Parents Are Scared of AI. Nobody's Warning Them About This (Degree Free #206)

Ryan Maruyama [00:00:00]:
Welcome back. Let's kick it off strong. Gen Z blames AI for the job market. Well, Gen Z college grads.

Hannah Maruyama [00:00:08]:
It's always the robots. It's never the paper. Now, underemployment for recent grads hit 42.5%. So we're basically talking about half of grads are underemployed. This is now the highest percentage since 2020. And this is very important because many of these underemployed grads will still be underemployed 10 years later. This, I think, is a really good example too of how strategic entry-level work is incredibly important and that if your child goes to college, it is more difficult for them to get that strategic entry-level work because so many people are not wanting to hire Gen Z grads. Again, we talk about intelligent.com survey that really tells a lot about where hiring managers are at mentally, and then also managers just as far as who they're looking for, who they're gonna hire.

Hannah Maruyama [00:00:53]:
A lot of it is because grads are just really high risk because they are way more likely to turn and they expect way higher than their skillset. They expect to earn way higher than their skillset, which Which, to be perfectly frank, is very little when you come out of college. It's very little to none. Many undergrads don't work while they're in college. So the reason that this matters so much, and again, I know this is an unpopular point to make, but the underemployment numbers didn't really move after the AI tools came on the scene. This was already a problem and it's still a problem, and it really hasn't been that dramatically impacted by AI. And this is one of those things where I think this is inconvenient. This is very much inconvenient for the colleges because they love to blame the robots because honestly, they're terrified of AI.

Hannah Maruyama [00:01:38]:
Colleges are terrified of AI because they've lost control of their campuses in general with kids just using AI to accomplish all their coursework, and then they're actively trying to keep them from using it, but then they're also using it to do their own work and then also to catch them using AI. They really just don't know what's going on. They don't know what the kids need to learn about AI to go out into the workforce. But also, I think ultimately the reason academia is so afraid of AI is because it's really showing how archaic the college system is. It's also showing young people earlier that they don't need to go to college for most things. And I think that is really inconvenient. So they're afraid of it for that reason. I think that's a lot of the reason of the colleges, you know, all these academics writing hit pieces, think pieces about AI is because they're just afraid for their own jobs, which makes sense because the funding's cut and they're all getting laid off.

Hannah Maruyama [00:02:26]:
So they're worried about their jobs. So they're comfortable blaming AI because that's better than blaming themselves for their own failures and the fact that their product is not good and the fact that their product is not helping young people. So I think that that's a huge thing. The robots are ruining everything is much easier to stomach and makes them feel probably better than, oh, actually this paper we're selling to kids is pretty much worthless and most of them don't need it to get good work and most of them shouldn't be here at all.

Ryan Maruyama [00:02:52]:
I wanted to back up a little bit and talk about the underemployment 10 years later, or rather, that's not the, this is completely from memory, but it rhymes with a statistic that I remember when I was in college about the amount of money that you take for your first job is very indicative, is like the number one indicator of your financial success, or rather of the amount of money you'll make if you stay into, in a career, in that career over your life. Basically that first job really matters. And so I'm making up the numbers here, but basically if you take a job that was $30,000 a year, the chances of you 10 years later, you know, making $200,000 is pretty low just because you, you'd have to go and get a 6 to 7x In that, in that 10-year span. Whereas if you take a job that is $90,000 a year, granted, you know, very, very difficult to find. Sure. All that. But if, but if possible, and you did, the jump is only a, is only a double or a triple from there. And so I think that that rhymes with what you're saying here regarding AI and the job market now.

Ryan Maruyama [00:04:09]:
And it being blamed for the underemployment or even for the unemployment. I think a large portion of that has to do with the way that these top-tier frontier model companies did their advertising. And if you look at the way a few months ago, the way that Anthropic advertised and marketed their frontier model Mythos and basically saying, It's gonna tear down the internet. Everything's gonna come to a, to a standstill. We must give this to 10 companies so that they can secure the internet and secure your life and everything like that. Otherwise, it's gonna be Skynet. If you look at even before that, they were saying, oh, all of the software engineer jobs are gonna be, are gonna be gone.

Hannah Maruyama [00:04:56]:
Mm-hmm.

Ryan Maruyama [00:04:57]:
In 6 months, there's gonna be no more software engineers. Then 6 months came and then they're like, in 6 months, there's gonna be no more software engineers. And the 6 months came and they'd be like, In 6 months, there's going to be no more software engineers. And then they've been saying that for like 4 years now. Yeah.

Hannah Maruyama [00:05:12]:
And so now entry-level positions are like up 18% or something.

Ryan Maruyama [00:05:15]:
Well, right. And so all of these places that are saying that, if you go to their careers page, how much are they paying software engineers? $200,000 a year.

Hannah Maruyama [00:05:24]:
So much money.

Ryan Maruyama [00:05:27]:
What?

Hannah Maruyama [00:05:27]:
Yeah.

Ryan Maruyama [00:05:28]:
Like these companies themselves, like go to Anthropic's page right now, whenever this comes out. I think this is actually going to come out in a few months too. So like, Uh, 'cause we run a little bit of a backlog. And so I promise you, go to their page, there's a software engineer role on it right now. They're making up stuff to make their jokes work.

Hannah Maruyama [00:05:46]:
Yeah.

Ryan Maruyama [00:05:46]:
Like they're making it, they're marketing it. And so, and now, and now you see the rollback in time. They're like, oh, well, it's not gonna destroy jobs. It's gonna, it's gonna be a net positive. And they're, they're doing all this now because they got all this backlash from all these data centers, like realizing now that like, hey, they need public opinion. You need public opinion on your side to build all of the data centers necessary to do all these things. And so it's like, no, it's not gonna, it's not gonna destroy jobs. It's gonna create jobs.

Ryan Maruyama [00:06:15]:
What, what, what are we talking about? I don't know where you would've gotten the idea that it was gonna destroy jobs.

Hannah Maruyama [00:06:20]:
Well, you told us that, right?

Ryan Maruyama [00:06:21]:
Exactly. And so, and so because they told us that, now all of the people, like there can be, there can be a ton of cope in the industry and like in any industry. And there's basically, there is a, there's a demon to blame because they named the demon. And it's like, AI is going to take jobs. And so therefore AI took jobs and therefore AI is responsible for my underemployment. AI is responsible for my unemployment, which is like largely not true.

Hannah Maruyama [00:06:50]:
That, you know what, you do bring up something though that I'm sure people are kind of mixing up because again, we talked about this, this was a couple years ago, but remember when a ton of, so I think it was after COVID, but a ton of HR got laid off and remember people were freaking out like, Oh my gosh, there's all these layoffs, everybody's losing their jobs. But actually not that many people lost their jobs. It was a lot of people that were in HR, and people that are in HR honestly are just more vocal on the internet. And so they just got more attention because they were just loud. And, uh, the same thing happened when there was a ton of funding cut from like NGOs and nonprofits that were just honestly like sending money around doing nothing. And so a lot of people did lose their jobs, but a lot of those jobs like shouldn't have been there to begin with. And I think what is happening, because, uh, this is probably just coinciding too, this is just like public sentiment. Like, so this is the way people feel, which does make it reality for a lot of people.

Hannah Maruyama [00:07:41]:
But a lot of the, uh, government money that was cut out of student loans, because, you know, they, they did that big beautiful— was it Big Beautiful Bill? Whatever it was, they, when they changed the amount of funding available to the universities, and that on top of the fact that there's an enrollment crisis because of age and also because parents are now not sending their kids at as high of a rate. And now there's less money available for the universities for public funding because there's just, the limits are lower. So because of that, a lot of universities, which I've said to you before, academia, I feel in a lot of ways is a jobs program. And so there are a lot of people employed in academia that should be employed elsewhere, but they're employed here because there's a surplus of public money and because there's artificial demand because of that. And so now that that demand is shrinking because there's less money available for them, There is a ton of layoffs going on for professors. There's a ton of colleges closing, but also they're laying off a ton of the admin staff because some colleges have like 8 admin to 1 student. It's like, what are these people doing? Like genuinely, what is their job? Like, how is it possible to need this many administrators to this ratio of students? That's like, what are they like, literally, what are they doing? You know? And so because that group of people is getting laid off and because again, they are allowed, because for the most part they're able to like You know, they get on the internet, they write, they say stuff like, you know, they're very vocal, they're very visual, uh, people. Whereas, you know, when, um, I'm trying to think of another example of a group that, that lost, like, loss of jobs during different times.

Hannah Maruyama [00:09:09]:
But during COVID a lot of people, do you remember there was that famous, uh, famously Biden told people who were working in the oil fields to like learn to code? Do you remember that? Where they lost their jobs because during COVID there was, there was a reduction of, uh, energy production. Yeah. And a lot of people who worked in oil field jobs, like operators, oil riggers, all kinds of guys like that lost their jobs. And Biden was like, oh, we'll just go learn to code. Right. And everybody lost, everybody was really angry about that, but they didn't get on the internet and like cry or say, oh wow, we lost it. They just don't do that. Like they just take layoffs and they just figure it out and they just do whatever.

Hannah Maruyama [00:09:45]:
Because that's just more the culture of people that work in those jobs. They're just a little bit more, yeah, they're just not as loud on the internet. But this group of people, professional, like people who work in academia and just have these like admin jobs, they're very loud on the internet. Like they'll get on the internet and cry, they'll get on the internet and scream it. And I'm not minimizing the fact that they're losing their jobs and that's incredibly stressful. Like you don't wish that on anybody, but at the same time, it's hard to avoid the fact that a lot of their jobs exist because we're stealing the futures of teenagers, of young people, and we're bringing that money to the present. And we are selling paper to these kids that they don't need to have a good life. And the money that we take from these kids upfront in order to give them paper that they don't need to have a good life, we are then distributing to a bunch of people in jobs that shouldn't and really don't have a real reason to exist other than the fact that we're able to take too much money from kids' futures and bring it to the present and then distribute it among this group of people.

Hannah Maruyama [00:10:40]:
And so because of that, along with all of the AI sentiment, like, and how much people do not like it on both sides, I think that that's contributing a lot to the fact that people feel like there's a lot of job loss when there's really actually not that much job loss. I think that has a lot to do with it. Who's losing their jobs and how loud about it they are on the internet has a lot to do with whether or not people feel like others are losing jobs and getting laid off.

Ryan Maruyama [00:11:05]:
Yeah, definitely. And I think from the news cycle perspective, it makes sense. The more vocal people are, I mean, the news, you just have to continuously, you have to feed the beast. They have to, they have to pick up a story somewhere. So if somebody goes viral for losing their job and the state stated reason is due to the employer saying, oh, because of AI, whatever it, they, they, they rather not say, hey, because we staffed up too much and we were irresponsible in our staffing, we can no longer afford your salary and therefore you must go. Because then that is like a decision that they made, a wrong decision that they made. Instead, the leadership is saying, you know, because of all this brilliant leadership decisions that I'm making, because we're bringing in efficiencies, et cetera, et cetera. We're getting rid of your job, right? And therefore AI.

Hannah Maruyama [00:11:52]:
But I do think, I am thinking about it now. I've seen probably close to 15 news segments, articles, interviews of like associate professors or TAs or admin staff at universities. And it's like these big sob story profiles with these really dramatic pictures of them sitting on the university steps. Like it's an attack on, like it's an attack on education. Like it's an attack on society itself. I didn't see a single— when all of those oil field workers who produce our energy got laid off, I did not see a single article. I did not see a single news interview. None of those people.

Hannah Maruyama [00:12:28]:
None of those people. I did not see a single one. I did not see a single piece of any of those people when they got laid off en masse during COVID and Biden said, go learn to code. I didn't see a single interview that was one even about that, about any of those people. And it definitely, if there was one, it was not sympathetic. But there are these long, and I'm talking like 10-page articles about like the attack on education, the attack on society itself by laying off a TA who's making $28,000 a year, going into debt to buy more paper to try to compete for a tenured position so they can teach a degree program at some small, like, private college that doesn't even need to exist. Like, you know, the college itself doesn't need to exist and the degree program that they're teaching definitely doesn't need to exist because it's not going to help the students who are buying it to financially get out of debt. anywhere, but because those people get so much media attention, it feels like lots of people are getting laid off when in reality only a certain group of people whose jobs again only exist because they're cannibalizing the futures of young people under the false premise that they need a degree to have a good life or get a good job or get a high-paying job or work, you know, or, or do anything other than literally what they were told in school was just flip burgers.

Hannah Maruyama [00:13:43]:
Like that's really, I think what's going on.

Ryan Maruyama [00:13:45]:
A little bit related to AI, not related to anything that we're talking about here. I'm putting together my thoughts on it and hopefully I'll have an episode out soon about what your child can do in the job market now to prepare. Because like the future is definitely 100% AI. 100% AI is going to be your future listening to this. I mean, in your role at your work. But then also your child natively, now from now until a long time from now, they're going to interact with AI. And so I, behind the scenes, my job largely all day is to work with AI. I mean, literally that is my entire job.

Ryan Maruyama [00:14:33]:
All I do is talk to AI.

Hannah Maruyama [00:14:35]:
I have joked before, and we, I frequently joke that I'm an AI widow because of how much you work with AI. Who was it that was, was it Marc Andreessen talking about, um, AI vampires?

Ryan Maruyama [00:14:45]:
Yeah.

Hannah Maruyama [00:14:45]:
The guys that stay up so late because supposedly AI was supposed to make it so that we don't all do work. But in reality, how it's looking is that actually—

Ryan Maruyama [00:14:53]:
It's creating more work than ever.

Hannah Maruyama [00:14:54]:
It's creating more work, which is what you and I have said from the beginning. Like, uh, you know, I think, I think the technical term is like AI optimist or whatever, but you and I have from the get-go gone, yeah, this is going to make so much more work. This is going to create so much more work. And indeed, that's exactly what's happening.

Ryan Maruyama [00:15:08]:
Yeah, it is increasing productivity, possibly, maybe, but it is at least increasing the amount of work. Like, I can't vouch for like how productive you are going to be or how productive your company is going to be with the implementation of AI. What I mean is like producing positive business outcomes and then like, you know, your child's company. And, but it is definitely increasing the amount of work that needs to be done And it's changing the nature of work. Whereas, you know, like if you think, once again, I'll, I'll get, I'll get, I don't want to get into the rabbit hole right now, but just suffice it to say, we, we got your back on the AI stuff. It is, I haven't fully formed. I mean, I have a lot of opinions. I just haven't like distilled it all down into an episode so that we can make a coherent case of the future and then how your child.

Ryan Maruyama [00:16:00]:
can integrate it in their life so that they can—

Hannah Maruyama [00:16:05]:
Just have base level skillset.

Ryan Maruyama [00:16:06]:
Right. Well, I was going to say to market it to employers.

Hannah Maruyama [00:16:10]:
I think, yeah, we need to do an episode about AI. Part of it too, I want to do a little bit of a more historical deep dive because we've talked about a couple of cases where when there's technological leaps like this, people always say, oh no, it's going to take all the jobs. And it literally never does that. All it does is create more work. And I do think that right now, one of the things that is going on, that there's a low hire, low fire job market. And I believe, and I believe a lot of that is because—

Ryan Maruyama [00:16:33]:
What does that mean?

Hannah Maruyama [00:16:34]:
Uh, it means that companies are not firing anybody and they're also not hiring anybody. Everybody's just kind of in slow motion, just kind of. And I think it's because a lot of these companies, as the whole, you're gonna lay off your whole, whole entire workforce and it's all gonna be AI, that's not panned out. Again, all of the doom, like from the AI companies who are trying to raise money. And so they needed to believe, like they needed to promise that they were gonna do that so that people would give them VC, would, you know, would like keep giving them an inflow of cash. And because of that, a lot of companies were expecting that that was going to happen. And also they're not sure how, as they integrate these tools, it's kind of what you and I are seeing, which is like, as you do it, you really don't know how much more work it's going to create or where you're going to need people. And so I think a lot of companies are kind of like trying to figure out where the tools fit, what now they're going to have to change about the jobs that they will have.

Hannah Maruyama [00:17:20]:
They don't even know how to describe. And this is something again, we've run into is like, if you're going to post a job, what are you even going to, what are you, what are you even going to post in this job? Like, what do you need this person to do? And right now I think a lot of companies are trying to figure out what they can offload to AI, how they're going to then hire, who they're going to need now, because it's totally changing the way that the jobs are going to look. And so I think a lot of this like hold brothers, I think a lot of it's because companies are not sure what job listings to write. They're not sure what to write in the job listings. And they're not sure how much more work in certain areas. And I think a lot of them are surprised by the areas in which there is a lot more work and there were layoffs. that a lot of people have attributed to too much hiring during COVID which did happen because of all the, again, all the government money. But I think that what's happening is companies are really unsure about how they're going to restructure.

Hannah Maruyama [00:18:10]:
And genuinely, when I say restructure, I think they're going to have to hire a lot more people, some of which they just let go because they thought that AI was going to do things it didn't do, and they thought it was going to do less of some things and more of some things, and they're just not sure where to put people or who they need. I think that's a lot of it.

Ryan Maruyama [00:18:24]:
It could also be expense as well. Because the tokens aren't cheap currently. And then also, if you let it go without tight reins, it can go ahead and do a whole bunch of work that doesn't, that never needed to be done. And a wage would have been cheaper and then therefore lead to more productivity. As I was saying, like literally the AI might be doing work. It just might not be productive. And so I don't know. whether or not I'm not smart enough to know whether or not we're ever going to reach a singularity or anything like that.

Ryan Maruyama [00:18:55]:
Like, I don't know if we're ever going to invent Skynet, but I, but I, but I am confident enough to see that like for a really good long time, we're all going to have work. I mean, there's going to be more work than ever.

Hannah Maruyama [00:19:08]:
Yeah.

Ryan Maruyama [00:19:09]:
And yes. Is it going to be different types of work? Yeah, probably. That happens whenever there's a technological leap. Is it now that your child is possibly doing the work of 2 to 3 people, possibly what used to take 2 to 3 people, and they have to be the human in the loop for that? Possibly. I, but who knows? I don't know. But right now it is all, I mean, at least I am very bullish on work. I'm very bullish on the work that it's creating. I mean, we see it, we see it in our company, like We need more people.

Ryan Maruyama [00:19:45]:
We need more people.

Hannah Maruyama [00:19:45]:
Like I was saying, and kind of what you were saying is it's really hard to know where to put them and what exactly they need to do and what they don't need to do and what's a good use of their time and their humanity and their creative skills and what's not. And it's difficult to write a job description because we're still trying to figure out where and what and how. And then again, the tokens, like you said, it's doing unnecessary work. It's doing productive work. Oh, it eliminated this thing that we thought we need. Oh, we don't actually need it. Now we need this. And like week to week, our urgent needs are changing because we're not really sure exactly where it's going to be like permanent and where it's not.

Hannah Maruyama [00:20:20]:
But eventually companies, especially the big companies, are going to have to figure that out because they have to move forward. Small businesses, I think, are going to be able to use AI in different ways and maybe it's going to be more fluid. But for big companies, they're going to have to be like, all right, this is our locked-in use case for it. This is our locked-in spend for it. Now, who do we need to put around this? And that, and that is going to even out. So I think that that's a lot of the reason for why it's everybody's low hire, low fire. People are not, companies are not hiring. They're not firing.

Hannah Maruyama [00:20:46]:
It's because they don't know what's happening right now. They're still trying to figure it out. And truthfully, so are the AI companies. And so it's all just kind of, it's kind of a mess right now.

Ryan Maruyama [00:20:53]:
Yeah. And so as far as making it actionable for your child here and positively in their career, we'll have something on paper. Like I said, I, I've been working with AI pretty much every day, all day for years, a year plus on this. And so I just haven't put down my thoughts on paper yet. And I know that it's long overdue. I wanted to switch gears a little bit here, not to completely just stop the bus and take a right turn here, but I'm going to.

Hannah Maruyama [00:21:24]:
Yay!

Ryan Maruyama [00:21:25]:
Yeah, exactly. Um, I wanted to talk about a call that we had this past week. It was for a family that signed up their child to the Launch Program and what was interesting about this family is that they have applied a bunch of times in the past year for the Launch Program, and they finally got on the call with us and it was the most defeated. Maybe defeated is not the word, but it kind of is. I'm at a lack for a better word here. So I'm just going to say defeated of just like, okay, well, I guess we're doing this then. And we're just, I guess, I guess we're, I guess we're signing, signing them up because—

Hannah Maruyama [00:22:02]:
That was the vibe.

Ryan Maruyama [00:22:03]:
Because there's nothing else, or because I, I, 'cause I don't know. And so—

Hannah Maruyama [00:22:07]:
The mom literally said, we're, we haven't gotten anywhere. That's what she said. Yeah, they, they had applied, yeah, 4 times, and I believe this was over a span of almost a year and a half. And originally they just said, hey, you know, this child doesn't have any direction about careers. Child was also employed, uh, working multiple jobs. So not a lack of work ethic, just completely not sure what direction to channel this work ethic or what To put it behind. And then I think that that is a major thing for parents. If your child is working, but they still have no clear career direction and you know the job that they're working is not one that they're gonna work long-term, most of the time that is not going to work out in that it's not going to resolve itself by suddenly they, the clouds open and they go, oh, this is what I need to be doing.

Hannah Maruyama [00:22:59]:
If they don't know what to do and you feel you are at a loss, um, and I especially see this as family has 2 working parents, they both work, and that I do see that a lot. If there's 2 working parents and the young adult does not have a clear career direction and they think that time is going to fix that, it usually doesn't because the parents simply just don't have time to do the amount of research, the amount of guidance, the amount of calling, the amount of vetting, the amount of work that's required to work through, eliminate options, be really strategic about what their child needs as far as income and schedule and work environment and location. And then also to help to prep them and equip them with the right direction to then start their career, figure out what they need to learn and then how they're going to learn it. And then also create a plan to keep them on track while they're doing that. And the mom came in and just said, yeah, we really thought we were going to be somewhere, but nothing has changed and we feel like we're running out of time and we really need to stop spinning our wheels. And so they enrolled their, their child and it was cool to hear the relief after they did. Where the dad too just said, I'm excited. I think that this is going to be really good.

Hannah Maruyama [00:24:06]:
And then the child was also very, very excited to start and could not wait to get a real answer. Because a lot of times these kids, especially if they're hardworking, they really do want to know what career they're building to, and they do want to be able to start it so that they feel settled and stable and that they can see the future. Because it's incredible the amount of relief that just knowing that reinforcements are coming And that someone's going to help. Someone's going to help you sort through this and someone's going to help you figure out what to do, why you're going to do it, how you're going to do it. And then what that looks like over the next year. And I'm very excited. I'm very excited too, to see the change over the next few weeks.

Ryan Maruyama [00:24:40]:
So to be fair, I don't think that this is necessarily isolated to families that have both working parents. I think that that's a little unfair to families that have, you know, largely stay-at-home moms. And it could be parents, but this is largely stay-at-home moms. You're expecting them, not like you're saying this, but it kind of seems that way. Like you're expecting them to know all of those things, like for them to know, to know where the job market is, to know how to find out what their, what their goals are, to know how to vet all these things and then, and then make the calls, try to find them opportunities to do that. And it's like—

Hannah Maruyama [00:25:15]:
True. You don't become a job market analyst overnight.

Ryan Maruyama [00:25:17]:
Right, exactly. Like that's not, Super, I understand what you were saying, but that's like super fair, right? To, to, uh, expect them to do that. Like, oh, if you, if you're a stay-at-home mom, if you're a stay-at-home parent, now exactly what you said. Now, now you have to do like what our career strategists do, which is like not, yeah, it's not true.

Hannah Maruyama [00:25:35]:
You're right.

Ryan Maruyama [00:25:36]:
And so, so for me, what was noteworthy about this, which is why we're bringing it up, was the year that this child just stayed in the loss window, right? Like, and that loss window was just like, I don't know what to do. I don't know what to do. Exactly. And it's largely in this 18 to 20, 18 to 21-year-old range where they're doing something like they are literally doing something. They're walking, but they are lost and they don't know what to do. And it just didn't have to be that way. Right. And so instead of, instead of coming into the program optimistically, all everything that you said, but instead of it being like, Oh, I, we're, we're beaten down and therefore like, okay, I guess, I guess this is what we're going to do.

Ryan Maruyama [00:26:19]:
It's like, no, when, when you see that there's a problem, when you see that they're lost, like, let's solve it now. And then they would have had the opportunity for the past year, past year and a half to pursue the things that they wanted to do.

Hannah Maruyama [00:26:32]:
As soon as you identify that the problem is direction and they are in a loss window, the sooner you can help them get to What do I need to do? Why am I doing it? How is it gonna help me get to a future I want? The more relief your child is going to experience.

Ryan Maruyama [00:26:46]:
It's not that you can't find direction on your own. Like your child can't find direction on their own. Obviously you probably did it. They will as well eventually. But what if we could shorten the time for that direction, right? Like what if we could shorten it and get them to where they're going quicker? And regardless where you are in life, I'm sure that you took a step and you took a beat eventually and said, hey, what am I doing? There needs to be some intention here. And then I need to act on those intentions. And largely to what you were saying earlier, that is not what they're doing at this stage. And a lot of parents don't have the bandwidth or the knowledge to know how to Get that intentionality out or sit down and do that intentionality.

Ryan Maruyama [00:27:35]:
And then how do we take those goals and then translate it into a plan? How do we go ahead and say, okay, this is your next step. This is your next step. This is, you know, do this, then this, then this type of thing.

Hannah Maruyama [00:27:46]:
I could not agree more. And it really does make all the difference.

Ryan Maruyama [00:27:49]:
So if this is you and your child and they're currently lost and you know it now, and you know that like, hey, actionable plan right now. We don't want to be stuck in the loss window for another year, another year and a half. You can go to degreefree.com/launch and you can apply for the launch program there. And that's pretty much it until next time.

Hannah Maruyama [00:28:09]:
Aloha.