0:00Jordan Metzner says Ryz Score takes a candidate's application and resume and scores them. Sam Nadler says the tool has had a big impact on the recruiting team, accelerating their workflow and making them more efficient.
2:13Jordan Metzner says popular job posts can draw hundreds of applications, recruiters often spend under 60 seconds per resume, and tired reviewers miss good candidates, so Ryz Labs built Ryz Score to score resumes against the job description.
4:23Jordan Metzner says Ryz Score rates skills, experience, education and cultural fit into an overall score posted into the applicant tracking system. Sam Nadler says the team tested whether scores felt right, and strong candidates at the bottom of the list no longer wait.
8:22Jordan Metzner says he built it mostly in Cursor with Vite, React, Tailwind and shadcn, using Supabase for auth and data; Supabase edge functions send new candidates to ChatGPT with a scoring matrix, job description and resume.
9:54Sam Nadler says he replaced MyFitnessPal with a ChatGPT project: he sends a voice note or photo of each meal and it returns calories, protein, carbs and fat, gives daily summaries and suggests what to eat later.
15:16Sam Nadler says ChatGPT identified why one of two identical plants was struggling and both were thriving a week later. Jordan Metzner says he photographed his cousin's restaurant menus and chalkboard specials and ChatGPT built a digital menu.
16:39Jordan Metzner says the Bloomberg Terminal has an old, clunky interface, and with Claude for Financial Services integrating providers like S&P Global, he expects LLMs to erode the terminal's value for financial analysis.
18:45Jordan Metzner says he uploads option trades with prices and Greeks to ChatGPT to estimate returns, and gave it his IRA, portfolio, age and goals for a retirement analysis. Sam Nadler says it pushed him toward a more conservative approach.
22:19Jordan Metzner says ChatGPT taking affiliate revenue cuts into Google's pie and could affect Amazon ads, Google Shopping and Shopify, while personalized shopping with direct checkout links replaces listicles like Wirecutter.
26:00Sam Nadler worries people may get too close to AI personalities, but says a senior companion mode could ease loneliness. Jordan Metzner says it may help with loneliness and notes Grok also signed a Department of Defense deal.
AI Resume Screening: How We Score Applicants with ChatGPT: the key questions from this episode, answered with quotes and timestamps.
Jordan Metzner [0:00]: 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.
Sam Nadler [0:09]: I've basically been using ChatGPT as a nutritionist. A lunch of 460 calories, Claude for financial services.
Jordan Metzner [0:18]: This might totally change the way Wall Street stock market financial services are being used today.
Sam Nadler [0:24]: Companion with NSFW mode, how AI feel much more to some users like a emotional relationship.
[0:38] 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.
Sam Nadler [0:48]: 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 [1:10]: Hey, Sam. Great to be here. Excited for episode four.
Sam Nadler [1:13]: 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, made us way more efficient. That's one of the biggest, topics we're gonna cover today. 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 use it in some ways that, 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 big AI headlines to cover this week. Anything top of mind before we bump jump into the tool?
Jordan Metzner [2:10]: No. Just excited to chat about what we got to show today.
Sam Nadler [2:13]: Okay. Great. To kick us off, let's go into Ryz Score. I'd love, as always, for you to give me a quick product demo.
Jordan Metzner [2:21]: Yeah. So let's talk about what Ryz Score is maybe before I just jump into it. But, here at Ryz Labs, 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. 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, not five or 10 applications, but sometimes hundreds of applications. To read each resume, it's common that, recruiters spend less than sixty seconds on a resume. If you have a hundred or 200 applicants, you could be spending two, three hundred minutes. Right? So, it could take hours and hours just to review the resumes. 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 haystack kinda thing. They just don't do a great job of finding what are the best ones.
Jordan Metzner [3:23]: And so, 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. The UI is maybe not perfect, but maybe it might be easier to see here in the white version. 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. And as we go down for each job, we have a different number of applicants just depending on where the job is, etcetera. Mhmm.
Sam Nadler [3:59]: Many of them over a 100 applicants. So, that's a lot to process, especially if you're looking to move fast.
Jordan Metzner [4:07]: Yeah. One you know, 53 here, one twelve here, 18 here, one fifteen here, 100 here, 55 here, fourteen, forty seven, 43, 66, 69. So one fifty two. Right? A 152 Ruby on Rails developers. It becomes very difficult to understand, 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 go directly to the resume or see any additional notes about the candidate. 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, in Austin, Texas or only in a certain area, then we could easily filter here, or we could type in a specific location. We could also filter here by scores so we could get rid of the lower scores. You know?
Jordan Metzner [5:11]: 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 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, zeros 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, we'd most likely see why, but it most likely has to do with their resume and 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 applicant tracking system. 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 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 basically send, people in these lower scores kind of messages saying thank you, but, you're you're not qualified for this role type of thing.
Sam Nadler [6:17]: 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 best resumes. It's all integrated. They see the score directly in our applicant tracking system and then can immediately move, those top candidates directly onto the next step. And we did a lot of testing to verify, does a 92 or a 90 feel like a 92 and a 90 before, like, put putting more trust into the system. And but for the most part, like, they can you know, it doesn't feel like we're missing candidates as much. Feels like, we're truly moving the top cohort through onto the next step. And, in many ways, it's it's a while they don't see this, it's a better experience for the candidates too. Because, if you get hundreds of applicants and, a recruiter's manually checking every resume, they could just move, what they get to in that day forward versus, 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, maybe the process is towards the ending stages for that that kind of first cohort.
Sam Nadler [7:37]: So it's been a huge accelerant to our recruiting process in the top of funnel and just getting candidates to the next step quickly.
Jordan Metzner [7:50]: Yeah. Absolutely. And here you can see inside our applicant tracking system, 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, many many of these factors here just make it really easy for recruiter to jump in here. And then, of course, they could click on the Ryz Score link and get right back to this page as well.
Sam Nadler [8:21]: Amazing. How was it built? Like, what tools are you using?
Jordan Metzner [8:24]: Front end is built in, Vite, React, Tailwind, shadcn. 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. And then we use Supabase edge functions to check whether or not we have a new candidate in the pipeline. And then 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.
Sam Nadler [9:16]: Great. Great. Okay. I love it. Our team loves it. It's had a huge impact, on their day to day and just moving faster and speeds, always important.
Jordan Metzner [9:28]: 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.
Sam Nadler [9:54]: Alright. Let's move on to our next segment where we typically cover a tool of the week, and it's, 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, for me, I'll jump into how I have a less common use case, 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. And, historically speaking, I'll do it for a period of time and then, 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, it's for the most part, does its job. It took a while to kind of input exactly 1.5 cups of rice, 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, since the July, I've basically been using a thread on OpenAI to track my calorie intake and macros, and it's been super simple.
Sam Nadler [11:30]: 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, to say, hey. Roughly, this is a lunch of 460 calories, 42 grams of protein, 57 grams of carbs, which is largely the rice, eight grams. 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. Net calories was strong. Protein, I could've always could eat more protein. Fat was low. This is one of my better days. I've had some worse Things where I
Sam Nadler [12:40]: Had, takeout
Jordan Metzner [12:43]: Some ice cream.
Sam Nadler [12:45]: Some ice cream, pineapple dessert here. This was I wanted to eat dessert, I think, here, and it said, some smart dessert options, 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, I asked a stupid question. Can I eat some pineapple for dessert? Yes. Of course. One thing I have noticed, it will
Jordan Metzner [13:16]: May I have some pineapple, please?
Sam Nadler [13:19]: It will and here's another picture of dinner I had with just with a quick voice note. And, for the most part, I think it captures everything. You know? Here's from the picture, zucchini, carrots, red onion, mushrooms, broccoli. You know? And, a, it's pretty easy just to do this on mobile. I don't have to pay anything for the macro counter. And, 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 can eat some ice cream.
Jordan Metzner [13:52]: Yeah. You probably shouldn't, but go for it.
Sam Nadler [13:55]: But I think, if you know, obviously, MyFitnessPal is has been really impactful for some people to count their calories. And I there are times when I'm more fitness 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? Probably. I just don't see the need to. Could you build your, like, your own custom little Personal
Jordan Metzner [14:26]: Nutritionist. Yeah.
Sam Nadler [14:27]: Yeah. But, I keep it within a project. It, like, knows my history, and, that I don't really see any need to. I'm not looking to, like, commercialize it.
Jordan Metzner [14:37]: I mean, that's interesting because it makes, like, 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, really interesting because now you kinda wanna pull it out. And ChatGPT can maybe figure out that you're kind of using it as an application and maybe wrap some nicer UI around it or maybe better accessibility, like a website link or something.
Sam Nadler [15:03]: Exact yeah. That could be interesting. 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. 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 plant that was struggling. ChatGPT gave me some quick fixes. I did those, and, a lot of it one, a lot of it had to do with kind of sunlight, watering, frequency, how much water, etcetera. But 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, 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, seemed to identify what the problem was, adjusted those.
Sam Nadler [16:07]: And, about a week later, both plants seem to be thriving. So it's another kind of interesting use case.
Jordan Metzner [16:14]: 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. 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
Sam Nadler [16:39]: 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. Hey. What does it mean? I haven't even read this yet. I know it came out yesterday, I believe.
Jordan Metzner [16:55]: Yeah. Well, I mean, financial services in The United States is, like, one of the largest industries in the entire country. 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, that's made Bloomberg a billionaire. But if you ever use Bloomberg, it's famously known as the Bloomberg terminal, which means it uses a terminal type interface, which is, historically not very friendly to users. Users end up becoming memorization of keyboard shortcuts in order to get certain things done. It has its own chat features so, 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 COBOL and uses some pretty old programmatic languages. And so, 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 think this is a huge opportunity for multiple companies to go after, the monopoly of Bloomberg in the financial services space. And, here, you can see Claude is kind of going into that space and probably, trying to get a lot of data so you can, quickly hear look. It's it's doing charts and graphs. And, you know, I think the LLMs are gonna have a huge upside leverage against, the historicals of Bloomberg in the space.
Jordan Metzner [18:18]: And I think this might totally change the way, Wall Street stock market financial services are being used today and how they do analysis. So, here, you can see it's already integrated with a lot of third party service providers, S&P Global, etcetera. But I think we're gonna continue to see the degradation of Bloomberg Terminal's value and increase value in using LLMs for financial analysis.
Sam Nadler [18:45]: Yeah. I mean, even 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, my strategy at the age I'm in, or the age I am. Do you see this obviously having an impact on personal investment decisions?
Jordan Metzner [19:14]: Yeah. Most likely. I mean, I usually do that as well, especially when I'm looking at an option trade. So, I'll take an option trade and, there's a there's, there's all the Greeks on top of that. Right? 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. If I buy a $1,100 contract kind of, what would I expect to return? What would be my IRR? And, what would that alternative be? I think you and I were just discussing the other day about, the cost of buying Bitcoin versus buying IBIT, 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 using something like Coinbase one 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 [20:10]: So, I do need to do further analysis there. But, yeah, that's just another way where, we're looking at how, making financial decisions and the impact on my own personal portfolio and just using ChatGPT to help me. So I don't know. Yeah. Same for you?
Sam Nadler [20:26]: Yeah. Abs I mean, I you turned me on to using it more for a holistic view of my 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, having played around with 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 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 [21:24]: Yeah. I mean, I think, we're both in our forties, and I think something I think about a lot is, will I have enough money for retirement? Am I saving enough? Well, will I have enough money to spend how I wanna spend when I'm in retirement? And, I think a lot of people rely on r a RIAs, retirement professionals, financial advisers so that they can get those types of answers because it feels good when someone else tells you. Right? It you know, when you calculate the numbers yourself, you might have some belief that they're accurate. But, 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, my IRA and my stock market portfolio and everything I have and my plans for retirement, my goals, my age, etcetera, and kinda get a much better holistic analysis of where I'll be and, how far close I am away to kinda hit my retirement goals.
Sam Nadler [22:19]: The next story I think we're gonna cover is the OpenAI to take a cut of shopping sales. 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. I also, am somewhat budget conscious. So, like, 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, after, sorting through several options. What do you think of this news of taking a cut of shopping sales?
Jordan Metzner [23:18]: Well, yeah. I mean, this is just more of kind of taking over some of the Google pie. Right? You search on Google, like, you want something, you have Google Shopping, you have all those leads on top. Right? You've got, Amazon and top search results kind of trying to use SEO like we talked about, in a previous episode, 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 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 be doing. And, honestly, I mean, I think there's there's a huge impact. I mean, this could have a big impact on Amazon ads, on Google Shopping ads, and most likely also, probably have a pretty big impact on Shopify. Hard to say whether that could be positive or negative. But, if Shopify does a good job integrating it to ChatGPT, maybe it could be positive in driving additional traffic up to Shopify, or it could be negative in that, people don't need these Shopify websites in order to sell things on the Internet. They just need a landing page or something that, ChatGPT can check out of.
Jordan Metzner [24:27]: So, yeah. 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. There's there's been so much content historically created about, the best headphones for this year or the best umbrella, for this season or, the best backpack to wear in the rain or whatnot. Right? And there's, New York Times, who knows what they spent on Wirecutter to have all these, like, listicles. And, we remember BuzzFeed with all their listicles, etcetera. But what happens when, these LLMs are able to actually give you true analysis based on, the top 10, what's import most important to you, not what's most important to everybody in general? Because, some things may not even be relevant to you based on where you live or how you like to act or 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 [25:24]: But, yeah, maybe we're even gonna see, ChatGPT with, full checkout buttons, and you they got your credit card stored and, just press the buy button. Even easier, you see the whole checkout happen all the way through ChatGPT. So, yeah, and, if ChatGPT is the player who's 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 it's a little interesting as well and just talk about Elon. I mean, it seems like he's in the news every week. So, yeah, you wanna kick this one off a little bit?
Sam Nadler [26:00]: Yeah. This companion with NSFW mode, I think it's just, another piece of news about how AI is, 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, 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 there's some benefits to it. But do do people feel are people getting too close to these AI personalities and will no longer, engage as much in real life relationships. And then NSFW mode, I mean, I'm, 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 be introverts, who may tend to shy away from social events or interactions, and does this have a negative impact on society or for those types of individuals in the future?
Jordan Metzner [27:32]: Yeah. Or does it have a positive impact on loneliness and, people who are alone and find this as a way to find, companionship and happiness? It's, it's like the Internet, good and bad coming at the same time. I just I mean, it's hilarious to me that, like, Elon launches a new model, the first thing he does is launch a not safe for work companion mode, rather than solving, real world issues. 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, it seems like they're trying to hit on all angles. I think the Grok four announcement was pretty impressive as far as its performance goes. It seems like, they did probably cut some corners as far as safety as we've seen with some of these, funny responses on Twitter and whatnot. But, hopefully, over time, those things will get solved and smoothed out. And, I think competition is good for the game. You know? I think we've almost, like, kind of decided, like, ChatGPT 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, Gemini started to come back, and now Grok is starting to come back.
Jordan Metzner [28:40]: And I just saw, yeah, Meta, obviously, invest big investment spend. I just saw Mistral launched a new, text to speech model that beats ChatGPT. So, this is yeah. Yeah. Amazon's new coding agent. You know? So it seems like this is a war. It's not gonna slow down. And the winner is the developer. At least, 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, for only a few dollars, you get access to these very, very expensive models and these very expensive chips that are, helping you process and write a lot of code. And, yeah. I mean, who knows what's gonna come next week? Who knows when, GPT five or whoever is gonna, you know, go above the current best model. But, once that happens, we'll see another, 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 [29:37]: Exciting for me as a builder and as a developer.
Sam Nadler [29:39]: Yeah. My final thought on this companion mode is I think it's easy to immediately point out the negatives. However, 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 seniors get older and older, they get more lonelier and lonelier, and it has really adverse health effects. And maybe a senior companion mode, obviously, not NSFW, but senior companion mode could help alleviate some of those feelings of loneliness and, drive better health outcomes. So there's always kinda two sides to the coin and, to be determined if seniors will use AI in that way or who knows. But, just something that popped up while we were discussing this.
Jordan Metzner [30:35]: Yeah. It just feels like, maybe Alexa came a little too early. I mean, I think we saw the first Alexa in, like, 2014 or 2015. 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, hopefully, we'll get a lot more value out of them.
Sam Nadler [30:53]: Alright, Jordan. Well, thanks for the time, and we'll talk again next week.
Jordan Metzner [30:57]: 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. Enjoy Built This Week. See you soon.
