A (2:33)

And just for the listeners, a part of the point, the reason I asked Josh specifically is, you know, even when you're building a tech company, a software business, a marketplace, like to do something really new and different is just a lot of hard shit, right? Like walking around the airport and knocking on the windows of drivers and trying to persuade them. And like, that's part of what it takes. And like it if you don't want to get your hands dirty, which doesn't mean doing things that are unethical, it just means like doing things that are uncomfortable and hard, you're probably not going to succeed. I mean now probably there aren't many people who have to do things like that, but that's kind of what it, what it takes. When you were building Uber in New York and Josh is being slightly modest, he took it from Nothing to a $2 billion a year business there. But the regulatory structure obviously is different everywhere else in the U.S. so how did, when you would think about sort of your job compared to your peer, other general managers around the country in the world, it kind of. How did you think about it?

B (3:36)

It, it, it certainly was different. You know, the business that Uber runs basically everywhere else in the US is a true ride sharing, where the person who picks you up, it's probably not a career for them, it's something they do a couple hours a week. They're not licensed as a driver in the same way. And so Uber's MO is sort of launching that and then getting rules written to make that the, the law here. We never did that. We were actually just the best paper fill outers license applicants that the city really had ever seen. And so it was, it, it is fundamentally different. And people say, oh, you know, Uber skirts the laws. It's actually quite the opposite. In New York, we were just the best rule followers we could be. And that, and that really worked. It was always a supply game. Demand was a bit easier because people like the idea of pushing a button and getting a ride. It was the drivers who needed the real sell.

A (4:37)

Although what's interesting is, you know, and obviously as a person that started sell Uber in a lot of ways for a long time, you know, the argument is pretty simple as to why customers liked it and that's why we were able to sort of win everywhere. But in a weird way, you had the highest bar to clear. Because as frustrating as a New York taxi Might be. It was still a vastly better system than most cities. Right. Most of these, it was like, well, so like you weren't doing D.C. but you remember this, the first campaign we ever did where we asked our customers to weigh in was I think 2012 in D.C. and one of the reasons, and it was very rudimentary, like we just emailed our customers. We didn't even have it in the app yet. But one of the reasons that it worked and I think surprised us so much is, you know, anyone who's been in a cab in dc, it's so horrible that people were like, no way am I going back to that.

B (5:26)

Right.

A (5:26)

You, I thought in some ways your job was harder because, like, taxis, New York really aren't tip. You can have a bad experience, but not that bad.

B (5:32)

It's not that bad. It's a, it's a street hail system, you know, like exclusively. You can only flag down, at least at that point.

A (5:39)

Right.

B (5:40)

You have to have line of sight and wave your arm. And so if you live in Manhattan, particularly south of like 59th street, getting a cab isn't that hard. Maybe in, in the rain or in certain extenuating circumstances. In other cities, you call the taxi. So if you're in the dc, you can flag them down too. But calling is a way that, that would typically work, particularly in San Francisco. And so you'd call and they would never show up. So that was the experience that people were really resonating with. I think here it was more arguments about the outer burrows around, like discrimination. If the driver doesn't like the way you look, he might not stop for you.

A (6:15)

Which was a big, actually political utility for us with Uber, because you had a whole community of African Americans who had always had the experience of having their ham up in a taxi. Passing by and therefore mobilizing that community was a little easier because they were so rightly angry at taxi.

C (6:32)

It was, it was really an interesting example of a system creating economic discrimination. Because I don't think it was that taxi drivers were racist. I think it was that taxi drivers have a limited amount of time to make money. On a shift, they saw an African American on the street. They know they're probably going outside the main zone of Manhattan and then they're going to have to come back to it empty, which means they're losing time, they're losing money. Money. So the city's medallion system was perpetuating a way of making money that ultimately discriminated against people in the outer boroughs, mainly people of color, people like Myself, I grew up and lived in Brooklyn. I remember you'd get in a cab, you would close the door, then you tell them where you're going, because otherwise they're gonna. They'll just drive off, try to kick you out.

A (7:11)

Right. So you leave Uber in 2017 and then what?

B (7:14)

I join you at Tusk Ventures?

A (7:16)

That was the leading question.

C (7:18)

Yeah.

B (7:18)

Which I. Which I really enjoyed. I did a bunch of investing with a few different flavors and just found that it wasn't really for me, which, actually I ended up starting a venture firm. I went all the way and then realized, actually I like focusing on one thing really exclusively. I've had some other operating roles and launched an app in 2023 that helps people record meetings using AI. Got Wave. AI. It's called Got it.

A (7:47)

And then you. When did you guys start working on this?

B (7:50)

So. So just to sort of.

A (7:52)

And we'll get into this in a second. Yeah, but when. When did the process.

B (7:55)

So I'm a computer nerd, but had never been a true software engineer. No one had ever paid me to write software before. At Uber, I was on the, like, marketing and operations side. I've always been friendly with engineers. I've been maybe envious of engineers because they get to build the thing that

A (8:09)

people use and they don't have to knock on the doors of windows of taxis.

B (8:12)

Well, sometimes we brought them out for that too. But I did feel like if you're building it something digital, if you. If you're selling software, which ultimately Uber is software, it's pretty fun to actually make the software. And so AI kind of helped me get the rest of the way in learning how to make software myself, which is obviously a big thing now. It's pretty early to that, right?

A (8:34)

Coding.

B (8:35)

Early vibe coding. I mean, I might be one of the first sort of successes of that. Of that era. It's everywhere now.

A (8:41)

Right.

B (8:41)

And so it's much easier now. But I think right around that time, I was doing Wave, and I said, you know, Matt, I was kind of looking for a few ideas, and one of them was the idea that we had that we'll talk about in a moment. But I sort of showed Matt, like, look how. Like, look what I can do. I can make this AI summarize bills as they come out, right? And we sort of had a prototype, and then I kind of put it down for a few years to work on my main thing. But the, like, models got so much better and the tooling got so much better, and building things got so much easier that I Was like, maybe we should.

A (9:12)

It's funny how I find this too now, where you have ide that you don't pursue, or you just pursue them a little bit, then you kind of realize it's not the best use of your time or resources. And then the world evolves in ways where either from a cultural normative standpoint or technological standpoint, or political. The idea you had 10 years ago, all of a sudden now makes sense.

B (9:32)

Yeah. Or it's easier to instrument, like AI makes everything easier tomorrow, like, I'll put this off till tomorrow. It will likely be easier. When Opus 4.7 rolled out, which was last week. I don't know when this will air, but it just came out. This happens every few months. It's like all the people, because I. I work alone, but all the AIs that I work with get smarter. All of a sudden, it's like I come into work on a Thursday and all of a sudden everyone is a little bit smarter. And that. That has happened every three months.

A (9:57)

Josh, you look like you didn't get sleep. Get enough deep, deep sleep at REM last night. So, Matt, your story is different because, you know, you're more like me, kind of a political operative. So walk us through that.

C (10:08)

So Josh is a tech nerd by training. I'm a political nerd by choice. I spent my first decade working in government and politics. Similar. Similar to you, Bradley. Couple of different jobs I held included being being communications director to Bill de Blasio when he was public advocate before he was mayor.

A (10:24)

So did you know how bad it was going to be?

C (10:29)

I. Well, it depends. Working for him was very emotionally painful the entire time. He's a very. I would. I think most people who worked in with him before and at City hall, when they're. When they're being honest, would say he is not a fun boss. He's a bit of a micromanager and he's lazy. It's. You know, I. He's. He's. He is. He. He, like, he starts his day late and he's demanding of others in a way that he doesn't expect of himself, which is something I have trouble respecting. And. And was something that ultimately, when I, When I left after three years, part of it was feeling a little bit of resentment and angst towards him personally. He. I mean, he also just was, like, mean to me and said, like, some of the nastiest things any boss has ever said. And when you're young, you know, and in politics, it's not a coincidence. I think that A lot of staffers are so young is because the older elected can sort of one of the.

A (11:21)

If, you know, it's, it's funny if you can give advice after you've kind of been through that for a while and look back at it is one of the things to me that I realized was. Was valuable was not knowing learning. Not just who to learn from and what to emulate, but just as much, if not more so, what not to emulate. Right. So like when I work for Mike Bloomberg, most of the stuff was worth emulating. You know, not empathy per se, but like a lot of things. Right. Whereas, you know, even Chuck Schumer, where there were certain. I learned a lot about media and politics and things like that, but Chuck was a horrible manager. Right. And some of that was like, do not be like him.

C (11:56)

Yeah.

A (11:57)

So did, did you feel like you were able. And then we'll get to Andrew C. But like, given that you work for some really terrible people in real time, were you able to know like this is how not to be, or do you think that you and especially a lot of your younger colleagues who are your age, then they sort of internalize the wrong lessons and behavior?

C (12:17)

It's a really good question. I think I was too young to know the difference. And the truth is this is the double edged sword. There's a lot to learn from these people. They. It's not a coincidence that Bill de Blasio got himself elected mayor and served for two terms. And he, he is one of the most brilliant political operatives I've ever met. Yeah, he is, despite his inability, I think, to communicate with people in the media, a very gifted policy wonk. He can go deep on the details, on things in ways that I think most people find surprising. I learned a lot from him. I. In hindsight, I learned that the type of management he had was not for me. I actually learned a lot of that at Uber, where you had in the private sector a little bit more investment in management when I went there later in my career, but in real time, no. And I like, I'm sure I was an awful boss to the people who had to report me because I was replicating bad patterns. I had one really wonderful boss early in my career, a guy named Jeff Lerner, who is Andrew Cuomo's communications director when he was Attorney General. And he was a really positive model for me of lifting up people who are junior, giving them added responsibility, but protecting them from kind of the craziness of the elected official. And so I think that saved me a Little.

A (13:26)

Yeah. I mean, it's funny, when I was in Illinois, work Blagojevich, I actually sadly, but I think rightfully saw some of my job as I will absorb all the insanity. So you guys can do your jobs. Yeah, right. Which sucked. But you almost. It helps to almost look at it that way so you can see the larger purpose to it. So then you went from bad to worse.

C (13:47)

Yeah, it's. People often said, I then went to work for Andrew Corporation. Cuomo. He was governor. It was his first term, which was a, you know, a very exciting time. I was first his deputy communications director for New York City, which was kind of a made up position, then became his press secretary. People often ask me which of them were harder to work for, and they expect the answer to be Andrew Cuomo. And the answer actually isn't, it's Bill. Bill was, I think, a little bit harder on me.

A (14:12)

Cuomo.

C (14:14)

One, it was early, so I think he was a little bit more controlled and restrained. He had learned the hard lesson of running for governor the first time. Of what, being kind of a terrorist to people or. But two, I mean, I was also a little bit more protected because I came in later. But also he. A big difference between him and Bill was he demanded a lot of people, but he. He did a lot of the things that he demanded of you. He showed up to work really early. Right. And he knew a lot of the details of what he was asking. He was also a micromanager. I actually think they have a lot of. Even though they would hate to think this, I think they have a lot of similarities.

A (14:50)

They can hang out together.

C (14:51)

Yeah. I think they.

A (14:52)

I think they both have a lot of free time.

C (14:53)

I always. I wanted. I pitched both of them through their staff on, you know, the Inner Circle is this performance that happens in New York City. The reporters, you know, do a musical making fun of the politicians and the mayor does a response. I thought it'd be really funny for them to do a video together about how they were secretly roommates.

A (15:08)

Yeah.

C (15:08)

Right at the peak of their animosity. But they did not go for that.

B (15:12)

That's funny.

C (15:12)

I thought it was funny. I thought it would have been great. It was a huge surprise. And then they would be pretending to be fighting for the media, but. But they were actually, you know, hanging out.

A (15:20)

They were around Cuomo for a pretty long time.

C (15:22)

Yes.

A (15:22)

So when he took office, I agree he had. He had been humiliated enough that he behaved well for a little while. What did you notice in retrospect, the moment where it Started to turn where he started to sort of think, I can do whatever I want and get away with it. And he's. Which ultimately was his downfall. But can you, like now go back and kind of pinpoint when that was?

C (15:45)

It wasn't. I don't think it was while I was there. I don't think it's a really interesting question. You know, there's the famous adage, power corrupts. I actually think it's just that power changes people, and it's hard. It's hard to not be changed by that. I also think ultimately he, like Bill maybe more so, is probably the best political operative in New York.

A (16:07)

Right.

C (16:08)

I know I say this after. After he ran a. Till he aged out of it, probably, but I would.

A (16:12)

He didn't have the ability, I would argue, to evolve. Y Camaro campaign he ran was like, it was 2004.

C (16:19)

But I say political operative. And like, when you look at that campaign, he still cleaned up on the endorsement side.

A (16:24)

But they don't matter.

C (16:26)

I agree, they don't matter. But it's like that moving of chess pieces, right?

A (16:29)

But it's like that scene in Austin powers where, like, Dr. Evil, whatever his name was, like, gets unfrozen and he's like, has like, the world is handling and I'm holding on for a million dollars. Like, everyone's laughing, right? That was kind of like what he was.

C (16:41)

Yeah, it's probably true. I think he was really. He knew Albany better than anything else. And so he was. Yeah, he didn't. It wasn't the job. And I think he's probably more gifted at passing really hard pieces of legislation through Albany than anybody I've ever seen. So I think at that time, he was still kind of in that mode, but he was getting bored, is the truth. Like you as press secretary, I traveled around with him to every event he did around the state. And they were all the same. You know, you go. And in part by design, because he designed them meticulously. But you go in a room, there's a bunch of elected officials who get up, who write talking points. We've written about how great Andrew Cuomo is for whatever we're announcing that day. Then he gets up and says the same thing. The room is the same people.

A (17:19)

I mean, not because we're scared of

C (17:21)

new people coming in, but without the. Trump gets up and improvises. And Trump feeds off the crowd. And Trump has a big crowd of kind of anybody who likes him. We had a control. Controlled crowd. Controlled crowd because we were scared of protesters. That was the worst thing that could have happened to Andrew Cuomo and to us was if someone in the middle of an event got up and said, I hate you, or started yelling. That was like our nightmare scenario. So it was always state employees, largely. And so they're, you know, they're clapping pro forma, but they've heard this, the same thing every time we've been there, and it just gets boring. And so I just. I think at the end of the day, he was trapped in the cycle of. He didn't want to be in the job anymore, but he also didn't know what else to do with his life, and he couldn't run for president. And so I think, you know, I speculate that that's kind of. Even though it was right off his peak in Covid, where everyone. He was the most popular politician in Americ America for a period of time.

A (18:12)

Yeah.

C (18:13)

You know, that something. Something clicked and he just. He was unable to control himself in the same way anymore.

A (18:19)

So when did you go to Uber?

C (18:20)

I went to Uber right after Cuomo's first re election in 2014. So I started with Josh in January of 2015. I was their first communications hire in New York, which was surprising given Josh's proclivity for saying crazy sooner.

B (18:33)

Yeah, but it took you so long.

C (18:35)

But, you know, and when I first got in, de Blasio was mayor. He had been mayor for about. For a year. And my initial approach was, let's go make nice with him. So we went. And I forget what we were proposing in the city, but, like, hiring recruitment for Uber drivers at nycha because it was a pretty prized economic position at the time. And there was like a couple other things, and we were just sort of pushed off politely, but just like told no until the big moment for all of us, which was when the taxi lobby proposed a cap under for vehicles and build a. Blasio said, this sounds great. I'm going to do it.

A (19:10)

Yeah.

B (19:11)

Yeah. Well, there was actually something. I mean, this is sort of like a. There was something before that also when the city wanted to review all the app updates.

C (19:19)

Yes.

B (19:20)

Do you remember that? That was the data fight.

C (19:22)

Yeah, that was right when I. That was right before I started. We had just.

B (19:26)

We got the. It was like Texas, right? No, I remember it being in the new office, so it would be 2015, but it was like a mini fight. They, like, wanted to ch app updates. Like, that doesn't really make sense. I don't think you really mean that. And they're like, oh, no, we Just want to. We don't know.

A (19:40)

Yeah.

C (19:40)

They wanted some form of our data that Travis Kalanick, the CEO at the time, was instinctively scared or nervous about. You shouldn't get it. And my thought was, you know, after talking, he was like, this is harmless.

A (19:53)

Right. I, I, Travis and I always sort of disagreed about this in general. And I, I watched Airbnb make the same. Yeah, I think wrong call. Which was if you're in the private sector and you've only ever been in it, especially in tech, data is like the most valuable currency. She's like, I'm not giving that away. The reality is the bureaucrats would have literally no idea what they were looking at or what to do with it, and therefore, like, their ability to actually harm you with it, in my view, was very limited simply because it was far too complicated for them to actually comprehend. But anyway, so Uber until when?

C (20:30)

7 and a half years.

A (20:31)

Okay.

C (20:32)

And during that time, I bounced the first communications for Josh in New York. Then I did product communications. I did corporate communications when we were going through sort of our big overhaul. And, you know, the Eric Holder Report, for those who don't know, is sort of this period of reputational crisis for Uber stuck around. Ultimately did marketing for. For drivers and couriers at the end of my time. Product marketing. So like explaining to them how to

A (20:59)

sign up, which actually useful for your later business.

C (21:02)

Yes. Which I then left briefly joined a music startup. It wasn't the right fit for me, and I was at a point in my career where I, I had been around enough environments I didn't want to be in to know that I didn't need to stay anymore.

A (21:12)

Yeah.

C (21:13)

Left started Wingspan, which is my current company. It's the goal. Our mission is public connection for the public good. And we are a civic studio that's trying to connect people to govern their government, to candidates running for office and to each other. I just generally think, especially in an age of digital isolation, the more we're using both media and video to bring people together in a way where they're going to produce something. Understand government in a newer way, which is something the mayor's kind of gifted at, is worth doing.

A (21:42)

Right. And interestingly, it kind of fits with your. Who I'm a big fan of your significant other. I like Patrick too. But. But in terms of working with Caitlyn and you know, take one second, describe her work.

C (21:54)

You ab you absolutely should. I am her number one fan. Caitlyn Lewis, who is my girlfriend, is the CEO of Work for America. It's a Nonprofit that was started about a year and a half ago. Its goal is to help local and state governments hire better. The hiring process for local governments is usually about six months, which is crazy. And even though it's one of the few jobs where you still can get a pension and really good health care, the salaries are not competitive with the private sector. And our generation has not gone into government in the same way that the generation above us did. And all those folks are retiring. And there's just these huge gaps in service, which is why 911 call centers, you can wait on hold in San Francisco when you call 911 for like 45 minutes. That's crazy. Potholes don't get filled, all of this stuff. So she's, she. One big thing she did was start Civic Match. It matches the fired federal employees who were let go by the Trump administration with local government opportunities. Certainly you can see in my description of what I want to do an influence of her work because it's, I find it pretty inspiring. We are both kind of, we love government nerds. We love people in government who are doing these kind of unsung jobs. The parts of government that are hidden from people, but if they knew about them, they would be really excited by them. Less the political side. Like I think communications from my time working, working for Bill and Andrew, where most of the time you're focused on making them look good. I think that's broken. I think that's a mistake. I think communications in government should be about service utilization. Your success metric should be, okay, we announced a program. How many people signed up for it and if they're, and if we've advertised it over and over and over and they're not signing up, well, we know the program's problematic. So we got to fix it. That's the, that should be the orientation. That's not today anywhere. Even in New York City where they're doing some sign up work through the mayor social channels, they're still focused on him. Yeah, that's the wrong orientation. The focus should be on the people getting excited about parts of government service that they don't know.

A (23:42)

That is, you know, typically not the goal of politicians. So. But it's a good segue into what you guys are doing. So you're the co founders of Smith and Moses. So which one of you is Smith and which one of you?

C (23:56)

That's a great question.

B (23:58)

I don't know.

C (23:59)

I think you, you, you would probably be Smith technically, because Smith says the

B (24:05)

dumb one is what he's saying. He's the one who needed the help.

C (24:08)

No, Smith is the more altruistic, policy oriented, you know, building one. And Moses is the kind of deviant political.

A (24:15)

Is this Al Smith and Robert Moses?

C (24:17)

Al Smith, yeah.

B (24:18)

Former Governor Al Smith, Joseph Smith and the Torah Moses.

C (24:22)

We were joking about that. If we were going to rebrand.

A (24:24)

Right. It could be a religious house.

C (24:26)

I'm a political nerd. I'm a fan of the power broker for those, so I'm ripping all this from that. But when Al Smith was an assemblyman, before he was governor, he came from Tammany Hall. He was kind of like he was an Irish immigrant. He was. He considered himself a hack and uneducated. When he goes to Albany, he reads. Instead of going out at night, which is a fun thing to do in Albany, he stayed in his hotel and read every new bill that had been introduced so that he could learn how the assembly worked. Smith, the Smith part of our AI offering analyzes every bill as they're introduced in Albany and gives you a very easy to read summary of it. That that's sort of the Al Smith part of. Robert Moses, who became his political aide when he was governor, was brilliant at seeing a bill and understanding the political ramifications, who would support it, who wouldn't, who they would have to call to oppose it. And so the other part of this program is rating bills based on their impact and their chance of passing based off of some of those inputs which you, Bradley, contributed to when we first started designing our interface.

A (25:28)

So, Josh, since you originally sort of started working on this, why don't you kind of go through what it is, why it matters, what you want to accomplish with it?

B (25:39)

Sure. So it starts that New York State has. They have an API, which is how a computer speaks to another computer that releases every bill in real time. So if an assemblyman introduces a bill, it'll appear in this feed right away. So what our system does is ingest that. I always felt like there was this idea of nobody reads the bill or there are too many bills to read them all, or the bill is too long to read it. It gets put out in the middle of the night, we have to vote on it the next day. AI Superpower is summary. It's taking a large amount of text and making it a small amount of text. That's literally where I thought this would be useful. Let's just take these bills and summarize them so people can read them every day. On a given day, the assembly and Senate will introduce anything between 50 and 100 bills when they're in session. And that's too much to read. So the system basically summarizes every bill. It talks about things like why it matters, who's likely to care, who will support or oppose, and helps you sort of glean the effectiveness of your assemblyman or senator based on that. So the first rule that you showed me is politicians want to get reelected. That's sort of their thing.

A (26:51)

I still think that get reelected.

B (26:52)

It is that. That is. That is still the case. And what are we deciding that on? Is it vibes? Is it. They come and they. They. They sound great. There's got to be an, an objective way to measure someone if they're already in the assembly or Senate. And the website aims to do that.

A (27:09)

And is the. So who's the audience? And because you just described two different things here, right. One is the how could people inside the system take an overwhelming amount of information and synthesize it in a way that they could then act as intelligently honored to the extent that that matters to them? And the other that you said was how voters could judge the efficacy of their elected officials. So what's the goal?

B (27:32)

Those are in some ways the two sides that we come from. I'm more the latter. I want to know. These guys are all running for the seat and what have they been doing the last few years? Are they good at their job? Are they not good at their job?

A (27:45)

So how do you. So I understand the first part. Right. Which is because it. That is, like you said, super power of AI on the second one. And obviously that's what we met about. But like walk us through some Matt want, like, obviously a thousand different criteria could be used to answer Josh's question. What did you guys settle on and why?

C (28:04)

So unlike perhaps your city council member, your state assembly member, your state senator, their main job is passing legislation. And so there's other things they do. They all have constituent services, etc. But that's kind of their core responsibility.

A (28:17)

Yeah.

C (28:18)

So we assign partners points for every state senator and assembly member based off of how one, how high impact the bills they introduce are, and then two, how many of those high impact bills actually get passed into law? We define impact on a couple criteria. One is just number of people it affects. So if you're proposing a bill that only affects Plattsburgh, which is a small, you know, city up in the north country, it's not as impactful as a bill that affects New York city because that's 8.7 million people. Not as. Not as impactful as A bill that affects the whole state, then the second criteria is, what is the bill doing? Is the bill renaming a street? Is it a resolution that's just declaring, you know, a day to, you know, today is Bradley Tusk day, or every day? Is every. Every day is Bradley Dust day, Or is it. Is it doing something like creating universal child care in New York City? Or is it changing our tax code so that all pied a tears are taxed higher in New York City? Is it increasing criminal penalties, which affects really all of us? Because if any of us commit a crime, it means we're in jail longer

A (29:24)

or less and impacted by what happens to the people who are committed crime, because then, you know, arguably, if they're in jail longer, we're protected from that. But we're also paying for that.

C (29:33)

Right?

A (29:33)

And vice versa.

C (29:34)

And fiscal. Fiscal impact is a big impact measure. So we judge bills on that basis, and then we estimate the chance of passage, it's a little harder because we're guessing to some degree, but we're guessing based on a couple criteria. One, who introduced it? You know, how, how. What's their track record in this session, previous sessions of passing bills into law? Two, what committee did it assign to? How powerful is the chair of that committee? How many co sponsors does it have? Are they only in one chamber or another? When in the session? Are we, you know, any bill introduced after June this year, not. Not getting passed, it's like purely for symbolic reasons.

A (30:08)

Right?

C (30:09)

And then basically, legislators get points. You know, let's say I passed a eight. A bill that is an impact of eight. It's a one out of ten score. It's passed into law, I get eight impact points.

B (30:20)

Right.

C (30:21)

The person with the most impact points is the highest rated. It is imperfect. It's still a work in progress. But the goal is to give one clear measure for every elected official at the state level in New York, in the legislature that voters can look to and say, okay, when I'm going to the polls, you know, maybe my state assembly member says they support all the things I like. Did they pass them into law or not? You know, did they do the job? Are they good at it? And it could be you dislike everything that they passed. And they're really good at it. That's good to know, too. It's just supposed to be an objective measure of their skill.

A (30:52)

And so in this, you know, your timing is good because this year we have pretty much everyone, all things up for election or reelection. So what's the plan to sort of get this in front of voters. Given that the primaries are sooner and the mo. Because of gerrymandering, most seats are determined in the primary. Like, how do you, between now and then, make this impactful? Or is this year just sort of a beta and it doesn't really matter.

C (31:25)

It's. It's certainly a side quest for both of us.

B (31:27)

We're appearing on podcasts.

C (31:28)

We are, we are, you know, we are trying to get attention out. We're also, you know, I, I. Part of my job is working with the press. So I'm definitely in the lead up to all the primaries. A lot of media, local media, will publish voter guides. My goal is to get Smith and Moses included in those voter guys the best I can.

A (31:46)

You know, I would argue just, you know, so here's them when we've thought this sort of privately as well, but like, from a. How do you get attention for this? The best thing that you're doing, I think, is the score, right? Because reporters really love it when there's a grade of some kind, right? Because then it's easy, you know, as opposed to having to sort of do something qualitative. So that's the good news. However, one, they have, they do have to believe that the criteria is legitimate enough, that it's not just you guys being paid to make some people look good and some people look bad. And then two, to me, like, no one reads voter guides. But I think that if you could get the right influencers on social to be able to sort of say, here's the Smith and Moses score for so and so, like, I would imagine, because it's again, from my perspective. And we'll talk about how much of a business this is or isn't. But what you would want is elected officials to sort of take it seriously enough that they would then try to improve their actual behavior to get a higher score, right? And that's how you guys could influence, sort of make the state actually truly better. Which means they have to think that it matters either to their election or to their ego. Right. So how are you thinking about that?

C (33:03)

So it's a. Those are all really good points, I think. One, we've briefed reporters, members of the media, the LCA in Albany, and influencers here in New York about how Smith and Moses work just to encourage them to use it to try to achieve that goal. I think, you know, that's, It's a fair point. It's like the more we can get it out, the better. I do think when people, I find, when my friends are going to vote and they don't know what they're voting about. They will often text me and be like, yeah, here's my race, who should I vote for? Because they know I'm in politics. I get that. And so like, and more and more they're going to go to AI, they're going to go to Google and they search a lot of the time. So if we can pop up in that SEO, I think that's kind of helpful. But I also, I do think the real answer for like, how do you get elected officials to be bought into this? It's media. Even in this day and age. Yeah, that's the mo. The thing that most elected officials respond to is the press.

A (33:53)

Because again, if you take like my core thesis, which is the vast majority of elected officials are desperately self loathing, insecure people who can't let the validation affirmation that comes with holding office.

B (34:04)

There it is.

C (34:05)

Now we're getting real.

A (34:06)

Right? If that's the case, then that's the election is really just solving for allowing them to keep doing something that makes them feel relevant and that how they feel while they're relevant is the kind of attention they get, positive or negative. And that's how you could really influence them. Josh, two questions. One, is there a business model here? And two, how do you think about SEO for AI platforms where you're really trying to get them to pick something up as opposed to a Google algorithm?

B (34:35)

Sure. So on the first one, is it a business? I think we're trying to figure that out right now. It's free. Free is friendly. We have a daily and weekly email that maybe a version of which could be paid for. Now we're just, it's just free. And then I think, you know, large language model optimization, like trying to get your brand mentioned in an LLM I think is a close cousin of search engine optimization. A lot of the LLMs will search the web in real time to try to get information because Google is better at indexing than, you know, OpenAI is. And so I think just following, you know, our website is, is SEO'd. It's, you know, if you search for certain bills, New York State will probably come up first. But we're in there and we have a growing Google source, you know, over time. So I think just being good at what you do tends to improve.

A (35:29)

Yeah. And ultimately, you know, back to Bachelor, the more press you guys get for the project, the more links, the more hits, the more search. So you know, we've talked about this when we met But I want to throw out there again. So two things that I'm either interested or working on and I just want to now that you guys been at this for longer how you think about it. So one is this tool that I'm building called how to create societal change where effectively where someone says I want to dance cell phones on my kids school, I want to put a stop sign my corner. It could be an, it could be an act of Congress. But I think realistically where it could be useful is at a hyper local level, maybe at a state level. Sometimes you guys are starting with New York. If I wanted to use Smith and Moses to be able to point our users when we, if, if we have any, when we launch, like hey, here is a tool that will help you analyze your idea, your issue from here's who likely is to support it, here's who's less likely to support it here all that like so the, the score for a politician in this case doesn't matter as much updated thoughts as to how we could do that together.

C (36:36)

So we, there's a couple new features we've introduced that would, that would help. The first is we've created user accounts so everyone who goes on the homepage, either using their email or creating username password can set up an account and then they can track individual bills, they can track individual legislators, all their actions, they can track just an issue agenda. So let's say they care about education, they care about cell phones in schools, they can just select education. The emails they get will only be about that. We're building features that will allow their homepage to be sorted by bills of that nature. So I see it less as a, the way, you know, they will get to be able to produce, you know, a stakeholder map each bill but it'll also allow them, let's say they get a bill introduced to the state, they can see where it's going and how its chance of passage is increasing or decreasing. I've actually briefed a few political groups on usage and that's the part that they're kind of most excited about.

A (37:30)

Right. So if we trained our model to search Smith and Moses, then when we give people a free campaign plan and we're saying here are the electives that matter, here are the different advocates matter, all that we could take your analysis, build it into our, our plan and give it to people.

C (37:48)

Yes, you could. You would get stakeholder a list of stakeholders which I still think is like very work in progress. Yes, it needs to be improved. You would. And then Also, as you're doing it, you'd be able to track. You'd be able to give them tracking for their. The legislators that they care about, what they're up to and whatever bills that they're introducing or pushing. And I would argue the exit for your tool. Like, more and more, as we see the federal government retreat from its responsibilities under the Trump administration, it's going to be hard for a new administration, Democrat or Republican, to change that. States are where it's at. Like, the city doesn't have that much power in New York. The state has all the power. And state elected officials are these kind of unknown, less attention given folks who actually hold a tremendous amount of power. If effective. If effective. And so the effective rating is kind of the piece. Also, as you're building for your users, like, here's the legislators that could introduce this bill. How effective are they? Let me choose the most effective one because they're more likely to get it through.

A (38:46)

Josh, have I already connected you to the people coding this for us or no.

B (38:50)

Or.

A (38:50)

I just gave you guys the white paper.

C (38:52)

You gave us the white paper?

A (38:53)

Yeah. So the next step is you guys are cool with it, is I'd like to, so that they can start incorporating itself. So the other thing is just a little more of an idea. But. So when I worked for Mike, one of the things that I did for him, this is what City hall, not the campaign, was. I created a campaign promises index where I went through every single thing he promised in the 2001 campaign. And this was very manual, right? I looked up, I read every transcript, every article, every editorial, every press release. There was no social media yet. And I came up with 381 things that I, in my view, that they promised to do. I put them all into a spreadsheet. And I went to Mike and said, I want to release the status of every single one of these things. And I'm actually not all that concerned where it stands. What I want to show is that you are truly transparent and you are truly accountable. Anyone else would have fired me immediately. Of course he fucking loved it. And we did it and we did it all 12 years of his. You know, I wasn't there for all of it, but first, mayoralty. And it's funny, because the Times did a story, I remember they called me and said, you know, where'd you get the idea from? I came up with it, and they were like, well, who else has done this? I'm like, I. I don't know. And, you know, again, the Internet wasn't as good back then to be able to search everything. So I was like, you guys tell me. And they did their own thing and they wrote a story saying, like, doesn't seem like anyone's ever done this before. I was hoping that we were going to start a trend. We did not. Nobody else ever did it. Which I understand because Mike is so unique. But the thought I've had over the last couple years, but again, to Josh's point, it's the tools weren't there to make it worth doing. It was, well, couldn't we do it to them, right? If they won't do it, couldn't we use AI to basically say, here's what you promised, here's what you've done. And I think what you guys have built is a key step in that, right? Like AI should be able to pretty easily read every tweet, every release, every everything and synthesize it into a list. Then it's sort of like, what do they do and how do you judge it to your point? Like if you just introduce something that never goes anywhere to check a box, how much should that really count? You know, did you actually sacrifice political capital to get this thing done? You guys see a world where you could take the idea that we had and then what you've done and kind of just create a way to hold elect officials accountable or even incorporate it into Smith and Moses maybe.

C (41:18)

I love this and I definitely see it and I think what I like about it is tying it to outcomes, actual outcomes. So not introductions, not promises. It certainly work. And the other part I think that you'd have to do for the elected official to care, to your point, is get buy in from the media, make it simple so anyone can understand. But the current mayor made a series of very specific promises that are easy to track, right? Like the bus is free. Our bus is free and fast right now. Right now. There are not necessarily faster everywhere. They're certainly not free. You know, do we have universal child care? We're gonna get 2,000 slots next year. Then we're gonna get funding for one year. Is it unit? Like, is it universal by the definition? Anyone can the advocacy of the right.

A (42:03)

I think the system that I had works a little better on the executive branch side because there's outcomes, right?

C (42:09)

Legislators is right.

A (42:10)

You introduce a bill, someone said, well, that's what I can do. Yeah, right. So all other states, right? So I agree with your premise. Although just for the listeners to understand a little more here, when Matt said cities have a lot less power than states. He's talking about policymaking, legislation, things like that. On an operational standpoint, that's different, right?

C (42:34)

100%.

A (42:35)

But most of that is not. It's just the mayor of wherever running it and having people to execute. Now that, Josh, that you've built this model and system, how hard or easy is it to then get the next 49 states into it?

B (42:52)

Many states have similar API feeds like New York does. I think not all of them do, but there's some infrastructure like open source infrastructure that people have built that sort of bridges, that gap so that this sort of does exist basically for every state. That is the feedback. So not. Not crazy.

A (43:10)

A sense of when that might be something you guys turn Smith and Moses.

B (43:14)

I don't know. I don't know.

C (43:15)

Our first. Yeah, our first thought was like, can we make this work in the place we know, which is New York, where, you know, I can judge a little bit how good these grades are because I sort of, I know I worked in Albany for three years. I know how it works. Right. If we were in Montana, I'd be like, I don't know, you know, like I don't know who these people are. I don't know what they're. Whether it's good or not. So if once we get the model down, then it's a question and then is there directional.

B (43:39)

I think directionally I'm more interested like right now it ingests the New York State data. But if the governor got up tomorrow and said Bill 1234 has no chance, I would rather, I will veto it or whatever. Our system doesn't. Doesn't hear that yet. It doesn't ingest real time media in that way. And so I'd rather go, what is it, an inch wide, a mile deep than the opposite. Like really nail New York. So it's reading all the papers, it's reading all the tweets. It's aware of what's happening in reality. Because right now the LLM is sort of using some just generalized logic about who cares about this. It's not finding a quote in the press about who cares about it. So I think I'd like to get New York so good that you could really bet on, you know, the rating of a bill is, is, is fixed. Like it happens. It's, it's an 8 out of 10 forever. The likelihood should in theory update, but hourly or every day because things change on the field, the date moves forward, maybe somebody says something right, whatever. So I'd rather nail New York so definitively Than, you know, sort of first and then think about other states.

A (44:49)

Right. And then do you see a world where the system can learn as it goes on so that, you know, you can. The. The. I mean, you guys are setting criteria. You have to start with something, but then you can sort of can without you guys doing it manually. Is there a world where the system says like, okay, in, you know, a bill introduction that gets 32 CO sponsors should be seen differently as a bill that gets two co sponsors or whatever.

B (45:15)

There's definitely, like on the to do list, like a back test, you know, in. In sessions past, what were the indicators that something was going to happen or not happen? Sort of a. That's like a big job, but that would be the way to do it. To sort of see, like in another session what happened that ended up making the outcome as a success or not that we're sort of figuring out how to do.

A (45:37)

Cool. When does it launch?

C (45:39)

It's live now.

B (45:41)

We have hundreds of subscribers.

C (45:43)

You just go to smithmosis.com you can sign up for our emails. You can create a user account, which I strongly encourage you to do, which allows you to narrow what you're tracking. So if you are a bike enthusiast and you only care about bikes, you can do that. If you're tech oriented and you want to just know about tech issues that are coming through the legislature, you can do that. You can track individual legislators. You can compare them based on their effective rating. So a fun thing. We have a very lively congressional race

B (46:10)

like Schmiker versus Schmallexplore.

C (46:13)

You can compare those two assembly members to see how their effective rating is. Spoiler alert. They're basically the same because very talented legislation.

A (46:21)

The sort of sad part is, you know, I am for Micah because he's been a good friend of mine for many years. But, like, you have two of the most talented people that happen to be running against each other. Yeah.

C (46:31)

And this is a thing that happens often in politics where the incentives are a little bit perverse in that way. It's unfortunate because it's like you want smart. You want more smart people, not fewer smart people in more of these positions. It doesn't always work out that way.

A (46:45)

All right, well, hopefully, though, what you guys are building can contribute over the long term to that happening more.

C (46:51)

Hope so. And thank you so much for having us. Yeah, always.

A (46:54)

Thank you for helping, but thanks for doing this, too. This is a cool service to the people in New York.

C (46:58)

Thank you for helping make it better and participating in building it.

A (47:01)

All right. Everyone. If you're interested in what we just spent an hour talking about, go to smithmoses.com Josh Matt, thanks for being here.

B (47:07)

Thanks for having us. Thank you.

A (47:11)

Firewalls recorded at my bookstore, PNT Netware, located at 180 Orchard street on the lower east side, the of Manhattan. We'd love to hear from you with questions, feedbacks or idea for a guest. Just email me at Bradleyirewall Media or find me on LinkedIn. And to keep up with what's on my mind in my latest writing, please follow my new substack@bradleytus substack.com thanks again for listening.