe.
Jordan Metzner:Yeah. Well, I mean, financial services in The United States is, like, one of the largest industries in the entire country. You know, almost every retiree is invested in the stock market. And, historically, kind of most of the financial data has been served up to financial firms via Bloomberg. And, you know, that's made Bloomberg a billionaire.
Jordan Metzner:But if you ever use Bloomberg, it it's famously known as the Bloomberg terminal, which means it uses a terminal type interface, which is, you know, historically not very friendly to users. You know, users end up becoming memorization of keyboard shortcuts in order to get certain things done. It has its own chat features so, you know, traders can talk to each other. But overall, it's a kind of pretty old and clunky interface. I believe it's still written in kind of Cobalt and uses some pretty old programmatic languages.
Jordan Metzner:And so, you know, I think Perplexity is probably the first one who's really started to step up their game as far as, like, financial research goes. But I I think this is a huge opportunity for for multiple companies to go after, the monopoly of of Bloomberg in the financial services space. And, you know, here, you can see Claude is kind of going into that space and probably, you know, trying to get a lot of data so you can, you know, quickly hear look. It's it's doing charts and graphs. And, you know, you know, I I think the LLMs are gonna have a huge upside leverage against, you know, the historicals of of Bloomberg in the space.
Jordan Metzner:And I think this might totally change the way, you know, Wall Street stock market financial services are being used today and and how they do analysis. So, you know, here, you can see it's already integrated with a lot of third party service providers, S and P Global, etcetera. But I think we're gonna continue to see the the degradation of Bloomberg Terminal's value and and increase increase value in in using LLMs for financial analysis.
Samuel Nadler:Yeah. I mean, even I I know this is for enterprises, financial services enterprises, but, I mean, I use AI to analyze kind of my own investment decisions, my own brokerage accounts, and, you know, my my strategy at the at at the age I'm in, or the age I am. You know, do you see this obviously having an impact on personal investment decisions?
Jordan Metzner:Yeah. Most likely. I mean, I usually do that as well, especially when I'm looking at an option trade. So, you know, I'll take an option trade and, you know, there's a there's, you know, there's all the Greeks on top of that. Right?
Jordan Metzner:So I'll just upload an option trade with the prices and the Greeks on there. I'll usually tell something like ChatGPT, like, hey. I think the price is gonna go to here by this time. You know, if I buy a, you know, a a $1,100 contract kind of, you know, what would I expect to return? What would be my IRR?
Jordan Metzner:And, you know, what would that alternative be? You know, I think you and I were just discussing the other day about, you know, the cost of buying Bitcoin versus buying iBit, you know, the ETF for Bitcoin. And, I did some analysis. I need to do some more analysis. But in the first year, iBit is actually significantly cheaper than than using something like Coinbase one to to purchase Bitcoin because they only charge point two five while Coinbase's fees are somewhere between the one to 3% when it all gets added up.
Jordan Metzner:So, you know, I do need to do further analysis there. But, yeah, that's just another way where, you know, we're looking at how, you know, making financial decisions and the impact on on my own personal portfolio and just using ChatGPT to help me. So I don't know. Yeah. Same for you?
Samuel Nadler:Yeah. Abs I mean, I you turned me on to using it more for a holistic view of my financial financial outlook. I would say, generally speaking, it, like, tried to push me into a more conservative approach, which, I'm not really ready to do quite yet. But, I mean, just, you know, having played around with it, you know, it it seemed, it seemed like everyone should move towards, like, analyzing their portfolio and each individual investment they make. Not saying there's there's no there's not gonna be importance of professional financial services for for people like you and me, but it just again, it's like I can do so much more or have access to so much more information or approaches than I would have had a couple years ago.
Jordan Metzner:Yeah. I mean, I think, you know, we're both in our forties, and I think something I think about a lot is, you know, will I have enough money for retirement? Am I saving enough? Well, you know, will I have enough money to spend how I wanna spend when I'm in retirement? And, you know, I think a lot of people rely on r a RIAs, you know, retirement professionals, financial advisers so that they can get those types of answers because it feels good when someone else tells you.
Jordan Metzner:Right? It it it you know, when you calculate the numbers yourself, you might have some, you know, some some some belief that they're accurate. But, you know, when other people tell you, especially when they say they're an expert in the space, it definitely gives you some confidence or maybe lack thereof confidence. So for me, I found it super interesting that I was able to put in, you know, my IRA and my stock market portfolio and everything I have and my my plans for retirement, my goals, my age, etcetera, and kinda get a much better holistic analysis of of where I'll be and, you know, how far close I am away to to kinda hit my retirement goals.
Samuel Nadler:The next story I think we're gonna cover is the OpenAI to take a cut of shopping sales. You know, from a personal point of view, again, I use ChatGPT to analyze different shopping trade offs. I just purchased on Prime Day a pool vacuum. It's the second pool vacuum I've purchased. The reason I want to use ChatGPT is the first pool vacuum I purchased died in one season, and I really want to avoid that.
Samuel Nadler:I also, you know, am somewhat budget conscious. So, like, you know, I didn't wanna spend an exorbitant amount on a pool vacuum. I want something within my budget that ideally would last multiple seasons. And at the end of the day, like, it highly informed my decision. I went with the decision, you know, after, you know, sorting through several options.
Samuel Nadler:You know, what do you think of this news of taking a a cut of shopping sales?
Jordan Metzner:Well, yeah. I mean, this is just more of kind of taking over some of the Google pie. Right? You know, you search on Google, like, you want something, you have Google Shopping, you have all those leads on top. Right?
Jordan Metzner:You've got, you know, Amazon and top search results kind of trying to use SEO like we talked about, you know, in a previous episode, you know, to use SEO to try to drive traffic into the site. But what happens when the customer never goes to Google? Right? And the customer starts their their search journey on top of ChatGPT. Well, ChatGPT you is gonna wanna take some of that affiliate, and that's looks like what they're gonna they're gonna be doing.
Jordan Metzner:And, honestly, I mean, I think there's there's a huge impact. I mean, this could have a big impact on on Amazon, on Amazon ads, on Google, on Google Shopping ads, and most likely also, you know, probably have a pretty big impact on Shopify. Hard to say whether that could be positive or negative. But, you know, if Shopify does a good job integrating it to ChatGPT, maybe it could be positive in in driving additional traffic up to Shopify, you know, or it could be negative in that, you know, people don't need these Shopify websites in order to sell things on the Internet. They just need a a landing page or something that, you know, ChatGPT can check out of.
Jordan Metzner:So, yeah. You know, I think this is an another new paradigm of how people are purchasing products and how they're shopping online. And I think this is, again, just the beginning. You know, there's there's been so much content historically created about, you know, the best, you know, the best headphones for this year or the best umbrella, you know, for this season or, you know, the best backpack to wear in the rain or whatnot. Right?
Jordan Metzner:And there's, you know, New York Times, who knows what they spent on the wire cutter to have all these, like, you know, listicles. And, you know, we remember BuzzFeed with all their listicles, etcetera. But what happens when, you know, these LLMs are able to actually give you true analysis based on, you know, the top 10, what's import most important to you, not what's most important to everybody in general? Because, you know, some things may not even be relevant to you based on where you live or how you like to act or what, you know, what your interests are. And so, yeah, personalized shopping with direct links for checkout sound like a huge opportunity and a step forward.
Jordan Metzner:But, yeah, maybe we're even gonna see, you know, ChatGPT with, you know, full checkout buttons, and you they got your credit card stored and, you know, just press the buy button. Even easier, you see the whole checkout happen all the way through through ChatGPT. So, yeah, and, you know, if ChatGPT is the player who's who's driving who's driving those purchases, obviously, that that becomes a huge economic fountain for them. So, yeah, let's let's just do, one more real quick because I think I think it's a little interesting as well and just talk about Elon. I mean, it seems like he's in the news every week.
Jordan Metzner:So, yeah, you wanna kick this one off a little bit?
Samuel Nadler:Yeah. This companion with NSFW mode, I think it's just, you know, another piece of news about how AI is, you know, becoming much more feel much more to some users like a, like, an emotional relationship. There was a segment, I believe, on CBS Sunday mornings recently about a gentleman who was married, had kids, but, you know, seemed to have a deep emotional connection with ChatGPT. There's this article. I think this is one of the bigger concerns I have with AI is, you know and maybe maybe there's some benefits to it.
Samuel Nadler:But do do people feel are people getting too close to these AI personalities and and will no longer, you know, engage as much in real life relationships. And then in SFW mode, I mean, I'm, you know, I'm these things tend to happen very quickly, and I'm I guess I'm not surprised. But, yeah, I do think there are some concerns for people who may who may be introverts, who may tend to shy away from social social events or interactions, and does this have a a negative impact on society or for those types of individuals in the future?
Jordan Metzner:Yeah. Or does it have a positive impact on loneliness and, you know, people who are alone and find this as a way to find, you know, companionship and happiness? It's, you know, it's like the Internet, you know, good and bad coming at the same time. I just I mean, it's hilarious. It's hilarious to me that, like, you know, Elon launches a new model, the first thing he does is launch a not safe for work companion mode, you know, rather than solving, you know, real world issues.
Jordan Metzner:But I did see kind of Grok at the same time as announcing this also just signed a deal with the Department of Defense. So, you know, it seems like they're trying to hit on all angles. You know, I I think the Grok four announcement was pretty impressive as far as its performance goes. It seems like, you know, they did probably cut some corners as far as safety as we've seen with some of these, you know, funny responses on Twitter and whatnot. But, hopefully, over time, those things will get solved and smoothed out.
Jordan Metzner:And, you know, I think competition is good for the game. You know? I I think we've almost, like, kind of decided, like, Jet GPT is the winner for most things, and Claude is the winner for code. And that seemed like that was almost it for a little while. And then, you know, Gemini started to come back, and now Grok is starting to come back.
Jordan Metzner:And I just saw, yeah, Meta, obviously, you know, invest big investment spend. I just saw Mistral launched a new, text to speech model that beats ChatGPT. So, you know, this is this is yeah. Yeah. Amazon's new coding agent.
Jordan Metzner:You know? So it seems like this is a war. It's not gonna slow down. And the winner is the developer. At least, you know, right now, the winner is the developer, the builder, the you know, you and me, the ones who get to sit down and use these tools every day because, you know, for for only a few dollars, you get access to these very, very expensive models and these very expensive chips that are, you know, helping you process and write a lot of code.
Jordan Metzner:And, yeah. I mean, who knows what's gonna come next week? Who knows when, you know, GPT five or whoever is gonna, you know you know, go above the the current best model. But, you know, once that happens, we'll see another, you know, form function change of kind of what these models can do and how helpful they'll be. And, yeah, I think that's exciting.
Jordan Metzner:Exciting for me as a builder and as a developer.
Samuel Nadler:Yeah. My final thought on this companion mode is I think it's easy to immediately point out the negatives. However, you know, you and I are somewhat familiar with one of our businesses about senior loneliness and its impact on health. It's like it's a really important problem where as as seniors get older and older, they get more lonelier and lonelier and lonelier, and it has really adverse health effects. And maybe a senior companion mode, obviously, you know, not in SFW, but senior companion mode could help alleviate some of those feelings of loneliness and, you know, drive better health outcomes.
Samuel Nadler:So there's always kinda two sides to the coin and, you know, to be determined if seniors will use AI in that way or who knows. But, you know, just something that popped up while we were discussing this.
Jordan Metzner:Yeah. It just feels like, you know, maybe Alexa came a little too early. I mean, I think we saw the first Alexa in, like, 2014 or 2015. You know, she really never got very intelligent or very smart or very companion like, but now we're starting to see kind of v two, v three of these kind of companions, and, you know, hopefully, we'll get a lot more value out of them.
Samuel Nadler:Alright, Jordan. Well, thanks for the time, and we'll talk again next week.
Jordan Metzner:Thanks, Sam. This was an awesome episode. Really cool to chat about all these things, and see everyone next week. Don't forget to like and subscribe. Thanks, everyone.
Jordan Metzner:Enjoy Built This Week. See you soon.