Billy Riggs (00:41)
Welcome back to Rewiring the American Edge, where we explore automation, innovation, how policy, design, and leadership can power the next generation of public service

leaders on our planet. I'm Billy Riggs and I am joined by the amazing Vipul Vyas.

Today's episode where we're focusing on code and our all star guest. We're thrilled to have a civic tech pioneer, somebody who focused on the rules of government and how we, shape it. Marci Harris, CEO of and co-founder of POPVOX helps really shape how people engage with Congress.

A friend and former congressional staffer, trained lawyer. I think one of the most thoughtful voices on digital democracy that I know. Always a pleasure to have you on board. And we've, mentioned Matt Mahan, who's mayor of San Jose, who actually connected us, which is, it's a very

friendly group we have here. So, thank you for joining us, Marci. I, I hope I've done a decent job providing your intro and maybe, maybe you could, round it out a little bit for us.

Marci Harris (01:45)
very much. That's awesome.

That's fantastic. Thanks so much. And yes, shout out to Billy's mom and shout out to Mayor Matt down in San Jose. And Vipul, it's great to be here with you. Yeah, Billy, as you said, been in civic tech a long time. Back when we started POPVOX.COM in 2010.

Billy Riggs (01:53)
Yeah.

Marci Harris (02:06)
I used to tell people we thought we were going to solve all the problems of Congress with a website. And we didn't, but we learned a lot of lessons, ⁓ including what it means to sit in the middle of the Venn diagram between Congress and technology. So I live on the West coast and do most of my work with DC. But I'm originally from Tennessee, so I kind of keep the perspective of lots of different places.

around the country, including teaching down at San Jose and being a fellow fan of the work that's happening in the City of San Jose. Not just that they're leveraging AI for their own work, but that they really have built up this GovAI coalition, bringing together cities from around the world to share around the world. Maybe it's just around the country, but there've been a lot of cities getting together and sharing, you know, what they're putting in their contracts or what they're hearing from vendors or, you know, how they're.

deploying different ⁓ apps, what ethical questions they're asking, how citizens are responding. you know, our work at POPVOX Foundation, which is the nonprofit that we founded in 2021 to take the lessons from POPVOX.COM and apply it in its appropriate charitable home. But we at POPVOX Foundation focus a lot on legislatures, primarily at the federal level. But, you know, we really believe that it's important for

these democratic institutions at all levels and all around the world to share what they're learning because everybody's figuring it out at the same time. We're all at the starting gate together on what GenAI means for democratic institutions, for governing and for lots of other things that policymakers need to have a position or weigh in on. So it's an important time to share information. And great to be here.

Billy Riggs (03:47)
That's great.

Yeah, thanks, Marci maybe ⁓ just from a background standpoint, so you got to POPVOX originally just from a legal career wanting to influence kind of from a policy standpoint with technology. Can you explain that trajectory a little bit?

Marci Harris (04:08)
Yeah. Well, so let's see, I'm trying to figure out how far back to go. so I worked in Congress right after law school, for the Ways and Means Committee on, the Affordable Care Act. You might've heard of it. and, you may have heard that when the Affordable Care Act got passed and over to the executive branch, that then, went to implement it,

there were some issues at the implementation stage, the rollout of healthcare.gov. being kind of part of that process and seeing how much congressional committee and staff is bombarded with information at the legislative phase and how much language and decisions made at that stage impact what happens at the implementation stage.

was massive aha moment, but, the, the original genesis of the idea for POPVOX.COM again, back in those early idealistic civic tech web two days was, let's take all of this advocacy that I was on the receiving end of as, a staffer from, you know, lobbying groups and advocacy groups and grassroots organizers and others. was the first time that Congress was kind of receiving.

all this digital advocacy. So the idea was to bring it all online in one website and, let, let the public see what Congress was hearing, which was a lot. So, you know, we built the site, we delivered millions of messages to Congress. Over the past 15 years, we also found that we weren't

We weren't solving the issue we set out to solve, which was making sure that people better understood what was happening. In fact, there was a lot of, call them frequent flyers and others using the site for advocacy that was not super productive. So we shifted gears in about 2017 to working more directly with committees and staffers and others to try to prototype different tools or think about ways that they could get information.

to, better inform policymaking. So, we've been working on that ever since. We think that GenAI provides a lot of opportunity for better data-driven lawmaking, better focus on outcomes, even better ways to engage with the public. just kind of at the beginning stages of what's possible with all that.

Billy Riggs (06:21)
Yeah, so I think that's where we want to go next where do you see the problems and what are the solutions that we can, you think we can work on there with GenAI?

Marci Harris (06:31)
So, I mean, the problem that I'm obsessed with, that our organization is obsessed with, is the pacing problem, not my original term that came from a professor at ASU. But the idea that tech, as we all know, develops exponentially and policy doesn't. And policymakers don't, their knowledge doesn't increase at that same rate, which means if we don't do something,

that every year our democratic institutions are further and further behind the technology that's changing our society. So our mission is to help democratic institutions keep up. And that means everything from helping them have better tools and processes and better capacity and talent among their people internally to deploying those tools to.

to make better policy, have tighter feedback loops as a program is implemented to see what the outcomes actually are in the world. And ideally be able to go back and adjust in a more agile way that you can see that I learned a lot from my time in Silicon Valley. And I think that there is a whole lot to be learned from the practices of modern software to incorporate into.

the lawmaking, the oversight and the refining process to ensure we've got policies that are more responsive to the world.

Billy Riggs (07:50)
Yeah, I think that's right. I mean, Vipul you've worked in the software industry and in I don't know if you'd want to weigh in on that as well in terms of your background working in the tech space.

Vipul Vyas (08:00)
I would agree with Marci that the stuff, things are changing fast from a tech perspective relative to the past. The rate, I guess the second derivative is increased in terms of acceleration. We're accelerating at a faster rate. And so I think it's gonna be even harder to keep up.

And in that context, you know, there's also there's a few trends actually happening or two. There's a variety of convergent Things happening in society trends is maybe the best word for him, but you're having the slow displacement of The older population of leaders with younger ones.

At the federal level, institutions are pretty ossified, I would say, or that's not the kind word, but they're pretty set. They're established is maybe a better way to observe it.

And at the local level, there's more dynamism or just by the nature of things there. It's more fluid. And so I see a lot more swap out occurring. I mean, you see that in New York, whatever you think about the, you know, specific policies or political philosophies, you know, the establishment folks, think both

Cuomo and Adams were boomers or our boomers rather and You know, they're being displaced pretty aggressively by younger folks.

And so you're gonna have a much more tech savvy tech comfortable set of folks. There are people in the boomer, you know demographic who just don't use email that much Forget like anything more sophisticated. That's not everyone. There's a lot of people who do obviously but

There's just that big digital divide because they didn't grow up with it in the same way that generations that came after them did so that's going to be a big change. And the second thing I think is that it doesn't necessarily have to be government or government leadership that does it; that there's an opportunity for government to actually expose data expose information outward

so that people, the average person can inspect and interrogate things. And the real template for that, think, and Marci may know better because I don't have a right to an opinion, but I have one. So this is COVID where everyone was publishing their infection rate data, their vaccination data, and all that was for public scrutiny.

And it was scrutinized. And I think that's probably the model where people can look at the budgets, can look at things in great detail themselves and interrogate it and interrogate it easily and quickly because you have AI. But part of it is making that stuff available. And this is where I actually see the intersection of AI and the now long forgotten

darling of yesteryear blockchain where you actually do have open track ability coupled with AI because now you're to have transactions that happen across many parties where no one person owns that quote unquote ledger and so the intersection of those two things enables

everyone to be able to interrogate what's happening and understand what's going on because in large urban contexts, I think Matt Iglesias may have said, I'm quoting him may get me in trouble in itself, but it does have an interesting insight in that whenever you have this concentration of wealth that you have in typical urban areas, you have the ability for certain interests to capture power and extract wealth.

and do that in a pretty systematic and deliberate and maintainable way and so what you want to do is potentially prevent that from happening on an ongoing basis or any substantial this is the best way to do it to have people just being able to see. So I'll stop there I think so big thing you can work with the leaders which was Marci's point, but which is great. I think that makes sense, but you can also just make government much more transparent

and there's no reason for it not to be in this era.

Marci Harris (11:35)
I'm definitely in favor of government transparency. do think, you know, part of the optimism of the early open gov days was that we were going to make it transparent. Don't get me started on how many transparent things were PDFs. And now we can actually parse those PDFs, but you're to make it transparent. And then everybody was going to turn into a watchdog. And yeah, you know, to a certain extent, maybe, but also people have lives and

So, you know, with the exception of things like COVID, where there was great interest and you saw a lot of folks doing a deep dive, it's, you know, we actually are living in a world when there are fewer journalists to parse that data and, you know, fewer resources to actually analyze it. And we actually see the watchdogs being defunded as opposed to ramping up the capability. So I think that's one force.

But I do agree with you that GenAI actually produces perhaps a new wave of opportunity for this, for the original kind of hope of open government to actually play out. and I, I, so, let me just say my dream of that is less, less individuals, you know, going in and spending their Saturdays parsing the data.

Vipul Vyas (12:35)
Yeah.

Marci Harris (12:47)
I, you know, we hear a lot of talk about the potential of agents and I think everybody's thinking about agents being deployed in, in governments or businesses, et cetera. I get excited about civic agents and, and watchdog agents and oversight agents. And so I think, I think the next phase of gen AI and agentic AI might actually bring us to that, that beautiful potential that we talked about, you know, decades ago.

Vipul Vyas (13:12)
Yeah, no, I think that makes sense. One thing I was just gonna add is what I noticed in San Francisco is there's a lot of citizen journalists, if you will. There are, you know, and I do wonder what they do with the rest of their time because it's a fair point, like, But they're the ones who actually uncovered or identified a lot of the issues, I think, in almost eight. I'm gonna put a figure on it, more than 50% of...

Billy Riggs (13:12)
It's really.

Marci Harris (13:24)
Yeah

Vipul Vyas (13:36)
of kind of, they spent money on that or someone did that or they, you know, they decided this made this decision. It's really come from the sort of blogosphere, if you will. The other thing, you know, from within government, I don't know if you guys follow, and I'm gonna butcher his name, Ken Mejia the city controller, it's city, yeah, Los Angeles city controller.

⁓ he has an amazing instagram site where he actually is kind of like Mandami He's like very he has a rap he has like a couple dance numbers that he does or he explains the city's data And the city budget to people in a super entertaining and relatable way And also, you know gives sometimes dire warnings about the city's financial health But that's probably a little bit of the future, too

And that if you can get even people in government to make things honest and relatable and entertaining for that matter It can create a compelling level of engagement.

Billy Riggs (14:32)
Yeah, we should put a link to that in our show notes because

that sounds pretty darn cool, but not as cool as your friend the ⁓ skater librarian, Vipul. We have a skater librarian here in San Francisco. Our head librarian is a skater.

Vipul Vyas (14:44)
then.

Yeah, and that's a way of,

Marci Harris (14:48)
I

Librarians are cool in all their stripes. I'm pro-librarian.

Billy Riggs (14:54)
Okay, but I'm gonna be the downer here. I'm gonna, you know, I think we have to kind of situate ourselves a little bit amongst the people who are out there and listening and skeptical. And because I do think there's a fair amount of people that may be sitting out there thinking that there's a...

a dark side to the AI future. And you know, what happens when things go wrong? You know, like the healthcare.gov rollout or when the result is big, slow and expensive, and there's not a timely rollout for technology so I guess, is there a counterpoint?

to this argument that, this AI thing, it's not gonna work. And I guess my argument would be to those people, "Hey this is not new. We've done this before. Agile government is not a new experiment."

⁓ Marci, can you talk a little bit about some of the work that's been done with the US Digital Service and some of the original experimentation with evolving some of the agile

governance, human centered design and open source tools. Because I think we skipped over a lot of the evolution that Jen Pahlka had already started within governance and the Obama administration that really has set a lot of this stuff up. And I really feel like our audience needs to understand this didn't come from nothing.

Vipul Vyas (16:13)
Really awesome.

Marci Harris (16:24)
Yeah. And certainly a lot of innovation has happened over the past decade, couple of decades. I am a very, very big Jen Pahlka fan for those who are not familiar. So she was in the Obama administration. founded Code for America, wrote a book called Recoding America that documents some famous examples of these kinds of

projects that Billy was just describing, digital services attempts to upgrade and fix legacy systems and the different places where they ran into issues. you know, I am working pretty closely now with Jen and some of her colleagues at the Niskanen Center and Foundation for American Innovation and, or excuse me, Federation of American Scientists, also FAI, to

to close, you know, what we describe as feedback loops. So you have a lot of folks who work in digital services on the ground, trying to deliver services better. But often what gets in their way are policies that have that, you know, are designed for different eras or, know, unintentionally place roadblocks in the way of implementing a program in, know, if, you're trying human centered design and the humans tell you needs to work one way, but the policy says it can't.

Billy Riggs (17:10)
Mm-hmm.

Marci Harris (17:34)
That's a problem. And so what's the feedback loop for the folks on the ground building the tech or delivering the service to let the policymakers know. And in the case of the federal government led Congress know, Hey, you know, we're working to implement this program, but we need this law changed or this regulation changed, et cetera. And those feedback loops haven't, haven't worked very well over the past decades. And so part of what Popbox foundation and others are working on is trying to make those

feedback loops more effective. But yes, US Digital Services and AT &F and others, those teams have now been folded into the DOGE service under the government's services, ⁓ the GSA General Services Administration. So there's all kinds of pieces being moved in the executive branch, and I'm not quite sure exactly where they've all landed.

And certainly lots of good folks who have departed from federal service. And, you know, and also I think that there are ⁓ lots of attempts to, to, you know, deploy technology for automation in areas that, you know, people who are not super familiar with government might think, well, that's just easy. Let's just automate that. Not understanding all of the different layers of policy that get in the way. But

All of that said, I think we're at a weird place where those kinds of efforts are massively politicized. I think there's a lot of good people with a lot of knowledge who've departed service and just in general, kind of a weird time to talk about this stuff. But if you talk about it in a general way, taking the politics out of it, I think...

there really needs to be a new approach to what are the services we're trying to provide? Does the policy as written, know, what is the outcome it's trying to achieve and does it enable that outcome and how are we carrying that out? does, you know, does the way we've been doing it make sense? Is there something that can be automated? And so, you know, I think there are some opportunities for some well-designed responsible.

experiments to be piloted over the next several years that are going to improve service delivery beyond what is possible now. I and, and I will steal from Jim Paulkin and say, you got to compare it to, don't compare it to perfect, compare it to the status quo. And often the status quo is if you've applied for, you know, VA benefits or social security disability insurance, you may, may wait years for a determination of whether you're going to receive that benefit. Well,

I mean, I don't know about you, but I personally would rather get an instant denial and be able to start my appeal, understanding what it is that, you know, it wasn't, wasn't approved as part of my application rather than waiting for two years and have the uncertainty of, whether I'm going to get approved. I think rethinking government services in general, we've, we've got a lot of opportunity to do that. And tech is often the easy part. I know I'm not a technologist, so I shouldn't really say that, but,

Billy Riggs (20:14)
Yeah.

Marci Harris (20:30)
Really often the hard part is going back and figuring out what is intended, who can make the determination about how we're going to do this, who's got the power to change a requirement or to approve an agile process or a product-based process as opposed to some terrible waterfall legacy system. And how do we rearrange the institution around what needs to be done? And then the building it part is, yeah.

Billy Riggs (20:56)
Great, great, great. Let's call

the tech the plumbing. We got to design the roadmap or the architectural drawings before we plumb the house.

Marci Harris (21:04)
Yeah.

But sometimes so clarifying when the engineers are asking the questions, you're like, yeah, right. Actually, it doesn't make sense. I know you're right. But it's the engineer that can call it out and say, yeah, what you're describing actually doesn't work.

Billy Riggs (21:11)
Thank

⁓ that's so fascinating. So, okay. If we were to step back and, and then just kind of look at some of the stuff you have been working on more recently, cause you're, you're situated right now. And you said this before we got on that you're, you're actually sitting right now, I believe in Norway. So you're sitting at, at a really macro scale

Marci Harris (21:37)
I am,

Billy Riggs (21:39)
what should we be rewiring

the way we do legislation in the US.

Marci Harris (21:45)
Yeah.

Vipul Vyas (21:45)
I see some amazing things happening down in San Jose. The mayor is very AI forward. I think it's unfortunate. And in some ways, I feel like...

AI has bailed out San Francisco from itself. And that's happened multiple times. Things that happened in San Jose ultimately benefit San Francisco in inordinate ways. This is my general belief situated here in Palo Alto. But Matt Mahan is doing a lot of things. He's got an AI initiative. Most of the cities in the peninsula, for example, use AI for language translation to promote inclusivity.

And I think Matt Mahan recently said that Hispanic engagement in San Jose civic discourse has increased by 300%. So city council meetings, et cetera. And that is because you simply now can apply translation services in many more content, interpretation specifically, in many more contexts because it's cost effective or cost possible, I should say. And, you know, I know that the current administration

designated that the US have now a official language by executive order in March and that's English but we've never had one before then but that doesn't you know belie the fact that this is a pretty diverse country constantly evolving constantly changing and so

You're going to have populations in many of these urban areas that not just English and Spanish, but English and many other languages. And many times you just can't find an interpreter for

Gujarati or Vietnamese and often times you need two interpreters because one is not enough, et cetera. So that's just an example of how that technology is coming in, making government more accessible and more inclusive for more people in a cost effective way. But there will be in other cases resistance. We can see it with, know, Billy, your own experience with

autonomous vehicles in San Francisco, right? And there's legitimate reasons for resistance in some cases, and in other cases, it's potentially unfounded fear, but that's what's gonna have to be navigated. So I'll stop there.

Marci Harris (23:40)
The way that policymakers understand this technology and, know, we think they ought to be using it and understanding, you know, its opportunities and its limitations. but we really care about, how the government, especially the policymakers are, are using this technology to better understand, you know, what they're working on. And, you know, I think, I think they're the future.

is outcome-based. So the future is, okay, lawmakers, you just got elected. You came to Washington. You know what you ran on. Get in a committee room. This is what you said you were going to optimize for, whether it's name that thing, health, economic growth, better environment, whatever it is, get in that room and talk about how you're going to know when you've achieved that outcome that you ran on.

Like how are you going to measure that you've achieved the outcome? And then let's back up from there to some policy options. My goodness, AI is fabulous at presenting options and running scenarios and things like that. Let's talk through some policy options and then let's write a law that says that we're going to leverage our federalist system. The fact that we have lots of opportunities for

Kentucky and Tennessee and California and New York and Maine and all these wonderful states and territories to implement based on what they need in their communities. Set the metrics at the agency level. Let a thousand flowers bloom in terms of implementation strategies. Let every implementation be its own experiment. Standardize data so you're comparing in real time what's working, what's not, what's within.

the bounds where the outliers are good outliers and bad outliers. We've got good outliers. Let's go find out what they're doing and share that information across the cohort and let policy implementation be a local, you know, you can have your community participation process at the local level and, and, and let it be, you know, a, a learning process as implementation happens and report back to Congress or let them see in real time dash reports, what's working, what needs a tweak, what needs refinement.

and really leverage this technology for making policy that works.

Billy Riggs (25:54)
Okay. That sounded really, high level, but it also sounded really ambiguous. And, but like, so are there specific guardrails you're talking about or specific things that when, it comes down to brass tax and policy with regard to kind of like things specifically that you're suggesting when, we're actualizing and we're writing legislation.

Marci Harris (25:57)
Okay.

Billy Riggs (26:17)
And are, you making specific suggestions to the United Nations or things like that when we're writing, when governments are writing policy, are there things that you're suggesting that, that, you know, when policymakers are going in and they're using an LLM for writing policy, there, are there nuggets that like when, a local council member is using a, LLM to write policy or should they be, is that a, is that a, is that a, is that a stupid move?

Marci Harris (26:42)
Not at all. No. we're actually prototyping a tool right now. We call it Policy Sandbox that it's basically designed for a staffer.

Marci Harris (26:51)
LLMs to model policy. And I'm happy to go there if you want me to.

Billy Riggs (26:54)
How would we talk to somebody that... So Matt Mahan apparently is doing all his talking with ChatGPT these days. That's very interesting to me.

Are there strategies for perhaps going in and having certain policy language and then structuring that language in a policy format or are there are there things that you're suggesting

⁓ to policymakers in terms of the way that they may pivot between different, different formats or things like that. I I'm just curious if there are tacit recommendations you would have.

Marci Harris (27:26)
Yeah. So,

well, so, so we're actually, you know, yes, absolutely. They should be using the various tools that are out there. not just because it's substantively is helpful for them in, you know, talking through different policy options, but also it helps them gauge how the various models are working, what their limitations are. Are they perceiving bias? You know, how, how, you know, how does Gemini compare to Grok compared to

ChatGPT and Claude, et cetera. Policy Sandbox right now it's using the OpenAI API, but we can shift it to Claude or others. But it actually is a rag system that's got ⁓ Congressional Research Service, Government Accountability Office and Congressional Budget Office reports.

in its system and let a staffer kind of talk through, well, I'm thinking about a policy on this. And then it says, well, has your boss ever made a statement about that? You know, what's their background? And they're like, well, you know, he says this and this. Well, what committee is he on? You know, should we, should we tailor it to the jurisdiction of that committee? And then, you know, have you thought about, you know, how you would like this to be implemented? So it's, it's basically a co-pilot for a staffer who's thinking through a policy. Now the output of that is not legislative language,

on purpose. It's instead a policy memo that a staffer would take to the very professional lawyers that work in the legislative council's office in the house and say, here's my idea. And now you, know, very accomplished keeper of the code, please write this into legislative language.

Billy Riggs (28:49)
Okay.

Okay.

Marci Harris (28:58)
And we talked to ledge council about that and they said, actually that would be helpful because sometimes staffers don't really know what they're asking. They don't really understand how various policies would work. So it's kind of walking them through the questions that ledge council would have to ask anyway, but not using LLMs right now at this point to do the legislative drafting because I think we still are quite a ways from that. But eventually we'll go there.

But that's going to have to be very careful process.

Billy Riggs (29:26)
Yeah, so there would be a filter per se. kind of in an intermediary in the...

grand scheme of things.

Marci Harris (29:36)
I mean, think at the stage we are now in lots of, know, even encoding, certainly in contract drafting and, you know, these tools are tools. They're co-pilots, they're research assistants, they're thinking partners, they're not lawyers, they're not, you know, maybe they're pair coders, but I think we've learned recently they shouldn't be the full coder of the thing. And I think we're seeing that,

Billy Riggs (30:00)
Yeah.

Marci Harris (30:02)
That's the stage we're in now. That's the stage we're in today. We certainly are, you know, as they always say, we're dealing with the worst AI today that we ever will, and it'll be better tomorrow and into the future. But starting to lay the path for how we want it to help us is important. It's important to start now.

Billy Riggs (30:20)
So any legislator or any public official that wants to use it for code should definitely be working through their legal counsel. So that's, yeah.

Marci Harris (30:28)
Well, yeah. And I mean, you know,

if you're a member of Congress or you're a state senator, you you may have interns drafting your talking points or staffers drafting your speech. You usually read it before you deliver it. So, I mean, it's the same principle. Ultimately, you're going to be the one signing your name or voting for that bill or giving a speech.

Billy Riggs (30:51)
Right, right, right, right. Well, Marci, I wanted to just say first say thank you to you, but also maybe offer you an opportunity ⁓ for a last word. And if you had any kind of ⁓

⁓ final reflections that you wanted to offer to me and to the rest of us. know Vipul already had to drop off. but any, any final thoughts or time time for a lightning round of, of advice you want to give to, to, my mother.

Marci Harris (31:16)
Well, I'm very glad to send a hello to your mother and also just appreciate the conversation. I think that my major point would be that I know there's a lot of folks who are in tech that get frustrated by the governing side of things. It's too important to ignore. And it's really important that, you know, there's lots of folks in government that are ignoring the tech or thinking that

that they don't need to engage there. Nope. ⁓ those days are over. We've got to all speak each other's language and understand what's going on in each of the worlds. And it is absolutely important that we bend that curve of the pacing problem and get democratic institutions at least at a little bit different angle in terms of keeping up with technology because

otherwise we're going to be lobbying tech companies to protect our rights in the future. Democratic institutions are really important and we need to preserve them. And that includes increasing their capacity so they can keep up with how quickly the world is changing.

Billy Riggs (32:16)
That's right. Thank you for that. And I think it's ⁓ not just, you know, if we want smarter government, we need smarter code. And that's not just thinking what we build. It's thinking how we build it. And so I really appreciate the work that you're doing. Thank you for sharing a little bit of your journey with us. And I hope we can talk more in the future. So, ⁓

Marci Harris (32:36)
Thank you.

Bye for now.

Billy Riggs (32:39)
Yeah, yeah, yeah, so hope to see you soon and thanks everybody for joining us today. Subscribe. Leave us a review and come back and see us next time.

Marci Harris (32:41)
Thank you.