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Speaker 1: Welcome. It is Verdict was centered Ted Cruz, Ben Ferguson

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Speaker 1: with you, and it is one am in the morning

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Speaker 1: Eastern time, after the State of the Union. I want

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Speaker 1: to be very clear that I am doing this show

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Speaker 1: in protest right now because I was on a plane. No, no,

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Speaker 1: let me let me rephrase that center true or fosse.

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Speaker 1: You and I hung out yesterday in your office.

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Speaker 2: We did, and you were in DC, and I can't

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Speaker 2: help it that you fled Washington during the State of

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Speaker 2: the Union. And listen, karmes A and so when you

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Speaker 2: decided you were a little girl and you had to

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Speaker 2: get out of town because the Democrats getting mad at

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Speaker 2: the president were scary. Yeah, there was a consequence, which

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Speaker 2: is for those who are watching on YouTube, a coup

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Speaker 2: is a courage. The original co host of Verdict has

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Speaker 2: returned and seize the seat. To be clear, he has

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Speaker 2: relegated mister Ferguson to appearing as a little box on

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Speaker 2: a monitor.

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Speaker 3: He banished Ben. I saw it, not just the seat,

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Speaker 3: but I saw this cigar, and I said, this is

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Speaker 3: pretty good. And this has actually become something of a tradition.

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Speaker 3: I've noticed it. I've only ever been to two stags.

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Speaker 1: By the way, if only TC would tell us that

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Speaker 1: there is a tradition, then I wouldn't have gone on

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Speaker 1: a plane at two o'clock this afternoon leave Washington, d C. Like,

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Speaker 1: think about this, hey, Ben, we should have cigars. I

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Speaker 1: have to say the union and do the show here.

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Speaker 1: Great idea, I'll change my flight. That is how normal

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Speaker 1: people would have done this. Michael a year in advance.

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Speaker 2: This happened late on the fly, and so this afternoon

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Speaker 2: Michael texted me and said, hey, you want to grab

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Speaker 2: cigars after everything tonight? And I was like, well, we

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Speaker 2: have to do the pod, but aha, I have an idea.

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Speaker 2: And I didn't really want to do the pod and

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Speaker 2: finish at two in the morning and then have cigars,

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Speaker 2: and so I'm like, we'll combine it. And by the way,

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Speaker 2: Daily Wire does this great. What is it late night?

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Speaker 2: What is it called backstage? Backstage? So I've done several

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Speaker 2: times done backstage with them where they sit around and

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Speaker 2: drink scotch and smoke cigars, and so I said, let's

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Speaker 2: bring some backstage. This is like a This is like

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Speaker 2: a Marvel Universe crossover, where like Daily Wire and iHeart

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Speaker 2: are intersecting.

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Speaker 3: This also, really it's kind of a double verdict tradition

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Speaker 3: in that two years ago, Yes, I came to my

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Speaker 3: first Date of the Union address. It was Biden State

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Speaker 3: of the Union, the one where they injected him with

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Speaker 3: whatever they injected him with, and he yelled for ninety

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Speaker 3: two minutes.

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Speaker 2: Yeah.

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Speaker 3: And then afterward, actually before i'd set it up, I said, hey, Senator,

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Speaker 3: I happened to be in town. Hate to pressure you

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Speaker 3: for a cigar. Same thing. He said, well, okay, we

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Speaker 3: can have a cigar, but you got to do the

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Speaker 3: podcast first. I said, okay, well that that'd be a

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Speaker 3: lot of fun. And so of course it's you know, midnight,

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Speaker 3: one o'clock in the morning. And this really takes us

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Speaker 3: back because when Verdicts started, it was always one o'clock

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Speaker 3: in the morning, and it was actually not all that

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Speaker 3: far from here in Washington, d C.

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Speaker 2: Though I noticed the digs have improved a little bit.

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Speaker 2: So we're in a high falutin cigar bar in DC.

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Speaker 2: Because it turns out it's actually complicated to find a

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Speaker 2: studio that will let you smoke a cigar.

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Speaker 1: I don't get to light my cigar. That's the part

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Speaker 1: that I'm really chapped about. I did look at my

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Speaker 1: wife and send her you know Anna well, and I

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Speaker 1: was like, what are the chances, for the sake of

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Speaker 1: the show in authenticity, I could smoke said cigar. I

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Speaker 1: literally did not get an answer. I got the look.

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Speaker 1: And when you're married, you guys both know the look.

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Speaker 1: Each one of our wives all have a look that

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Speaker 1: they give you. And I was like, Okay, I got it.

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Speaker 1: I know how this is.

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Speaker 2: So Ben you are thoroughly domesticated, yes, yes, and it

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Speaker 2: doesn't pune your manhood, yes, but and I'm not going

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Speaker 2: to tell a story on myself. So when Heidi and

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Speaker 2: I were engaged in an apartment in DC, and I

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Speaker 2: would host poker games, and at the poker games, we

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Speaker 2: would smoke cigars and we do it at my dining

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Speaker 2: room table, and my buddies that would come over and play,

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Speaker 2: they'd be like, dude, how does Heidi let you smoke

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Speaker 2: cigars inside? And I was in my twenties and stupid,

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Speaker 2: so I'm like, look, if you're the man of the

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Speaker 2: house and you want to smoke a cigar, you smoke

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Speaker 2: a cigar in your damn house, right, And I said

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Speaker 2: it with all the bravado of a young idiot. Yeah.

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Speaker 1: Meanwhile, he didn't own set house. It was an apartment,

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Speaker 1: but like this store.

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Speaker 2: Yeah. So then we get married. We actually get married

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Speaker 2: twenty five years ago May twenty seventh, two thousand and one.

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Speaker 2: That's our twenty fifth anniversary.

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Speaker 3: Wow.

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Speaker 2: And we come back from our honeymoon, and shortly thereafter

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Speaker 2: I'm hosting a poker game and Heidi says, get the

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Speaker 2: damn cigars out of the apartment. You will never smoke

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Speaker 2: another one inside again. And in twenty five years I

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Speaker 2: never have. And so when I say, that's another way

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Speaker 2: of saying, you're actually married.

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Speaker 3: Aren't we all? Aren't we all? In a way?

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Speaker 2: So all right, So, Ben, Ben, what do you think

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Speaker 2: of the damn State of the Union?

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Speaker 1: I actually think it was the best speech Donald Trump

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Speaker 1: has ever given. I actually thought it was one of

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Speaker 1: the most real and authentic responses from him to the

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Speaker 1: Democrats and how they were acting. I love that he

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Speaker 1: was like, you can't even stand for that. You won't

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Speaker 1: even say say.

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Speaker 2: You guys are crazy.

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Speaker 1: Yeah, you guys are crazy.

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Speaker 3: Line, And it came like the third most incredible line.

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Speaker 3: I mean, there were a lot of them, yeah, but.

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Speaker 1: But it came what stood out TV in an amazing way,

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Speaker 1: did it? Yeah? Oh, I mean it was just his look,

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Speaker 1: his demeanor. He was looking over at them. I mean,

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Speaker 1: you were there obviously, so it's going to feel different

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Speaker 1: to you. But like I'm watching, I'm going that line

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Speaker 1: landed and I think the American people probably saw it

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Speaker 1: and They're like, wow, this is going to be really good.

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Speaker 3: So I'm sitting there. It was very kind of Speaker

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Speaker 3: Johnson to invite me, and I'm sitting over the Democrats,

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Speaker 3: so I got a prime view of the Democrats. And

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Speaker 3: the first line that really brought down the House was

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Speaker 3: when President Trump looked over and it was beautifully written

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Speaker 3: and beautifully executed. He looked over, he said, Okay, I

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Speaker 3: want everyone to stand up if you agree with the

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Speaker 3: statement that America should protect Americans or something to that

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Speaker 3: effect and over illegals. Yes, and they refuse to stand

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Speaker 3: political malpractice the likes of which one has rarely seen.

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Speaker 3: And it was a brutal moment. He totally took advantage.

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Speaker 2: Then, so that moment will be played in a million campaigns.

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Speaker 3: Yes.

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Speaker 2: Yes, And by the way, it was the longest sustained

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Speaker 2: applause of Republicans. We stood, and we applauded, and we applauded,

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Speaker 2: and he just looked over. He stepped away from with

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Speaker 2: amazement watching them, and the ad rights itself. They're for

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Speaker 2: illegals and not for you. And they were given that choice,

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Speaker 2: do you stand with Americans or do you stand with

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Speaker 2: illegals and the entire party? No, we're the party of

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Speaker 2: illegal aliens and not the party of Americans.

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Speaker 3: It was shocking. So then he doubles down on I'm

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Speaker 3: skipping around a little bit in time because it escalated

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Speaker 3: well by the way.

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Speaker 1: He noticed a trend. He noticed, this is going to

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Speaker 1: be the trend of my speech, Like I don't think

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Speaker 1: he planned it this whole, Like you guys aren't going

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Speaker 1: to stand for that. It was the moment and then

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Speaker 1: it hit and then it was like, I'm going to

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Speaker 1: keep doing this tonight to show Americans how crazy these

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Speaker 1: guys are on the left. That's how it came across

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Speaker 1: on TV.

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Speaker 3: Well, he landed it on the transgender ideology. Yes, kid

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Speaker 3: who had been transed and had destroyed his family, and

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Speaker 3: then the kid finally ended up in the right place,

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Speaker 3: and the he said, isn't that wonderful? The family's reunited

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Speaker 3: and everyone's flourishing, and the Dems wouldn't stand. And that

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Speaker 3: was when he dealt the blow. He said these people

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Speaker 3: are crazy, and that that too lit it up now

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Speaker 3: where it got a little dark. But it was the

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Speaker 3: same strategy. It was the same tactic, I suppose is

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Speaker 3: when he started bringing up violence, and he obviously turns

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Speaker 3: to Erica Kirk, this national hero, this perhaps the most

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Speaker 3: sympathetic figure in the entire country, certainly up there, and

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Speaker 3: the Democrats didn't want to stand for Charlie. They didn't

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Speaker 3: want to stand for Erica again, that itself is disgraceful.

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Speaker 3: But he even gave them it out. He said, we're

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Speaker 3: a country where we say in God we trust, and

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Speaker 3: we reject political violence of all kinds. And I was

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Speaker 3: looking over some Democrats stood for that.

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Speaker 2: I'd said more than half on the political violence. I looked,

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Speaker 2: and it was probably sixty seventy percent think about that.

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Speaker 2: But a third did not.

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Speaker 3: A third did not, third would not stand for we

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Speaker 3: reject political violence of all kinds. It was I felt

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Speaker 3: a disaster of optics for Democrats and disaster of morals well.

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Speaker 2: And on the we don't stand for political violence. The

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Speaker 2: reason two thirds stood is Schumer stood. By the way,

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Speaker 2: have you ever noticed how much Chuck Schumer looks like

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Speaker 2: the villain and the Smurfs? But what's what's the name?

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Speaker 2: I don't remember the name of the villain? Like the

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Speaker 2: curved over like like you know, he's hunched, he has

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Speaker 2: kind of a hunchback.

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Speaker 3: Maybe Penguin from Batman was what I got.

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Speaker 2: Yeah, yeah, but he sort of.

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Speaker 1: No, I couldn't agree with you more. By the way,

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Speaker 1: you guys are in there, so you may not know this,

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Speaker 1: So I may break news to you. Did you guys

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Speaker 1: see what Rashid Tillie was chanting? Wow? Everyone was chanting USA, USA.

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Speaker 1: At one of the points in the speech, she was

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Speaker 1: chanting kkk kkk kkk.

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Speaker 2: Really yes, well, you know Christon advertising credit credit.

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Speaker 1: For her you guys, I don't know if you can see,

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Speaker 1: but let's be our good friend. Steve Guests put it

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Speaker 1: out there. Watch Democrat representative to leave. She's chanting kkk

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Speaker 1: while everyone else is cheering USA.

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Speaker 2: Well. The KKK was founded by Democrats. It was almost

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Speaker 2: exclusively populated by Democrats. Nathan Bedford Forrest, the founder of

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Speaker 2: the clan, was a delegate a delegate to the DNC

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Speaker 2: National Convention in eighteen sixty he was a national delegate.

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Speaker 2: And you look at the Klan was founded by Democrats.

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Speaker 2: Jim Crow. Laws were founded by Democrats. Segregation was enforced

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Speaker 2: by Democrats. They have been the party of racial bigotry

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Speaker 2: the entire history. And by the way, our party, I mean,

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Speaker 2: we often refer to our party as the Party of Lincoln,

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Speaker 2: but we were literally founded to abolished slavery, right, That's

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Speaker 2: why the Republican Party came together. And by the way

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Speaker 2: we did. The first Republican president is who signed the

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Speaker 2: Emancipation Proclamation.

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Speaker 3: Well, you know on racial animus and Rashida Talib did

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Speaker 3: you see. I don't know if you caught this, but

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Speaker 3: when President Trump said, what a wonderful thing. We released

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Speaker 3: all the hostages. We got the ostage released, both dead

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Speaker 3: and alive. We returned even their remains, and most people

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Speaker 3: stood up. I looked Ilhan Omar and Rashida Talib were

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Speaker 3: sitting down.

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Speaker 2: Yep. Yeah. And by the way, mean at one point

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Speaker 2: they heckled when there was a reference to the end

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Speaker 2: of the war in Gaza. They heckled and screamed genocide.

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Speaker 2: I mean, that's that's who their party is.

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Speaker 1: Well, and if you look at tonight there was four

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Speaker 1: Democrat responses like, that's not good for your party when

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Speaker 1: you're that broken.

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Speaker 2: Four Who were the four?

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Speaker 1: So you had one in Spanish, you had one that

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Speaker 1: was a progressive radical, you had one that was like

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Speaker 1: at the next level Manter, and then you had the

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Speaker 1: Virginia governor. You had four official res.

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Speaker 2: Sorry, I'm gonna have to disagree with you. I don't

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Speaker 2: even know who they were. But there are four who

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Speaker 2: were progressive radicals.

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Speaker 1: Well, I agree with you. Yes, I'm giving you their

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Speaker 1: official statement, but they literally had Hey, depending on how

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Speaker 1: crazy you are, if you're a Marxist, socialist, communist, or

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Speaker 1: a radical lefty or like the transgender, or maybe just

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Speaker 1: like a normal Democrat, here's your all of your responses

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Speaker 1: for you, and we'll have all of those for you.

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Speaker 2: So right after the State of the Union, I did Hannity,

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Speaker 2: and as I was sitting there waiting to go on,

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Speaker 2: Fox wouldn't put Hannity on air until Spamberger finished her response.

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Speaker 2: So I sit down and put my earpiece in and

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Speaker 2: it's just her voice screeching and loud. Yeah, And I'm

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Speaker 2: turned to Handy and I said, Sean, I haven't led

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Speaker 2: nearly a wicked enough life to deserve to listen to this.

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Speaker 2: As I just turned the volume off, I'm like, I can't.

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Speaker 2: There's just a limit to how much pain I can endure.

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Speaker 3: But you know what's very telling about Spanberger is you

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Speaker 3: had Andy Bisheer come out, who is a serious presidential candidate,

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Speaker 3: Kentucky governor. Yeah, and he said spam Burger is the

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Speaker 3: model for Democrats in the midterms, which means translation will run.

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Speaker 3: They will run as moderates.

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Speaker 2: It means live, don't lie.

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Speaker 3: They'll run as moderates, and they will immediately enact the

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Speaker 3: most radical leftist agenda you could maybe imagine.

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Speaker 1: I love by the way. I know you're a man

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Speaker 1: of the people and you do all of your own

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Speaker 1: yard work. But if you if you lived in Virginia's

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Speaker 1: crazy wearing French cuffs, that would be only that guy

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Speaker 1: right there. I just want to be talking the one

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Speaker 1: where the big cloud of smoke that just went up

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Speaker 1: in the air, that would be that guy's cufflings. Yeah,

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Speaker 1: that's the one there, so there there.

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Speaker 2: Look, it is impressive because at Yale he wore a cravat.

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Speaker 3: I'm going more populous as I age, and I wish Michael.

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Speaker 1: Had to sign it because before we knew what the work.

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Speaker 2: But I'm also impressed because Ben att old miss never

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Speaker 2: wore pants, so so we're kind of reaching a kind

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Speaker 2: of middleman down actually.

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Speaker 1: A man of the people, a man of product. Gucci.

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Speaker 1: It just it is. It is what it is.

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Speaker 3: No.

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Speaker 1: But like in Virginia, they've gone so crazy. They're they're

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Speaker 1: they literally have laws written right now that she's in

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Speaker 1: favor of to ban gasoline powered weed eaters and blowers.

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Speaker 1: And then they're putting a ten percent tax on electric blowers,

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Speaker 1: so they're going to charge even more to be green.

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Speaker 1: That's Virginia.

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Speaker 2: I love that the President brought up that to shovel

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Speaker 2: snow in New York under multiple IDs, you need two

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Speaker 2: forms of ID, which I actually had been advising. I

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Speaker 2: think humor is a really powerful way to drive this point.

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Speaker 2: And I think that and also the fact that John

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Speaker 2: ossoff to get to his rally against photo I D.

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Speaker 2: For voting, you had to show an.

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Speaker 1: Idea, you had to photo, you had to show vote

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Speaker 1: I D. Yeah, this kick.

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Speaker 3: Was the key, I mean, really the reason that the

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Speaker 3: State of the Union succeeded. And I agree it was

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Speaker 3: one of Trump's best speeches. The Warsaw Each in the

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Speaker 3: first term was also an excellent speech, but this was

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Speaker 3: up there, and I think the reason it succeeded was

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Speaker 3: the President had to reassure voters who voted for him

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Speaker 3: on mass you know, he won the popular vote. He

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Speaker 3: had to reassure them that we are still the party

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Speaker 3: of normal, of safety, of flourishing, of sanity, of sanity

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Speaker 3: where I think some voters you have this question after

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Speaker 3: the Minneapolis immigration enforcement Why is it that voters still

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Speaker 3: support mass deportations but oppose ice supporting people. You know,

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Speaker 3: that's kind of a contradiction. Why is it that the

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Speaker 3: fundamentals of the economy are looking pretty good? You know,

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Speaker 3: record I sed, stock market pretty good, inflation, pretty good,

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Speaker 3: job numbers, pretty good. GDP could have been better if

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Speaker 3: not for the government shutdown that the Dems gave us.

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Speaker 3: Why is it that they're a little the voters are

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Speaker 3: worried about the economy, but the economy seems to be

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Speaker 3: doing well. It's this fear that we're in a precarious

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Speaker 3: mone moment, and so I think both sides went into

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Speaker 3: this saying we want to be the party of stability,

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Speaker 3: of security of normal flourishing. That's why Hakim Jeffries told

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Speaker 3: the Democrats, hey, be cool and if you can't be cool,

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Speaker 3: don't show up.

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Speaker 2: You know, I think for Soyle Green got shot thrown out.

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Speaker 3: Al Green couldn't resist.

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Speaker 1: At least at least he had a big sign that

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Speaker 1: he got to walk around with, right he felt he

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Speaker 1: felt just.

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Speaker 2: So in his signs said blacks aren't apes. Yeah, and

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Speaker 2: I turned. I was sitting next to Todd Young and

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Speaker 2: I said, wow, is ow Green protesting Gavin Newsom? Yeah?

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Speaker 3: Yeah, yeah, look like it.

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Speaker 2: By the way, Gavin Newsom, he's like the perfect Democrat

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Speaker 2: made in the laboratory. An idiot.

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Speaker 1: He sayscis open racist? Yeah, he says racist.

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Speaker 2: He goes in front of a crowd of African Americans

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Speaker 2: and goes, I'm just like you, You're stupid, and I

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Speaker 2: am too.

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Speaker 3: Unbelievable and I can't what.

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Speaker 2: I got a nine to sixty on the sat which,

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Speaker 2: by the way, Michael got a nine sixty on the

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Speaker 2: verbal portion of his set. And yes, I know it's

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Speaker 2: only eight hundred.

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Speaker 1: But but but still, yes, I love that you just

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Speaker 1: had to geek out and show the giks that you

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Speaker 1: know the Max is an eight hundred. There, to be clear,

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Speaker 1: I can't remember I took the damn thing, and I

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Speaker 1: can't remember what.

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Speaker 2: Did anyone doubt I was a geek?

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Speaker 1: Yeah, that's I just we have to remind you, though,

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Speaker 1: every once in a while.

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Speaker 2: Let's be clear on things like that. I popped, Michael,

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Speaker 2: mostly because my own vulnerabilities are so glaring on that.

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Speaker 3: No, listen the admission rate for Princeton. I think.

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Speaker 1: Let's let's be clear. Both of you know your scores

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Speaker 1: right by heart. What you made? So what were you? Michael?

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Speaker 1: Don't lie?

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Speaker 3: It was higher than Gavin Newsom's. I'll tell you that.

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Speaker 2: No, what was it?

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Speaker 1: I want to know. I want to know what it was.

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Speaker 3: Do you want to know the irony. I'll tell you

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Speaker 3: the irony of my essay?

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Speaker 1: Oh, I can't. This is this is him delaying the brilliance.

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Speaker 1: Keep going.

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Speaker 3: I did. I did get on the math and the verbal.

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Speaker 3: I got a perfect score.

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Speaker 1: That's what I was.

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Speaker 3: However, you don't want to know the irony. There was

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Speaker 3: at that time the writing component. There was a writing

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Speaker 3: thing that they added. It was kind of optional or experimental.

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Speaker 3: And the funny thing is I did not get a

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Speaker 3: perfect score. I actually don't remember the exact it was less.

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Speaker 3: It was the six eighty or something. But the funny

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Speaker 3: thing is that's the thing I went into and my

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Speaker 3: most famous book has no words in it. So it

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Speaker 3: ended up it ended up working out just fine.

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Speaker 2: Uh Newsome, I am going to decline to answer on

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Speaker 2: the advice accounts, oh wow, because I am in elected

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Speaker 2: politics and running around like squawking about your SAT score?

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Speaker 1: Did you have two three categories? Like Michael, I just

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Speaker 1: want to know what cant.

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Speaker 2: I did not any of that. I did not and

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Speaker 2: I did well on the test. But I am I'm

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Speaker 2: just telling you I may not know much about politics,

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Speaker 2: but I am quite certain it is dumb as hell

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Speaker 2: you say this was my SAT score?

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Speaker 1: Like to prove how much of a man of the

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Speaker 1: people I am. I walked in and took the test.

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Speaker 1: I forgot my calculator and I looked at the lady

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Speaker 1: that does the test, and I said, what is the

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Speaker 1: minimum for NCAA requirements? Can I do it without a calculator?

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Speaker 1: And she goes, I'm intrigued to see if you can.

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Speaker 1: And I was above the NCAA minimum without a calculator,

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Speaker 1: and I took it once and the score came in,

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Speaker 1: and my mom was furious when it came to mail.

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Speaker 1: She's like, you're taking it again. She was so mad.

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Speaker 1: I forgot my remember the TI eighty three or whatever

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Speaker 1: it was like, you know, like the calculator you took

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Speaker 1: with you. And I was like, I forgot it that.

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Speaker 1: My mom's an educator. She was like, you're taking it.

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Speaker 1: I was like, no, I'm not. I'm above the minimum

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Speaker 1: for NCAA requirements. That's all I care about. And that way,

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Speaker 1: I took it once.

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Speaker 2: All right, So I'm going to tell you sat lsat story.

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Speaker 2: So when I show up at college. My first job,

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Speaker 2: I worked at Princeton Media Services, videotaping things and like

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Speaker 2: like a run and operate a video camera and like

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Speaker 2: videotape all sort different programs and things. And that paid

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Speaker 2: either seven or eight bucks an hour. And then I

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Speaker 2: got hired by the Prince to review to teach the SAT,

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Speaker 2: which was a much better job because it paid fifteen

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Speaker 2: bucks an hour. And so I'm like, hot, diggity damn,

400
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Speaker 2: I could do that math and fifteen is better than seven.

401
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Speaker 2: So so for like a year or two I taught

402
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Speaker 2: the SAT. I guess a year and then I'm like, wait,

403
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Speaker 2: there's no margin in teaching the SAT. I've already taken it.

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Speaker 2: And I knew I wanted to go to law school.

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Speaker 2: So I went to the course and said, hey, can

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Speaker 2: I teach the l SAT? And so they paid me

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Speaker 2: to train me to teach the l SAT, which was

408
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Speaker 2: useful because I had to, in fact teach the l set.

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Speaker 2: So when I was a sophomore in college, I was

410
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Speaker 2: teaching the l SAT and the students would say, well,

411
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Speaker 2: what score.

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Speaker 1: Did you take daycare right now?

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Speaker 2: Well, no, no, it was there were real classes. But

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Speaker 2: the hysterical story is, so I taught the l SAT

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Speaker 2: for a year and then so Junie year year, we're

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Speaker 2: taking the l set And you guys both know my

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Speaker 2: college roommatee. It was my law school roommate, and other

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Speaker 2: than Heidi, my best friend of the world. David Panton, Yeah, Jamaican,

419
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Speaker 2: incredibly talented, became Barack Obama, was the first black president

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Speaker 2: of the Harvard Law Review. David was the second black president

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Speaker 2: of Harvard Larview. So but when David and I are

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Speaker 2: in college, we're both taking the l set. The night

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Speaker 2: before the l set, David and I like complete morons,

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Speaker 2: did I mention that we were like nineteen or twenty.

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Speaker 2: I guess twenty. We stayed up all night playing Nintendo.

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Speaker 2: We literally did not sleep. We pulled an all nighter

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Speaker 2: playing Mario Brothers on Nintendo.

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Speaker 1: The Bistelle check out by the way, OK.

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Speaker 2: The l set was in Newark, so I had my

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Speaker 2: first car was a green seventy eight Ford Fairmont. So

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Speaker 2: I drove us to Newark. We take the l set.

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Speaker 2: It was at eight am. So we leave at like

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Speaker 2: six six thirty go sit for the test. It's like

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Speaker 2: four hours or so. So we're coming home, coming back

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Speaker 2: to college at like one in the afternoon, and we're

436
00:22:05,560 --> 00:22:07,439
Speaker 2: driving back and I said, so, David, how did it go?

437
00:22:08,760 --> 00:22:11,560
Speaker 2: And he said, well, during one of the sections, I

438
00:22:11,600 --> 00:22:16,640
Speaker 2: put my head down and fell asleep, and he said,

439
00:22:16,640 --> 00:22:19,359
Speaker 2: I woke up with two minutes left and I just

440
00:22:19,400 --> 00:22:22,399
Speaker 2: filled out B for every question. And he turns to

441
00:22:22,400 --> 00:22:23,959
Speaker 2: me and says, do you think B is the right answer?

442
00:22:25,119 --> 00:22:27,880
Speaker 2: And so it turns out you can cancel your LSAT

443
00:22:27,920 --> 00:22:30,919
Speaker 2: score on the spot if you want to see what up?

444
00:22:30,920 --> 00:22:33,639
Speaker 2: And just canceled a score. That's the poor guy had

445
00:22:33,640 --> 00:22:35,360
Speaker 2: to take it again. And then he did. He did well.

446
00:22:35,400 --> 00:22:37,679
Speaker 2: The second time he took it, but he literally I

447
00:22:37,800 --> 00:22:41,719
Speaker 2: laughed so hard I almost crashed the car, but I

448
00:22:41,800 --> 00:22:44,080
Speaker 2: ended up keeping him up all night and making him

449
00:22:44,080 --> 00:22:45,880
Speaker 2: fall asleep during the elbe What if all.

450
00:22:45,840 --> 00:22:47,919
Speaker 3: The answers were be they could have been, he might

451
00:22:48,000 --> 00:22:52,040
Speaker 3: have missed out on the perfect score score. The Newsome

452
00:22:52,119 --> 00:22:54,520
Speaker 3: thing is is really frustrating because right now he is

453
00:22:54,560 --> 00:22:57,639
Speaker 3: the leading candidate for the Democrats, I think, without question,

454
00:22:57,880 --> 00:23:02,800
Speaker 3: and I'm the Munich Security Conference. Newsom's still the leading candidate.

455
00:23:03,240 --> 00:23:05,440
Speaker 3: And on the one hand, he has these social media

456
00:23:05,480 --> 00:23:10,800
Speaker 3: posts where he's sitting there performatively reading Beloved by Tony Morrison,

457
00:23:11,040 --> 00:23:12,679
Speaker 3: performatively reading all these books that.

458
00:23:12,680 --> 00:23:15,840
Speaker 2: Are by the way, are you aware that Newsom let

459
00:23:15,920 --> 00:23:19,040
Speaker 2: himself on fire in a social media exchange about Verdict?

460
00:23:20,320 --> 00:23:20,639
Speaker 1: No?

461
00:23:21,480 --> 00:23:24,359
Speaker 2: So so coming back from Munich, we did. We did

462
00:23:24,400 --> 00:23:28,440
Speaker 2: a whole show on Munich, lighting up AOC and lighting

463
00:23:28,520 --> 00:23:33,800
Speaker 2: up Newsom and Newsom, and Munich said Donald Trump is

464
00:23:33,840 --> 00:23:36,359
Speaker 2: the first president in history to federalize the National Guard,

465
00:23:37,640 --> 00:23:44,560
Speaker 2: and so on Verdict, I said, Gavin Newsom is historically illiterate. Yes, uh,

466
00:23:44,600 --> 00:23:48,399
Speaker 2: And actually you talked about it, defended your use of

467
00:23:48,440 --> 00:23:53,479
Speaker 2: the English language properly and so I said that, and

468
00:23:53,520 --> 00:24:01,520
Speaker 2: then he tweeted out he said, calling someone who's dyslexic

469
00:24:02,160 --> 00:24:08,560
Speaker 2: illiterate is a new low, even for cruise. And mind you,

470
00:24:08,600 --> 00:24:11,600
Speaker 2: who knew he was dyslexic. I didn't know that until

471
00:24:11,640 --> 00:24:12,560
Speaker 2: he sent out his tweet.

472
00:24:13,400 --> 00:24:16,080
Speaker 1: Yeah for a guy that then also claims in a

473
00:24:16,080 --> 00:24:18,080
Speaker 1: white podcast, so he can read a three hundred page

474
00:24:18,080 --> 00:24:20,520
Speaker 1: book in two hours. Don't forget that came out yes

475
00:24:20,560 --> 00:24:23,320
Speaker 1: as well, So so much for being majorly dyslexic.

476
00:24:23,400 --> 00:24:28,600
Speaker 2: Right, But then, so we had we actually had twin responses.

477
00:24:29,440 --> 00:24:32,600
Speaker 2: So my staff came up with a response with a

478
00:24:32,640 --> 00:24:39,639
Speaker 2: gift from Zulander, and I wrote a response and said

479
00:24:40,280 --> 00:24:43,720
Speaker 2: something like I didn't say you couldn't read, you clown,

480
00:24:44,080 --> 00:24:48,119
Speaker 2: I said you were historically illiterate because you apparently have

481
00:24:48,280 --> 00:24:50,960
Speaker 2: no idea about the civil rights movement and the fact

482
00:24:50,960 --> 00:24:55,280
Speaker 2: that Eisenhower federalized the National Guard. And this is actually

483
00:24:55,359 --> 00:24:58,359
Speaker 2: a cool I think this is the first tweet I've

484
00:24:58,400 --> 00:25:03,919
Speaker 2: ever said that was partially written by AI. So I

485
00:25:04,000 --> 00:25:09,160
Speaker 2: went to Google and I just typed in Eisenhower federalizing

486
00:25:09,240 --> 00:25:14,199
Speaker 2: National Guard, and instantaneously several paragraphs pop up that are

487
00:25:14,240 --> 00:25:17,600
Speaker 2: beautifully researched and so I cut and paste one of

488
00:25:17,640 --> 00:25:20,040
Speaker 2: them that said on date and I didn't know the date.

489
00:25:20,600 --> 00:25:23,720
Speaker 2: You know, Eisenhower signed executive order number and I didn't

490
00:25:23,760 --> 00:25:26,120
Speaker 2: know the executive order number. But it was like this

491
00:25:26,440 --> 00:25:30,199
Speaker 2: beautifully researched. So the second half of the tweet. I

492
00:25:30,280 --> 00:25:34,159
Speaker 2: actually wrote that tweet while playing Hoops. So, as you

493
00:25:34,200 --> 00:25:35,840
Speaker 2: guys know, I played Hoops twice a week, so it

494
00:25:35,880 --> 00:25:39,119
Speaker 2: was like in between games on my phone, I like,

495
00:25:39,240 --> 00:25:42,280
Speaker 2: type the first half, put it the.

496
00:25:42,840 --> 00:25:45,320
Speaker 1: Last way, wait time out, timeout? I got it. You

497
00:25:45,800 --> 00:25:48,560
Speaker 1: opened up something there? You set in between games? Were

498
00:25:48,600 --> 00:25:49,720
Speaker 1: you the odd man out?

499
00:25:50,440 --> 00:25:51,159
Speaker 2: Yeah? Did you?

500
00:25:51,359 --> 00:25:53,439
Speaker 1: I lost? I just wanted to get that on there.

501
00:25:54,200 --> 00:25:55,879
Speaker 1: Did you hear what he said? Michael? Can you make

502
00:25:55,880 --> 00:25:58,120
Speaker 1: sure it's Mike's working? He just did? He say he lost.

503
00:25:58,160 --> 00:25:59,520
Speaker 1: It's going to be very clear.

504
00:25:59,359 --> 00:26:00,720
Speaker 3: But I think that was recorded.

505
00:26:01,240 --> 00:26:04,159
Speaker 1: Okay, got it? Okay, yeah, yeah, I'm glad that we

506
00:26:04,240 --> 00:26:06,199
Speaker 1: got that. That was worth staying up plate for just that,

507
00:26:06,320 --> 00:26:08,240
Speaker 1: right there. Keep going with your story, sir, This is

508
00:26:08,280 --> 00:26:08,800
Speaker 1: getting good.

509
00:26:09,280 --> 00:26:12,320
Speaker 2: So but when I sent my tweet, my social media

510
00:26:12,359 --> 00:26:14,800
Speaker 2: team was all mad and they're like, wait, we like

511
00:26:14,880 --> 00:26:18,360
Speaker 2: our Zoolander tweet, and I said no, no, no, put them

512
00:26:18,400 --> 00:26:22,639
Speaker 2: both out. Yeah, and let's have an experiment. Let's see

513
00:26:22,680 --> 00:26:26,080
Speaker 2: who wins. Who gets more like like you've got mine

514
00:26:26,400 --> 00:26:31,639
Speaker 2: and you know you guys, And so it was close.

515
00:26:32,880 --> 00:26:35,359
Speaker 2: I only beat them by two hundred and fifty percent.

516
00:26:36,240 --> 00:26:38,359
Speaker 2: So they got I think four hundred thousand engagements and

517
00:26:38,400 --> 00:26:41,840
Speaker 2: I got one point one million. But I will confess

518
00:26:42,000 --> 00:26:47,040
Speaker 2: making an admission on this. Although they didn't get nearly

519
00:26:47,080 --> 00:26:51,280
Speaker 2: the reach the comments on the Zoolander gift, the people

520
00:26:51,320 --> 00:26:53,320
Speaker 2: that saw it way better loved.

521
00:26:53,560 --> 00:26:53,760
Speaker 3: Yeah.

522
00:26:53,880 --> 00:26:55,879
Speaker 2: I mean they're just like the best tweet in the

523
00:26:55,960 --> 00:26:58,720
Speaker 2: history of the Internet, like they were, so I think

524
00:26:58,760 --> 00:27:01,800
Speaker 2: it was a smaller niche audience. Yeah, but the ones

525
00:27:01,840 --> 00:27:02,960
Speaker 2: that hit it really hit.

526
00:27:03,920 --> 00:27:05,720
Speaker 1: It's almost like as good as when you were the

527
00:27:05,760 --> 00:27:08,400
Speaker 1: Zodiac Killer. Maybe you still are, but you know, those

528
00:27:08,520 --> 00:27:10,080
Speaker 1: those never make me not laugh.

529
00:27:10,560 --> 00:27:12,320
Speaker 2: What do you mean when I was the Zodiac Yeah?

530
00:27:12,520 --> 00:27:13,159
Speaker 2: Exactly when did I?

531
00:27:13,920 --> 00:27:17,399
Speaker 3: I haven't shaped the statute of limitations recently. Yeah, but

532
00:27:17,680 --> 00:27:19,400
Speaker 3: I think you're safe now.

533
00:27:19,440 --> 00:27:24,400
Speaker 2: So do you know that? In twenty sixteen, an actual

534
00:27:24,600 --> 00:27:28,360
Speaker 2: poll done in the state of Florida found thirty eight

535
00:27:28,480 --> 00:27:32,040
Speaker 2: percent of Floridians believe that I could be the Zodiac Killer.

536
00:27:33,000 --> 00:27:36,359
Speaker 2: I to be clear. The Zodiac Killer killed at least

537
00:27:36,400 --> 00:27:39,360
Speaker 2: five people in northern California in the late nineteen sixties.

538
00:27:40,040 --> 00:27:41,520
Speaker 2: I was born in nineteen seventy.

539
00:27:42,080 --> 00:27:43,680
Speaker 3: Yeah, yeah, and yeah.

540
00:27:43,760 --> 00:27:46,680
Speaker 2: Maybe nearly half of Floridians believed I could be the

541
00:27:46,720 --> 00:27:47,359
Speaker 2: Zodiac Killer.

542
00:27:47,480 --> 00:27:50,480
Speaker 1: Yeah, yeah, that's you could have lied about your age.

543
00:27:51,280 --> 00:27:53,640
Speaker 1: You could have lied about your age. This is how

544
00:27:53,680 --> 00:27:54,800
Speaker 1: conspiracies begin.

545
00:27:55,560 --> 00:27:59,600
Speaker 2: I did have one one rally where this kid had

546
00:27:59,640 --> 00:28:01,960
Speaker 2: a sign and it's like twenty and he had a

547
00:28:02,000 --> 00:28:04,760
Speaker 2: sign that said, are you the Zodiac Killer? And I

548
00:28:04,800 --> 00:28:06,560
Speaker 2: went up to him. I put my hand on his shoulder.

549
00:28:06,600 --> 00:28:10,280
Speaker 2: I said, son, if I was the Zodiac Killer, would

550
00:28:10,359 --> 00:28:12,560
Speaker 2: you really want to be here with that sign right now? Yeah?

551
00:28:12,640 --> 00:28:13,760
Speaker 2: You know.

552
00:28:13,880 --> 00:28:16,080
Speaker 3: This actually was the point, which is how we got

553
00:28:16,080 --> 00:28:18,240
Speaker 3: into news him the sign. I don't know if you

554
00:28:18,280 --> 00:28:20,119
Speaker 3: guys saw the memes that were going around.

555
00:28:20,520 --> 00:28:23,080
Speaker 2: So I lost a bet on this.

556
00:28:23,320 --> 00:28:25,879
Speaker 3: I bet that the Democrats would not have a member

557
00:28:26,160 --> 00:28:28,280
Speaker 3: ejected from the speech. I thought they might have.

558
00:28:30,119 --> 00:28:31,399
Speaker 1: Did you actually believe that?

559
00:28:31,480 --> 00:28:33,960
Speaker 3: Though I didn't think that. I thought they would listen

560
00:28:33,960 --> 00:28:36,080
Speaker 3: to HACKEM Jefferies and try to chill. But they can't

561
00:28:36,080 --> 00:28:38,320
Speaker 3: know Eygreen has no chill, So he opens up.

562
00:28:38,320 --> 00:28:40,880
Speaker 2: By the way, there's a very real chance al Green

563
00:28:40,960 --> 00:28:44,360
Speaker 2: loses his Democrat primary a week from now. Yeah, really,

564
00:28:44,680 --> 00:28:48,120
Speaker 2: he's actually in jeopardy. And so I think the antics

565
00:28:48,120 --> 00:28:50,520
Speaker 2: were partially. Of course, he did his antics last year,

566
00:28:50,960 --> 00:28:55,360
Speaker 2: like waving his cane, which like to embody a grumpy

567
00:28:55,400 --> 00:28:58,800
Speaker 2: old man, like get off my lawn, you kids.

568
00:28:58,880 --> 00:29:01,560
Speaker 3: It's perfect. But he made it. He made a real

569
00:29:01,640 --> 00:29:04,280
Speaker 3: optical error, which is he unfurled the sign, which from

570
00:29:04,360 --> 00:29:06,600
Speaker 3: my angle in the gallery I could not see, and

571
00:29:06,880 --> 00:29:08,440
Speaker 3: so I said, wow, what's he saying? And I guess

572
00:29:08,480 --> 00:29:11,720
Speaker 3: the sign said black people aren't apes. But the problem

573
00:29:11,760 --> 00:29:17,280
Speaker 3: was the way he was holding it, the one the

574
00:29:17,280 --> 00:29:19,400
Speaker 3: one that I saw, and maybe one of those said

575
00:29:19,440 --> 00:29:22,920
Speaker 3: that too, the one I also said black people rent apes,

576
00:29:23,560 --> 00:29:26,480
Speaker 3: which was like an unfortunate any way you slice it,

577
00:29:26,520 --> 00:29:29,160
Speaker 3: These are very unfortunate optics, And I thought, you know,

578
00:29:29,400 --> 00:29:33,560
Speaker 3: the Democrat leader in the house asked one thing. He said, hey, guys,

579
00:29:33,960 --> 00:29:39,160
Speaker 3: please don't look crazy during the speech. And as the

580
00:29:39,160 --> 00:29:43,720
Speaker 3: President is walking into the room, al Green unfurls this sign,

581
00:29:43,800 --> 00:29:47,040
Speaker 3: and I thought, you have the discipline of a fruitfly,

582
00:29:47,360 --> 00:29:50,920
Speaker 3: Like there is no chance they didn't make it five minutes.

583
00:29:51,120 --> 00:29:52,920
Speaker 1: They're insane, all right. I have to ask you guys

584
00:29:53,040 --> 00:29:55,240
Speaker 1: being there, because one of the best lines of the

585
00:29:55,240 --> 00:29:58,360
Speaker 1: whole speech, and that was just one of those little

586
00:29:58,400 --> 00:30:00,719
Speaker 1: kind of tit for tatlines and it but it worked,

587
00:30:01,400 --> 00:30:04,680
Speaker 1: was when he was talking about insider trading and then

588
00:30:04,720 --> 00:30:09,200
Speaker 1: he said Nancy Pelosi's name, And it was amazing on

589
00:30:09,360 --> 00:30:12,560
Speaker 1: TV because if you didn't know the story, free one,

590
00:30:12,680 --> 00:30:14,040
Speaker 1: you immediately went to.

591
00:30:14,120 --> 00:30:15,760
Speaker 2: Every one of us was there.

592
00:30:15,760 --> 00:30:18,680
Speaker 1: Yeah, and I was too, But like if you didn't know,

593
00:30:19,360 --> 00:30:22,240
Speaker 1: and then you saw the reaction and you heard the

594
00:30:22,880 --> 00:30:24,960
Speaker 1: hissing bit whatever it was in the hall. I don't

595
00:30:24,960 --> 00:30:26,880
Speaker 1: know exactly what they were saying. It was like they

596
00:30:26,880 --> 00:30:29,480
Speaker 1: were like, you can't say her name like that. You

597
00:30:29,600 --> 00:30:33,280
Speaker 1: know that everybody went and googled insider trading, Nancy Pelosi

598
00:30:33,760 --> 00:30:36,120
Speaker 1: and then they learned about the story. Like they literally

599
00:30:36,160 --> 00:30:39,200
Speaker 1: helped him sell the story. What was the reaction from

600
00:30:39,200 --> 00:30:41,440
Speaker 1: the were Democrats mad or what was the reaction?

601
00:30:42,720 --> 00:30:45,760
Speaker 2: You were on the floor, Oh, look, they were mad constantly.

602
00:30:45,840 --> 00:30:48,160
Speaker 2: So is there one I will say though, there's a

603
00:30:48,200 --> 00:30:51,560
Speaker 2: difference from this year and last year. So last year

604
00:30:51,600 --> 00:30:54,840
Speaker 2: they went through the entire state of the Union and

605
00:30:54,880 --> 00:30:57,680
Speaker 2: they didn't applaud. They didn't applaud when Trump walked in.

606
00:30:58,880 --> 00:31:01,040
Speaker 2: They didn't applaud for any thing. They just sat for

607
00:31:01,160 --> 00:31:04,000
Speaker 2: the stone faced and heckled and waved their cane in it.

608
00:31:06,600 --> 00:31:08,480
Speaker 2: This year, before the State of the Union, I actually

609
00:31:08,480 --> 00:31:12,000
Speaker 2: went to several Democrats and asked them. I said, okay,

610
00:31:13,080 --> 00:31:17,280
Speaker 2: are you guys going to applaud for the US hockey team, like,

611
00:31:17,480 --> 00:31:20,800
Speaker 2: come on? And they all said yes. In fact, several

612
00:31:20,840 --> 00:31:25,000
Speaker 2: of them had an expletive. They said f yes, And

613
00:31:25,040 --> 00:31:28,240
Speaker 2: I said, look, to be clear, last year, you didn't

614
00:31:28,240 --> 00:31:33,640
Speaker 2: applaud for a kid with cancer, and question, Okay. One

615
00:31:33,680 --> 00:31:35,960
Speaker 2: of the Democrats who I actually like, he's I'm not

616
00:31:35,960 --> 00:31:37,640
Speaker 2: going to identify it, but he's got a good sense

617
00:31:37,640 --> 00:31:39,680
Speaker 2: of humor. I said that to him and he said, yeah,

618
00:31:39,680 --> 00:31:43,120
Speaker 2: we hate kids with cancer, which was like all right,

619
00:31:43,280 --> 00:31:45,720
Speaker 2: Like don't argue, just kind of vote it. And I'm like,

620
00:31:45,720 --> 00:31:47,760
Speaker 2: all right, well, well played like.

621
00:31:48,400 --> 00:31:50,000
Speaker 3: They did it again. This year. By the way, there

622
00:31:50,080 --> 00:31:53,200
Speaker 3: was a little girl who couldn't walk and it was

623
00:31:53,240 --> 00:31:56,960
Speaker 3: the same thing. A good chunk of Democrats would I

624
00:31:57,040 --> 00:31:59,240
Speaker 3: guess they were trying to play the stoic card. It

625
00:31:59,360 --> 00:32:02,160
Speaker 3: did not reached, at least from my vantage. I thought

626
00:32:02,200 --> 00:32:05,160
Speaker 3: it looked really callous because there was no unity within

627
00:32:05,200 --> 00:32:07,840
Speaker 3: the party, so there was no clear messaging. You know,

628
00:32:08,040 --> 00:32:11,240
Speaker 3: look that it all seemed pretty disastrous. The question that

629
00:32:11,400 --> 00:32:14,600
Speaker 3: I have as a as a proper conservative who is

630
00:32:14,680 --> 00:32:17,680
Speaker 3: always looking for the downside of things just to temper

631
00:32:17,760 --> 00:32:23,160
Speaker 3: my you know, jubilation. Do you think I think universally

632
00:32:23,200 --> 00:32:26,760
Speaker 3: the speech was viewed as quite good, quite effective. Does

633
00:32:26,840 --> 00:32:29,560
Speaker 3: it make a meaningful difference in the midterms?

634
00:32:29,640 --> 00:32:33,560
Speaker 2: Look, I think it does. Do you all right? Layout why?

635
00:32:33,880 --> 00:32:38,200
Speaker 1: I'll tell you why. This speech was the things that

636
00:32:38,360 --> 00:32:47,440
Speaker 1: irritate Republican slash moderate voters about Trump, that it's all

637
00:32:47,480 --> 00:32:49,959
Speaker 1: about him, and he doesn't know when to you know that,

638
00:32:50,040 --> 00:32:52,600
Speaker 1: the mean tweets and when to shut up, and and

639
00:32:52,760 --> 00:32:55,520
Speaker 1: and the things that irritate those that can stay home

640
00:32:56,320 --> 00:33:00,800
Speaker 1: watching his demeanor tonight. He came across in such a

641
00:33:00,800 --> 00:33:04,280
Speaker 1: way of like, these guys don't want this, These guys

642
00:33:04,320 --> 00:33:07,160
Speaker 1: don't put you first, these guys don't do this. He

643
00:33:07,240 --> 00:33:11,200
Speaker 1: also was giving incredible accolades and awards and the US

644
00:33:11,240 --> 00:33:14,880
Speaker 1: hockey team. There was momentum there. It was one after another.

645
00:33:14,920 --> 00:33:17,200
Speaker 1: It was one hundred year old man, a veteran, It

646
00:33:17,240 --> 00:33:19,560
Speaker 1: was the guy who was flying the helicopter, the Chinook

647
00:33:19,760 --> 00:33:23,000
Speaker 1: and telling a story. He was praising what makes America

648
00:33:23,080 --> 00:33:27,280
Speaker 1: great and the people that make America great. I actually

649
00:33:27,360 --> 00:33:30,720
Speaker 1: think that if you are a moderate voter, someone maybe

650
00:33:30,760 --> 00:33:33,840
Speaker 1: a Republican that traditionally stays home during the mid terms,

651
00:33:34,560 --> 00:33:38,120
Speaker 1: I actually think that this speech landed with you more

652
00:33:38,200 --> 00:33:40,200
Speaker 1: than any other speech of Trump the way it played

653
00:33:40,240 --> 00:33:43,840
Speaker 1: on TV. I think it also is going to land

654
00:33:43,960 --> 00:33:47,280
Speaker 1: on the economic issues of him reminding the no tax

655
00:33:47,320 --> 00:33:50,360
Speaker 1: on tips, the no tax on overtime, I'm trying to

656
00:33:50,400 --> 00:33:54,200
Speaker 1: make life more affordable, the gas prices. Those are things

657
00:33:54,200 --> 00:33:56,880
Speaker 1: that I actually think, Well, you know, they've been hammering

658
00:33:56,960 --> 00:33:59,120
Speaker 1: him on all the approval rings at forty this or

659
00:33:59,160 --> 00:34:01,600
Speaker 1: thirty nine or thirty depending on poll. I think he

660
00:34:01,640 --> 00:34:05,320
Speaker 1: gets a bump that actually stays because he landed it

661
00:34:05,440 --> 00:34:08,680
Speaker 1: so well in the audience, and he looked really calm,

662
00:34:08,960 --> 00:34:11,560
Speaker 1: He looked really just like I'm doing this because I

663
00:34:11,600 --> 00:34:14,839
Speaker 1: want to fix the country, and other speeches haven't come

664
00:34:14,840 --> 00:34:15,840
Speaker 1: across that way always.

665
00:34:16,280 --> 00:34:19,040
Speaker 2: Yeah, let me agree with you in that I think

666
00:34:19,360 --> 00:34:24,640
Speaker 2: the message tonight was the record of the last year. Yeah,

667
00:34:24,719 --> 00:34:28,839
Speaker 2: the record of the last year, I believe is objectively phenomenal. Yeah,

668
00:34:28,840 --> 00:34:31,480
Speaker 2: and I've been in the Senate now fourteen years. We've

669
00:34:31,560 --> 00:34:35,040
Speaker 2: never had a year where we've accomplished even a fraction

670
00:34:35,920 --> 00:34:38,040
Speaker 2: of what we did have been accomplished in the last year.

671
00:34:38,360 --> 00:34:40,359
Speaker 2: I mean, it is staggering. And he did a good job.

672
00:34:41,040 --> 00:34:43,960
Speaker 2: You know. We talked about on the last pod how

673
00:34:44,440 --> 00:34:47,560
Speaker 2: I spent thirty forty minutes on the phone with Trump

674
00:34:47,640 --> 00:34:50,240
Speaker 2: last week, and one of the things we talked about

675
00:34:50,280 --> 00:34:54,200
Speaker 2: was messaging for the midterms, and I said, listen, we

676
00:34:54,239 --> 00:34:57,480
Speaker 2: need to focus on results, on the very real results

677
00:35:00,080 --> 00:35:04,360
Speaker 2: during the border ninety nine percent drop in ELU crossings.

678
00:35:05,000 --> 00:35:09,000
Speaker 2: And then I encouraged him a message that's not getting

679
00:35:09,000 --> 00:35:12,919
Speaker 2: the attention it should is the impact on crime. Yes,

680
00:35:13,120 --> 00:35:17,920
Speaker 2: they murder rates have dropped twenty percent, drug overdose deaths

681
00:35:18,000 --> 00:35:22,040
Speaker 2: have dropped twenty percent. They're literally thousands of Americans who

682
00:35:22,040 --> 00:35:25,280
Speaker 2: were alive today because Trump was elected and Republicans won Congress.

683
00:35:25,320 --> 00:35:26,680
Speaker 3: It's a great message.

684
00:35:26,600 --> 00:35:31,040
Speaker 2: And that's been lost. And I was really happy, like

685
00:35:31,239 --> 00:35:35,160
Speaker 2: the first twenty minutes of the speech were laying out

686
00:35:35,200 --> 00:35:38,840
Speaker 2: that message and going through murder rates and crime rates

687
00:35:38,840 --> 00:35:42,520
Speaker 2: and d C rates and like how unhappy the Democrats

688
00:35:42,560 --> 00:35:46,640
Speaker 2: were that crime rates had plummeted in d C. And

689
00:35:46,719 --> 00:35:49,239
Speaker 2: New Orleans and your hometown of Memphis, Memphis. Yeah, the

690
00:35:49,280 --> 00:35:52,720
Speaker 2: Democrats were furious that fewer people are being murdered.

691
00:35:52,719 --> 00:35:56,120
Speaker 3: They wouldn't stand up on mass for murder declining. You

692
00:35:56,200 --> 00:35:58,440
Speaker 3: know this. I was looking at the polls and aggregate

693
00:35:58,520 --> 00:36:00,719
Speaker 3: of the polls from just January and.

694
00:36:00,640 --> 00:36:02,840
Speaker 2: February leading into this, and to be fair, the pro

695
00:36:02,960 --> 00:36:04,760
Speaker 2: murder community in America is pretty small.

696
00:36:05,400 --> 00:36:08,360
Speaker 3: It is. Look, it's a constituency, but it's not the

697
00:36:08,360 --> 00:36:10,719
Speaker 3: one you want. And so I was looking at as

698
00:36:10,719 --> 00:36:16,200
Speaker 3: aggregate of polls, Maris, PBS, a handful of others. And

699
00:36:16,880 --> 00:36:19,080
Speaker 3: the hard fact I spoke to some members of Congress

700
00:36:19,120 --> 00:36:22,800
Speaker 3: about this today. The hard fact is Republicans are underwater

701
00:36:23,200 --> 00:36:26,279
Speaker 3: on the economy, on economic perception. I think you could

702
00:36:26,400 --> 00:36:28,560
Speaker 3: could turn it around, but right now we're a little

703
00:36:28,560 --> 00:36:31,920
Speaker 3: bit underwater on healthcare. Democrats always went on healthcare and

704
00:36:32,080 --> 00:36:36,680
Speaker 3: on a defensive democracy or it's kind of a contrived category,

705
00:36:36,760 --> 00:36:39,520
Speaker 3: but anyway, they went on that. So the ones that

706
00:36:39,560 --> 00:36:44,120
Speaker 3: we're winning on right now quite decisively are immigration and

707
00:36:44,400 --> 00:36:48,040
Speaker 3: border enforcement, even more so now the border is shut down,

708
00:36:48,320 --> 00:36:51,640
Speaker 3: and especially on crime. So the key, it seems to me,

709
00:36:51,800 --> 00:36:54,600
Speaker 3: is one that tells you people are concerned about safety.

710
00:36:55,160 --> 00:36:58,080
Speaker 3: And two, if you can tie all of that together,

711
00:36:59,200 --> 00:37:02,560
Speaker 3: the crime relates obviously to illegal immigration, that's why it's

712
00:37:02,560 --> 00:37:06,440
Speaker 3: called illegal And the housing prices even by the way,

713
00:37:06,440 --> 00:37:07,879
Speaker 3: to the you know, the fact that you have six

714
00:37:07,920 --> 00:37:12,439
Speaker 3: months consecutive decline on housing prices coinciding with Mastery petition two.

715
00:37:12,360 --> 00:37:15,719
Speaker 2: Million people being deported, and that's just less demand, you know,

716
00:37:15,800 --> 00:37:17,440
Speaker 2: by the way, Like a couple of weeks ago, the

717
00:37:17,480 --> 00:37:22,120
Speaker 2: Houston Chronicle had a front page story that said murder

718
00:37:22,200 --> 00:37:26,680
Speaker 2: rates in Houston have declined eighteen percent. Yep, And Heidi

719
00:37:26,760 --> 00:37:29,080
Speaker 2: showed me the article because she knew it pissed me

720
00:37:29,120 --> 00:37:34,160
Speaker 2: off because the article, yes, the article the Chronicle says,

721
00:37:35,239 --> 00:37:38,920
Speaker 2: nobody can figure out why. It's completely inexplicable. The experts

722
00:37:39,000 --> 00:37:41,480
Speaker 2: we talk about have no idea why the murder rate

723
00:37:41,520 --> 00:37:44,239
Speaker 2: is dropping, and it like doesn't occur to them that

724
00:37:44,400 --> 00:37:48,840
Speaker 2: arresting and deporting murderers and gang bangers will reduce the

725
00:37:48,920 --> 00:37:52,800
Speaker 2: murder rate. Like it's not. This is not rocket science.

726
00:37:53,760 --> 00:37:59,799
Speaker 2: Fewer murderers means fewer murders. But yet to Democrats that

727
00:37:59,840 --> 00:38:00,320
Speaker 2: may makes.

728
00:38:00,200 --> 00:38:00,879
Speaker 3: No sense to them.

729
00:38:00,960 --> 00:38:04,480
Speaker 2: Yeah, and so that message was good. I also liked

730
00:38:04,480 --> 00:38:07,880
Speaker 2: on no tax on tips that he had the mom

731
00:38:07,960 --> 00:38:11,760
Speaker 2: who is the waitress stand up and he said, between

732
00:38:11,760 --> 00:38:14,880
Speaker 2: no tax on tips and no tax on overtime, she's

733
00:38:15,040 --> 00:38:18,520
Speaker 2: going to take home five thousand more dollars this year

734
00:38:18,560 --> 00:38:21,799
Speaker 2: than last year. That was real and it's not abstract.

735
00:38:22,040 --> 00:38:24,200
Speaker 2: And by the way, the Democrats wouldnt applaud for like

736
00:38:24,840 --> 00:38:28,160
Speaker 2: the mom waiting tables. They're not rooting for her, and

737
00:38:28,200 --> 00:38:30,000
Speaker 2: they want to take that five thousand dollars.

738
00:38:29,840 --> 00:38:31,840
Speaker 3: And that's real money. You know, five thousand dollars is

739
00:38:31,920 --> 00:38:36,040
Speaker 3: real money. It's not some abstraction. So nuts and bolts.

740
00:38:36,160 --> 00:38:38,600
Speaker 3: You know, if this was a speech, obviously you're at

741
00:38:38,640 --> 00:38:41,960
Speaker 3: the midterms, do you think it moves the needle?

742
00:38:43,239 --> 00:38:46,040
Speaker 2: I did keep message discipline of focusing on it. Yes.

743
00:38:46,840 --> 00:38:50,000
Speaker 1: By the way, yes, yesterday morning, you and I Adam

744
00:38:50,000 --> 00:38:52,680
Speaker 1: talking about this. I had breakfast a Speaker Johnson and

745
00:38:53,920 --> 00:38:55,920
Speaker 1: you talk about the reason why I think this one sticks.

746
00:38:56,680 --> 00:39:01,040
Speaker 1: There is a very real sense that Republican leadership have

747
00:39:01,160 --> 00:39:03,719
Speaker 1: our act together for once that we haven't had in

748
00:39:03,719 --> 00:39:07,880
Speaker 1: a long time. I also think that matters. Speaker Johnson

749
00:39:07,960 --> 00:39:12,640
Speaker 1: understands he basically has a one person majority. He does

750
00:39:12,680 --> 00:39:15,600
Speaker 1: not want to have and President Trump doesn't want to

751
00:39:15,600 --> 00:39:19,680
Speaker 1: have the Democrats take over the House. It is insanely slim,

752
00:39:20,160 --> 00:39:22,839
Speaker 1: and I think they're working so well together the same

753
00:39:22,840 --> 00:39:24,960
Speaker 1: way Center that you work so well with the president.

754
00:39:25,280 --> 00:39:27,680
Speaker 1: There does seem to be that we're actually on the

755
00:39:27,719 --> 00:39:30,720
Speaker 1: same team for once. I've not experienced that many times

756
00:39:30,719 --> 00:39:33,320
Speaker 1: in my life in the Republican Party. Like there's always

757
00:39:33,320 --> 00:39:35,279
Speaker 1: the infighting. We always not as screwed up when we

758
00:39:35,320 --> 00:39:39,439
Speaker 1: get power. There's different people jacking for positions. There does

759
00:39:39,520 --> 00:39:41,239
Speaker 1: seem to be a little bit of momentum now that

760
00:39:41,239 --> 00:39:43,080
Speaker 1: we're on the same team going the midterms. That's the

761
00:39:43,120 --> 00:39:45,239
Speaker 1: other reason I think this speech will continue in the

762
00:39:45,239 --> 00:39:47,480
Speaker 1: momentum because you have Johnson and others advocating.

763
00:39:48,520 --> 00:39:53,000
Speaker 2: Look, I hope so to play Devil's advocates. We're a

764
00:39:53,360 --> 00:39:56,720
Speaker 2: very divided country, and so the people who hate Trump

765
00:39:57,320 --> 00:40:00,760
Speaker 2: still hate them after the speech for sure actually listening,

766
00:40:03,120 --> 00:40:06,759
Speaker 2: and so I do think Ben, you focused on the

767
00:40:06,840 --> 00:40:09,640
Speaker 2: right area, which is the people who voted for him

768
00:40:09,680 --> 00:40:14,280
Speaker 2: in twenty four but maybe demoralized by the press narrative

769
00:40:14,360 --> 00:40:17,759
Speaker 2: that has been driven and to the extent this focuses

770
00:40:18,000 --> 00:40:21,719
Speaker 2: them on Wow, we're winning some big, big victories. I

771
00:40:21,800 --> 00:40:24,800
Speaker 2: also really liked. Look, the no tax on tips emphasis

772
00:40:24,880 --> 00:40:28,600
Speaker 2: I liked because I wrote that bill. And I really

773
00:40:28,719 --> 00:40:31,680
Speaker 2: liked his emphasis on the Trump accounts because, as you

774
00:40:31,719 --> 00:40:35,320
Speaker 2: guys know, I wrote that too, and the Democrats wouldnt

775
00:40:35,320 --> 00:40:35,800
Speaker 2: applaud for that.

776
00:40:35,880 --> 00:40:38,440
Speaker 3: I'm sorry, I actually have to pause here because I'm

777
00:40:38,480 --> 00:40:41,680
Speaker 3: sitting in the upper part of the gallery to the right.

778
00:40:41,880 --> 00:40:45,960
Speaker 3: If you're the president appointing and you didn't get everyone

779
00:40:46,080 --> 00:40:48,399
Speaker 3: was standing up at certain moments. That was one where

780
00:40:48,400 --> 00:40:51,000
Speaker 3: I bolted up, and other people were kind of slower.

781
00:40:51,040 --> 00:40:53,400
Speaker 3: I think they didn't quite process what the Trump accounts meant.

782
00:40:53,760 --> 00:40:57,080
Speaker 3: I'm really into the Trump accounts. Like the Trump accounts

783
00:40:57,080 --> 00:41:01,560
Speaker 3: I think are such a white pill, you know, focusing

784
00:41:01,600 --> 00:41:05,440
Speaker 3: on which is an existential issue. It's so practical, and

785
00:41:05,480 --> 00:41:08,400
Speaker 3: I'm going to confess something. I should follow this, I'm like, professionally,

786
00:41:08,400 --> 00:41:11,239
Speaker 3: I'm supposed to follow this closely. I did not know

787
00:41:11,880 --> 00:41:14,560
Speaker 3: that you were pushing the Trump accounts. You were, I

788
00:41:14,600 --> 00:41:17,560
Speaker 3: wrote it unbelieved I should have known, but I didn't know.

789
00:41:17,719 --> 00:41:19,480
Speaker 2: In fact, do you want to hear the story of

790
00:41:19,520 --> 00:41:21,880
Speaker 2: the origin of the Trump accounts. It's a cool story.

791
00:41:21,880 --> 00:41:23,560
Speaker 2: I've told it on the pod but not in a while.

792
00:41:24,840 --> 00:41:29,520
Speaker 2: So they originated from a poker game in Vegas. So,

793
00:41:29,719 --> 00:41:31,400
Speaker 2: as you guys know, I like poker.

794
00:41:32,360 --> 00:41:34,560
Speaker 1: By the way, Michael, were you invited to this poker night?

795
00:41:34,600 --> 00:41:35,640
Speaker 1: I just want to be clear about it.

796
00:41:35,680 --> 00:41:40,760
Speaker 3: I'm very offended, but I was not invited.

797
00:41:40,360 --> 00:41:43,759
Speaker 2: To the We're on the same team again. It was

798
00:41:43,760 --> 00:41:46,799
Speaker 2: a poker game for political donors. If you guys will

799
00:41:46,880 --> 00:41:56,120
Speaker 2: write me a check, okay, rich podcasters, so you know

800
00:41:56,600 --> 00:41:58,600
Speaker 2: you ought to Michael.

801
00:41:58,680 --> 00:42:00,879
Speaker 1: If you and I ever have a poke, I think

802
00:42:00,920 --> 00:42:03,360
Speaker 1: we will will organize it next time. We'll invite the

803
00:42:03,360 --> 00:42:04,799
Speaker 1: Center in advance. You agree with that.

804
00:42:05,040 --> 00:42:06,160
Speaker 3: We're very generous people.

805
00:42:06,200 --> 00:42:09,359
Speaker 1: Yes, we're very kind podcasters. Keep going with your story,

806
00:42:09,520 --> 00:42:09,879
Speaker 1: all right.

807
00:42:09,920 --> 00:42:13,000
Speaker 2: So I do a poker fundraiser typically in April in Vegas,

808
00:42:13,640 --> 00:42:16,120
Speaker 2: and so not last April, but two aprils ago. I

809
00:42:16,200 --> 00:42:20,839
Speaker 2: was there and and typically several poker pros will come.

810
00:42:20,880 --> 00:42:23,200
Speaker 2: I'm buddies with a number of the poker pros. And

811
00:42:23,280 --> 00:42:25,840
Speaker 2: so we're sitting at the Bellagio three in the morning

812
00:42:26,000 --> 00:42:30,040
Speaker 2: and Phil Hellmuth, who's one of the greatest poker players

813
00:42:30,080 --> 00:42:31,920
Speaker 2: to have ever lived. Phil would tell you he is

814
00:42:31,960 --> 00:42:34,680
Speaker 2: the greatest poker player to ever live, and he's got

815
00:42:34,719 --> 00:42:38,760
Speaker 2: a real argument to it. He's got I think fifteen bracelets,

816
00:42:38,920 --> 00:42:40,640
Speaker 2: so it's it's crazy.

817
00:42:40,640 --> 00:42:41,840
Speaker 1: That's a lot.

818
00:42:42,080 --> 00:42:44,440
Speaker 2: So we're sitting there playing poker and he asked me.

819
00:42:44,520 --> 00:42:48,719
Speaker 2: He says, hey, do you know Brad Gerster And at

820
00:42:48,760 --> 00:42:51,319
Speaker 2: the time I didn't. I'm like, yeah, who's he? And

821
00:42:51,360 --> 00:42:56,480
Speaker 2: he's a very successful venture capitalist in Silicon Valley and

822
00:42:56,520 --> 00:42:58,960
Speaker 2: he has this idea that was called in West America.

823
00:43:00,120 --> 00:43:00,640
Speaker 3: Like what's that?

824
00:43:00,719 --> 00:43:04,000
Speaker 2: And Phil describes it for a minute, and I said, Hey,

825
00:43:04,040 --> 00:43:07,880
Speaker 2: that sounds like something I'd be really interested in. And

826
00:43:07,960 --> 00:43:11,320
Speaker 2: so Phil pulls out his phone and he puts together

827
00:43:11,360 --> 00:43:14,400
Speaker 2: a text thread and connects me and Brad and says,

828
00:43:14,440 --> 00:43:16,799
Speaker 2: you two should should talk. You would really like each other.

829
00:43:18,120 --> 00:43:21,919
Speaker 2: The next week, Brad gets on a plane, flies to DC,

830
00:43:23,360 --> 00:43:27,160
Speaker 2: comes to my office and pitches the Invest America accounts.

831
00:43:27,960 --> 00:43:31,120
Speaker 2: I immediately called my policy team in and said, let's

832
00:43:31,120 --> 00:43:34,759
Speaker 2: start drafting this. So we drafted the legislation. Now, Brad

833
00:43:34,800 --> 00:43:37,560
Speaker 2: has said for months he had talked to a bunch

834
00:43:37,560 --> 00:43:40,520
Speaker 2: of other senators and none of them did a damn thing.

835
00:43:41,320 --> 00:43:43,280
Speaker 2: He talked to them and they'd all kind of nod

836
00:43:43,360 --> 00:43:45,000
Speaker 2: and be like yeah, yeah, that's a great idea, and

837
00:43:45,000 --> 00:43:47,000
Speaker 2: then no one would do anything. We sat down and

838
00:43:47,000 --> 00:43:52,120
Speaker 2: wrote the bill. That is the bill that is Trump Accounts.

839
00:43:52,280 --> 00:43:56,880
Speaker 2: It was my bill's great that we wrote. And it

840
00:43:57,000 --> 00:44:01,640
Speaker 2: is literally the case that if Phil Hellmuth does not

841
00:44:01,680 --> 00:44:05,120
Speaker 2: connect me with Brad Gersner April a year ago, there

842
00:44:05,200 --> 00:44:08,239
Speaker 2: are no Trump accounts and the American the kids of

843
00:44:08,280 --> 00:44:11,759
Speaker 2: America do not have trillions and investments, which is what

844
00:44:11,800 --> 00:44:13,399
Speaker 2: they're going to have through Trump account.

845
00:44:13,080 --> 00:44:15,000
Speaker 1: You know, this is Michael, Michael, you know what I

846
00:44:15,040 --> 00:44:17,200
Speaker 1: heard there by the way I heard that. Could you

847
00:44:17,280 --> 00:44:20,400
Speaker 1: imagine the bills that could have been written if you,

848
00:44:20,760 --> 00:44:23,520
Speaker 1: Michael and I were there at that table. I know,

849
00:44:23,640 --> 00:44:27,080
Speaker 1: I mean, we could have come up with we could

850
00:44:27,080 --> 00:44:29,480
Speaker 1: have cured cancer. Maybe at this point, we could.

851
00:44:29,280 --> 00:44:31,319
Speaker 3: Have ended the ninth and tenth wars. That could have

852
00:44:31,360 --> 00:44:32,280
Speaker 3: added to the record.

853
00:44:32,560 --> 00:44:34,759
Speaker 1: We could state department, the ending of the Michael and

854
00:44:34,800 --> 00:44:35,759
Speaker 1: Ben Warres. I like this.

855
00:44:35,880 --> 00:44:38,920
Speaker 3: You know. The thing that I love about the Trump Accounts,

856
00:44:38,960 --> 00:44:43,560
Speaker 3: in particular from the Republican coalitional standpoint is, you know,

857
00:44:43,760 --> 00:44:47,360
Speaker 3: the right always has all these different ideological factions because

858
00:44:47,440 --> 00:44:50,319
Speaker 3: we're more independent thinkers, and the left has progressives and

859
00:44:50,400 --> 00:44:53,200
Speaker 3: very progressives and John Fetterman, I guess and we you know,

860
00:44:53,280 --> 00:44:55,279
Speaker 3: we kind of have all these divisions. And so one

861
00:44:55,280 --> 00:44:57,600
Speaker 3: of the divisions that's come about in recent years, last

862
00:44:57,600 --> 00:45:00,239
Speaker 3: five or ten years, is people who were focused on

863
00:45:00,920 --> 00:45:03,400
Speaker 3: more the common good, you know, kind of an Aristotelian

864
00:45:03,480 --> 00:45:05,920
Speaker 3: view of politics, and people are more focused on the

865
00:45:05,920 --> 00:45:09,520
Speaker 3: libertarian view that comes from classical liberalism up through Seyhayak.

866
00:45:10,000 --> 00:45:12,319
Speaker 3: And what I love about the Trump accounts is it

867
00:45:12,360 --> 00:45:15,879
Speaker 3: actually marries the two. It's this beautiful. It just hits

868
00:45:15,960 --> 00:45:19,880
Speaker 3: this sweet spot. It's good that no flattery because I

869
00:45:19,880 --> 00:45:22,080
Speaker 3: actually didn't even know you were behind it. That is

870
00:45:22,520 --> 00:45:23,160
Speaker 3: really good.

871
00:45:23,200 --> 00:45:26,640
Speaker 2: By the way, we had Brad on Verdict. You know,

872
00:45:26,680 --> 00:45:29,120
Speaker 2: he's come on Verdict and talked about the whole idea.

873
00:45:29,680 --> 00:45:32,279
Speaker 2: And Brad came up with the idea with his two

874
00:45:32,400 --> 00:45:38,319
Speaker 2: teenage sons, and they spent years pushing it and and

875
00:45:38,360 --> 00:45:40,320
Speaker 2: Brad was there and recognized by the President of the

876
00:45:40,320 --> 00:45:43,880
Speaker 2: State of the Union. So Brad had put together a

877
00:45:43,920 --> 00:45:47,600
Speaker 2: CEO's council behind the invest America accounts, and the chairman

878
00:45:47,640 --> 00:45:49,960
Speaker 2: of it was Michael Dell. And Michael's a good friend

879
00:45:50,000 --> 00:45:51,400
Speaker 2: of mine, He's a Texan. We spent a lot of

880
00:45:51,400 --> 00:45:57,120
Speaker 2: time together, and the CEOs had all committed that they

881
00:45:57,200 --> 00:45:59,799
Speaker 2: would contribute or match to Trump accounts. So they're two

882
00:46:00,000 --> 00:46:02,640
Speaker 2: accelerators that are written into these these Trump accounts that

883
00:46:02,719 --> 00:46:06,279
Speaker 2: make them even more potent. Number one is that employers

884
00:46:06,280 --> 00:46:12,080
Speaker 2: can contributor match. And listen, when Congress passed Section four

885
00:46:12,120 --> 00:46:17,000
Speaker 2: oh one K of Arissa, nobody knew how fundamentally they

886
00:46:17,040 --> 00:46:20,719
Speaker 2: were changing how Americans save for retirement. Today, there's more

887
00:46:20,760 --> 00:46:23,400
Speaker 2: than twelve trillion dollars in four to one K accounts.

888
00:46:24,560 --> 00:46:26,799
Speaker 2: Trump accounts are four to one case for kids. Yeah,

889
00:46:27,200 --> 00:46:29,920
Speaker 2: so in very short order, you're gonna see trillions of

890
00:46:29,960 --> 00:46:36,799
Speaker 2: dollars in there. The two accelerators one is that employers

891
00:46:36,840 --> 00:46:39,319
Speaker 2: can contributor match, and so all the employers on the

892
00:46:39,360 --> 00:46:43,160
Speaker 2: CEO council had already committed, we're going to contributor match.

893
00:46:43,600 --> 00:46:47,480
Speaker 2: This is gonna become a ubiquitous as standard employee benefit,

894
00:46:47,719 --> 00:46:50,560
Speaker 2: just like a four to one K contribution is a

895
00:46:50,560 --> 00:46:54,360
Speaker 2: pretty standard employee benefit. You're gonna see employers. We're already

896
00:46:54,360 --> 00:46:58,440
Speaker 2: seeing a bunch who will match or contribute to the

897
00:46:58,480 --> 00:47:00,839
Speaker 2: Trump accounts of the kids that their employ So that

898
00:47:00,960 --> 00:47:04,879
Speaker 2: accelerates massively. The second thing and we deliberately wrote this

899
00:47:05,760 --> 00:47:08,400
Speaker 2: so that it can accept philanthropy and it can accept

900
00:47:08,480 --> 00:47:13,399
Speaker 2: charitable gifts. And as you know, Michael and Susan Dell

901
00:47:14,280 --> 00:47:18,120
Speaker 2: have given six and a quarter billion dollars and what

902
00:47:18,120 --> 00:47:21,960
Speaker 2: they've given is two hundred and fifty dollars for America's

903
00:47:21,960 --> 00:47:26,640
Speaker 2: two hundred and fifty Birthday to every child in America

904
00:47:27,280 --> 00:47:31,879
Speaker 2: under age ten who lives in a zip code where

905
00:47:31,880 --> 00:47:34,239
Speaker 2: the median income is one hundred and fifty thousand or less.

906
00:47:34,960 --> 00:47:37,360
Speaker 2: And so we wrote it so you can turn the dials.

907
00:47:37,840 --> 00:47:40,600
Speaker 2: You can turn the dials geographically, you can turn the

908
00:47:40,640 --> 00:47:43,240
Speaker 2: dials age wise, you can turn the dials income wise.

909
00:47:44,000 --> 00:47:50,560
Speaker 2: So Michael's done that. Brad Gersner has given two hundred

910
00:47:50,560 --> 00:47:54,600
Speaker 2: and fifty dollars to every kid in Indiana under age

911
00:47:54,640 --> 00:47:58,719
Speaker 2: five in zip codes with median income of one hundred

912
00:47:58,719 --> 00:48:01,560
Speaker 2: and fifty thousand or less. And Ray Dalio, the hedge

913
00:48:01,560 --> 00:48:06,000
Speaker 2: fund billionaire, has sponsored the kids in Connecticut. And I

914
00:48:06,080 --> 00:48:12,200
Speaker 2: actually have talked to a number of gazillionaires and Michael

915
00:48:12,280 --> 00:48:15,319
Speaker 2: Dell and Brad are getting on zooms and talking to

916
00:48:15,360 --> 00:48:20,759
Speaker 2: people with great wealth. That's awesome, encouraging them give your resources.

917
00:48:20,760 --> 00:48:22,520
Speaker 2: And here Michael and I have talked at length about that,

918
00:48:22,600 --> 00:48:26,960
Speaker 2: and one of the things that he got excited about. So, look,

919
00:48:27,640 --> 00:48:30,200
Speaker 2: Michael and Susan have between one hundred billion and two

920
00:48:30,239 --> 00:48:33,120
Speaker 2: hundred billion dollars, Like it's a massive amount of money,

921
00:48:34,040 --> 00:48:37,440
Speaker 2: and they're smart and responsible, and so they've had serious

922
00:48:37,480 --> 00:48:44,040
Speaker 2: conversations about how do you give away your fortune? And look,

923
00:48:44,080 --> 00:48:46,759
Speaker 2: you look at people who achieved great fortunes. They create

924
00:48:46,760 --> 00:48:50,160
Speaker 2: a foundation. The foundation gets taken over by a bunch

925
00:48:50,160 --> 00:48:52,600
Speaker 2: of Marxists who spend all their money undermining everything the

926
00:48:52,640 --> 00:48:56,080
Speaker 2: founders believe. Every time Henry Ford is rolling over in

927
00:48:56,120 --> 00:49:00,920
Speaker 2: his grave, John D. Rockefeller is bidding in his grave.

928
00:49:02,800 --> 00:49:07,319
Speaker 2: And one of the problems with that much money is

929
00:49:07,360 --> 00:49:09,680
Speaker 2: it's hard to give it away. Most charities can't take

930
00:49:09,680 --> 00:49:11,920
Speaker 2: a billion dollars like it's too much money and it

931
00:49:12,000 --> 00:49:15,920
Speaker 2: swamps them. So Michael and Susan have given six and

932
00:49:15,960 --> 00:49:19,680
Speaker 2: a quarter billion dollars, but they've told me they are

933
00:49:19,719 --> 00:49:23,360
Speaker 2: contemplating giving much much more than that.

934
00:49:23,360 --> 00:49:24,080
Speaker 1: That's so cool.

935
00:49:24,840 --> 00:49:27,080
Speaker 2: One of the things that's really powerful about these Trump

936
00:49:27,120 --> 00:49:33,520
Speaker 2: accounts is they're infinitely scalable. They could literally absorb the

937
00:49:33,760 --> 00:49:39,359
Speaker 2: entirety of Michael Dell's fortune and the fortune of every

938
00:49:39,400 --> 00:49:44,720
Speaker 2: other gazillionaire. And what is really potent is the time

939
00:49:44,840 --> 00:49:48,080
Speaker 2: value of investing. Look, if someone starts saving or investing

940
00:49:48,120 --> 00:49:51,960
Speaker 2: when they're sixty, it's hard for it to grow and

941
00:49:52,040 --> 00:49:57,520
Speaker 2: accumulate enough to be really significant by the time they retire.

942
00:49:58,640 --> 00:50:03,319
Speaker 2: What makes the Trump account so incredibly potent is we're

943
00:50:03,400 --> 00:50:07,040
Speaker 2: starting at age zero, We're starting at babies. So you've

944
00:50:07,080 --> 00:50:10,920
Speaker 2: got a time horizon where the kids of a single

945
00:50:11,040 --> 00:50:16,160
Speaker 2: mom waiting table can accumulate hundreds of thousands and even

946
00:50:16,280 --> 00:50:21,200
Speaker 2: millions of dollars. And so for philanthropy, the math is powerful.

947
00:50:21,239 --> 00:50:23,840
Speaker 2: If you put another thousand dollars in at the outset,

948
00:50:24,880 --> 00:50:28,160
Speaker 2: it really really grows. And so that's something that is

949
00:50:28,200 --> 00:50:32,439
Speaker 2: going to be really significant to speed these up. And

950
00:50:32,440 --> 00:50:34,759
Speaker 2: and the point, Michael you made, which which got me

951
00:50:34,920 --> 00:50:39,320
Speaker 2: really excited, is we're creating a new generation of capitalists

952
00:50:39,800 --> 00:50:43,839
Speaker 2: that every kid will have skin in the game and

953
00:50:43,920 --> 00:50:45,960
Speaker 2: be an owner of the biggest employers in America.

954
00:50:46,040 --> 00:50:48,240
Speaker 3: I thought this was a really important point. The President

955
00:50:48,280 --> 00:50:51,600
Speaker 3: touched on well one that the Trump accounts just do that,

956
00:50:52,480 --> 00:50:54,719
Speaker 3: so it gives people skin in the game. Even when

957
00:50:54,719 --> 00:50:57,040
Speaker 3: the prison pointed out only half of Americans have access

958
00:50:57,040 --> 00:50:58,920
Speaker 3: to for a one case. Yeah, they said, we want

959
00:50:58,960 --> 00:51:01,120
Speaker 3: to we want to bring that other half of them, let.

960
00:51:01,080 --> 00:51:03,440
Speaker 2: Them opt in to the thrift savings plan. That's an

961
00:51:03,480 --> 00:51:05,640
Speaker 2: idea I've talked with the President in the White House about.

962
00:51:05,840 --> 00:51:08,520
Speaker 2: I think it's a brilliant idea. I strongly support it.

963
00:51:08,760 --> 00:51:10,799
Speaker 2: I'm working on legislation to do that as well, to

964
00:51:10,840 --> 00:51:17,080
Speaker 2: codify that because it's Look, the more you can create investors,

965
00:51:17,440 --> 00:51:20,799
Speaker 2: get people with equity. And one of the important things

966
00:51:20,800 --> 00:51:24,640
Speaker 2: about how how the administration is designing the Trump Accounts

967
00:51:24,640 --> 00:51:29,239
Speaker 2: app is that it is not gonna simply say you've

968
00:51:29,280 --> 00:51:31,920
Speaker 2: got X dollars in the S and P five hundred.

969
00:51:32,880 --> 00:51:37,200
Speaker 2: It's gonna break down every constituent stock they own within it.

970
00:51:37,320 --> 00:51:37,920
Speaker 1: That's awesome.

971
00:51:37,960 --> 00:51:39,839
Speaker 2: So a ten year old will be able to see

972
00:51:40,560 --> 00:51:43,879
Speaker 2: I own a hundred bucks of Apple or Tesla or

973
00:51:43,920 --> 00:51:48,880
Speaker 2: Ford or McDonald's, and they'll see so so a kid

974
00:51:48,960 --> 00:51:51,640
Speaker 2: won't be rooting. I hate evil corporations. I want them

975
00:51:51,680 --> 00:51:53,880
Speaker 2: to fail. They're gonna be like, wait, I own that corporation.

976
00:51:54,040 --> 00:51:57,480
Speaker 2: I want them to do better. That changes their whole worldview.

977
00:51:57,680 --> 00:51:59,480
Speaker 2: It makes them capitalist, you know it.

978
00:51:59,600 --> 00:52:02,560
Speaker 3: Even during one of the big crises of capitalism in

979
00:52:02,600 --> 00:52:06,440
Speaker 3: the early twentieth century where you had real excesses of

980
00:52:06,440 --> 00:52:09,000
Speaker 3: industrialization that created you know, like child labor and all

981
00:52:09,000 --> 00:52:13,280
Speaker 3: this stuff. There was this movement among serious Christian thinkers

982
00:52:13,600 --> 00:52:17,560
Speaker 3: to try to resolve these tensions between capitalism and the

983
00:52:17,600 --> 00:52:20,200
Speaker 3: working poor. And there were all these chesters and had

984
00:52:20,200 --> 00:52:23,719
Speaker 3: a version with Bellock distributism. But the whole point, and

985
00:52:23,760 --> 00:52:26,759
Speaker 3: there's didn't really work. But the whole point was you

986
00:52:26,840 --> 00:52:31,279
Speaker 3: need people to really have a stake in the society

987
00:52:31,800 --> 00:52:35,400
Speaker 3: in following subsidiarity, and you know all these principles that

988
00:52:35,400 --> 00:52:39,000
Speaker 3: are so enshrined in the American system too, and this

989
00:52:39,160 --> 00:52:40,960
Speaker 3: really does that where you think, oh, I have a

990
00:52:41,000 --> 00:52:43,239
Speaker 3: stake in the corporations, I have a steak. He by

991
00:52:43,239 --> 00:52:44,280
Speaker 3: the way, I.

992
00:52:44,200 --> 00:52:48,279
Speaker 2: Miss geeky, cerebral academic stuff on the pod. I will say,

993
00:52:48,360 --> 00:52:52,040
Speaker 2: the sort of tenor of verdict has shifted. I don't

994
00:52:52,040 --> 00:52:55,080
Speaker 2: know why. I can't imagine the cause, but I'm just saying,

995
00:52:56,480 --> 00:52:58,680
Speaker 2: you know, I'm having a waft of nostalgia.

996
00:52:58,719 --> 00:53:00,640
Speaker 3: There's a little more Chester comes it.

997
00:53:00,760 --> 00:53:03,399
Speaker 1: Yes, all the people that just tell us the wake

998
00:53:03,560 --> 00:53:06,400
Speaker 1: back up, I got you back, keep going, wake up.

999
00:53:07,360 --> 00:53:10,640
Speaker 1: Our audience level just went like this but we're back now,

1000
00:53:10,640 --> 00:53:12,399
Speaker 1: they're all awake again. Make your final point.

1001
00:53:12,480 --> 00:53:17,840
Speaker 3: Go ahead, this this this key is really important because

1002
00:53:17,960 --> 00:53:21,080
Speaker 3: this is what really jazzed me about it. I don't

1003
00:53:21,160 --> 00:53:23,280
Speaker 3: like it when the right fractures into a million directions,

1004
00:53:23,320 --> 00:53:27,000
Speaker 3: because you know, I feel for Speaker Johnson. He has

1005
00:53:27,040 --> 00:53:29,319
Speaker 3: the worst job in all of politics. Yes, he has

1006
00:53:29,360 --> 00:53:31,480
Speaker 3: to hurt a bunch of cats. They all have all

1007
00:53:31,560 --> 00:53:33,640
Speaker 3: sorts of views, they have all sorts of principles, some

1008
00:53:33,680 --> 00:53:35,719
Speaker 3: of which conflict with each other, and so it's hard

1009
00:53:35,719 --> 00:53:38,520
Speaker 3: to get the right to do anything together. And these

1010
00:53:38,800 --> 00:53:39,440
Speaker 3: he is a.

1011
00:53:39,280 --> 00:53:41,760
Speaker 2: Good and decent man.

1012
00:53:41,840 --> 00:53:44,799
Speaker 3: Amazing, Yeah, he's a one. He's a wonderful guy, and

1013
00:53:44,800 --> 00:53:46,759
Speaker 3: he's doing a great He happens to also be doing

1014
00:53:46,760 --> 00:53:49,120
Speaker 3: a great job. But I just think what what the

1015
00:53:49,120 --> 00:53:51,879
Speaker 3: president was speaking on, especially these kinds of issues, These

1016
00:53:51,920 --> 00:53:54,319
Speaker 3: are the kind of things that can actually rally the

1017
00:53:54,360 --> 00:53:58,960
Speaker 3: way together with moderate voters, frankly even central so who

1018
00:53:59,000 --> 00:54:00,120
Speaker 3: don't want the crazy.

1019
00:54:00,320 --> 00:54:02,840
Speaker 1: Question for each of you. Quickly, as we are hitting

1020
00:54:03,000 --> 00:54:06,040
Speaker 1: about an hour here in our say the union coverage

1021
00:54:07,320 --> 00:54:11,719
Speaker 1: over under on the midterms. Now, how much better do

1022
00:54:11,760 --> 00:54:14,080
Speaker 1: you feel going at leaving the end of the night

1023
00:54:14,239 --> 00:54:16,280
Speaker 1: compared to going into the beginning of the speech tonight,

1024
00:54:16,320 --> 00:54:18,759
Speaker 1: how much more optimistic are you that we can hold

1025
00:54:18,760 --> 00:54:19,520
Speaker 1: the house.

1026
00:54:21,840 --> 00:54:25,080
Speaker 3: Hold the House. It's going to be very hard in

1027
00:54:25,120 --> 00:54:28,160
Speaker 3: my view, to hold the House. I would say, look,

1028
00:54:28,239 --> 00:54:30,720
Speaker 3: I feel I'll just pick a number. I feel twenty

1029
00:54:30,760 --> 00:54:35,480
Speaker 3: percent better. If the Republicans can stay on message, if

1030
00:54:35,520 --> 00:54:38,719
Speaker 3: the Republicans cannot devolve into petty in fighting, if the

1031
00:54:38,800 --> 00:54:43,920
Speaker 3: Republicans can be disciplined in the way they campaign, these

1032
00:54:43,960 --> 00:54:47,120
Speaker 3: are all you know. If wishes were horses, beggars would ride.

1033
00:54:47,760 --> 00:54:52,320
Speaker 3: I still think historic headwinds, best of circumstances, the party

1034
00:54:52,360 --> 00:54:54,719
Speaker 3: and power, especially with unified government, loses the House in

1035
00:54:54,760 --> 00:54:58,160
Speaker 3: the midterms. However, I think that the President did every

1036
00:54:58,560 --> 00:55:02,880
Speaker 3: single thing possib to put the party in an advantage

1037
00:55:02,920 --> 00:55:03,800
Speaker 3: heading into the center.

1038
00:55:05,440 --> 00:55:12,080
Speaker 2: And look, my view right now, the political environment is rough. Yes,

1039
00:55:12,719 --> 00:55:16,080
Speaker 2: if the election were today, it would not be a

1040
00:55:16,080 --> 00:55:20,680
Speaker 2: great outcome. We are nationally in about a D plus

1041
00:55:20,760 --> 00:55:25,360
Speaker 2: six environment. What that means is where polling is nationally

1042
00:55:25,400 --> 00:55:27,719
Speaker 2: is about six points more Democrat than it was an

1043
00:55:27,719 --> 00:55:30,800
Speaker 2: election day in twenty twenty four. If we're in a

1044
00:55:30,880 --> 00:55:35,960
Speaker 2: D plus six environment, we lose the House and the

1045
00:55:36,000 --> 00:55:37,640
Speaker 2: Senate is potentially in jeopardy.

1046
00:55:38,160 --> 00:55:38,560
Speaker 3: Crazy.

1047
00:55:39,800 --> 00:55:43,120
Speaker 2: If the election were today, that would be a real possibility.

1048
00:55:43,640 --> 00:55:46,920
Speaker 2: The good news is we got eight months and the

1049
00:55:47,080 --> 00:55:50,760
Speaker 2: substantive record is phenomenally good. It's not just a little

1050
00:55:50,760 --> 00:55:55,040
Speaker 2: bit good, it is insanely good. And so tonight was

1051
00:55:55,200 --> 00:55:59,760
Speaker 2: encouraging because Trump focused most of his time on laying

1052
00:55:59,760 --> 00:56:03,440
Speaker 2: out methodically that substance record and just how good it

1053
00:56:03,520 --> 00:56:06,640
Speaker 2: is and what we have to do. I mean, I

1054
00:56:06,719 --> 00:56:10,279
Speaker 2: do like that we have eight months. Most Americans don't

1055
00:56:10,320 --> 00:56:13,320
Speaker 2: know all these victories we're winning, and so our task

1056
00:56:14,239 --> 00:56:18,800
Speaker 2: is communicate the victories that are making a real difference

1057
00:56:18,840 --> 00:56:22,520
Speaker 2: in people's lives. But the good news is we have

1058
00:56:22,560 --> 00:56:25,480
Speaker 2: a monster amount of substance to talk about. We just

1059
00:56:25,560 --> 00:56:28,200
Speaker 2: need to talk about it. And and I think if

1060
00:56:28,200 --> 00:56:33,800
Speaker 2: we make that case, we could certainly keep the House

1061
00:56:33,840 --> 00:56:35,920
Speaker 2: and the Senate and grow our majorities in buds there