Speaker 1: Pushkin.
Speaker 2: I try to bring my lunch to the office, but
Speaker 2: when I can't get my act together, which is most
Speaker 2: of the time, I go out and get lunch at
Speaker 2: a salad bowl place, and I pay like fourteen dollars.
Speaker 2: This always makes me feel like a little bit of
Speaker 2: a chump, because fourteen dollars seems like a lot to
Speaker 2: pay for a salad. But the salad is healthy and
Speaker 2: fast and tasty, so I buy it. There's of course,
Speaker 2: an issue here that goes beyond my own conflicted relationship
Speaker 2: to lunch, and that is this, a restaurant meal made
Speaker 2: with healthy, fresh ingredients costs more than a restaurant meal
Speaker 2: made with unhealthy processed ingredients. A salad costs more than
Speaker 2: a burger and fries. And it would be great not
Speaker 2: just for me, but for everybody if somebody could use
Speaker 2: technology to make my overpriced salad a lot cheaper. So
Speaker 2: I was pretty excited the other day when someone showed
Speaker 2: me video of a machine that might help make that happen.
Speaker 2: This video you sent me is password protected, which is
Speaker 2: curious to me, Like, why is it a secret this video?
Speaker 2: Why don't you want to show the world that your
Speaker 2: thing works?
Speaker 3: Because right now that version of the makeline is being
Speaker 3: tested at the Chipotle Cultivate Test Center.
Speaker 1: Oh and so you.
Speaker 3: Know, we haven't officially announced anything about this.
Speaker 1: I mean, we have.
Speaker 3: Announced that we're working together, right, but we haven't showed
Speaker 3: anything yet. O.
Speaker 1: Great, we'll I should be doing that very shortly. So
Speaker 1: this is like, which is.
Speaker 2: Why scoop it. You can't see the video yet, but
Speaker 2: we're gonna tell you about this video that you cannot
Speaker 2: yet see. I'm Jacob Goldstein. This is What's Your Problem?
Speaker 2: The show where I talk to people who are trying
Speaker 2: to make technological progress. My guest today is Stephen Klein.
Speaker 2: He's the co founder and CEO of Hyphen, a company
Speaker 2: that's developing an automated make line, basically an automated way
Speaker 2: to make the bold based meal that you get at
Speaker 2: fast casual restaurants like Chipotle or Sweet Green or whatever.
Speaker 2: Chipotle is an investor in Hyphen, and one of the
Speaker 2: major projects the company is working on is an automated
Speaker 2: system that could make online orders at thousands of Chipotle's.
Speaker 2: Steven's problem is this, how do you make restaurant food
Speaker 2: made from fresh ingredients cheaper?
Speaker 3: When my co founder Daniel and I started the company,
Speaker 3: we actually wanted to really be a vertically integrated restaurant,
Speaker 3: meaning that we wanted to effectively make the cost of
Speaker 3: healthy and delicious food the price of fast food. And
Speaker 3: we wanted to be as ubiquitous as fast food, right,
Speaker 3: And we thought that we could do that by automating
Speaker 3: the production of the food and then having it beyond wheels.
Speaker 3: So we built a fully robotic food truck at about
Speaker 3: fifteen months with five people and two million dollars, and
Speaker 3: then COVID hit about two months later, and so where
Speaker 3: we were operating at this in the back of this
Speaker 3: robotic food truck, you know, they were effectively ghost hounds,
Speaker 3: you know, overnight, and so I still remember viscerally kind
Speaker 3: of walking the streets in aerie silence, deciding like what
Speaker 3: are we gonna do. So we effectively retooled the system
Speaker 3: to put it in a make line, and that's what
Speaker 3: we're seeing today in that video.
Speaker 1: So it actually started as a food truck.
Speaker 2: Here's what you see in that password protected video. Stephen
Speaker 2: sent me this thing called the make line, which looks
Speaker 2: like what you see when you walk into a Sweet
Speaker 2: Green or a Chipotle or whatever along counter with containers
Speaker 2: of ingredients sunk into the counter. But this make line
Speaker 2: is different than all other make lines. Each container here
Speaker 2: has an automated trapdoor or augur or something in the
Speaker 2: bottom to dispense the food, and underneath the counter, like
Speaker 2: where the cabinets would normally be, there is this automated
Speaker 2: system where a bowl drops down into this like clamp
Speaker 2: at the beginning of the line, and some lettuce or
Speaker 2: whatever automatically drops into the bowl from the bin above.
Speaker 2: Then the clamp like pivots and hands the bowl off
Speaker 2: to another clamp a little further down the line, and
Speaker 2: the next ingredient is dropped into the bowl, and all on,
Speaker 2: all down the line until the salad is made, the
Speaker 2: bowl gets to the end of the line, and then
Speaker 2: finally this little elevator raises the bull up to the
Speaker 2: top of the counter.
Speaker 3: Actually, the guy that designed the elevator was designing an
Speaker 3: elevator for one of the reads at disney Land, very
Speaker 3: similar design about you know, ten thousand times the size.
Speaker 3: But it was pretty funny that that was his first project.
Speaker 1: When we kicked off.
Speaker 2: When you watch the video, the whole process actually looks
Speaker 2: kind of simple, which, of course it is not. Steven says,
Speaker 2: one of the hardest parts, which you can't see at
Speaker 2: all in the video, was getting the little trapdoor system
Speaker 2: to allow just the right amount of every ingredient to
Speaker 2: drop down into the bowl every time. And the details
Speaker 2: of why that's a hard problem illuminate why fresh food
Speaker 2: tends to be more expensive than processed food.
Speaker 3: It's extremely difficult to dispense and properly meter and plate
Speaker 3: ingredients because of the almost infinite permutations. Right, Let's take
Speaker 3: kale for example. If you have kale, it will change
Speaker 3: its permutations or characteristics depending upon how it's cut. Whether
Speaker 3: that's sautaied, blanched of and roasted, it will change permutation.
Speaker 1: Potentially if it's.
Speaker 3: Sourced in Salinas you know, where we're at, you know,
Speaker 3: or nearby where we're at, or somewhere else, it will
Speaker 3: change depending upon the cut method, right, if you cut
Speaker 3: it a different way. So being able to be agnostic
Speaker 3: to the type of ingredient is extremely difficult.
Speaker 1: So we basically have to you know, map.
Speaker 3: All these materials and characteristics to basically better understand how
Speaker 3: to feed that ingredient, and then it will get better
Speaker 3: over time.
Speaker 2: That's interesting, I mean, it makes me think about the
Speaker 2: difference between processed food and fresh food, right, And when
Speaker 2: you buy processed with anything that's like in the middle
Speaker 2: of the grocery store, you know, comes in a box,
Speaker 2: it's like become very homogenized, right, presumably so that it
Speaker 2: can be produced at scale by machines, whereas what you
Speaker 2: get at a Chipotle or sweet grain is very heterogeneous. Right,
Speaker 2: as you say, not all kale stocks are the same.
Speaker 2: And not to mention, there's like fifty different ingredients there
Speaker 2: could be. So do you have to build or more
Speaker 2: obviously there's more than fifty different ingredients? Do you have
Speaker 2: to build a different dispenser for every ingredient? Like if
Speaker 2: somebody's like, we want to do cantilina beans, right, do
Speaker 2: you have to be like, oh shit, all we know
Speaker 2: how to do is chick beans. We got to go
Speaker 2: build a whole new machine for cantelini beans.
Speaker 3: Yeah, So we have about six different feeder types or
Speaker 3: dispenser types. We'd have one that you know, has to
Speaker 3: deal with like guauca mole in the case of Chipotle,
Speaker 3: or pico de gayo, which is very different than guacamole
Speaker 3: in terms of this viscosity as well.
Speaker 1: As it's kind of you know, the chunkier.
Speaker 3: Ingredients, and then you have leafy greens, right, and that
Speaker 3: that's going to you know, perform wildly arugula, et cetera.
Speaker 3: So we yeah, we effectively have about six six dispensers
Speaker 3: handle you know, thousands of ingredients at this point that
Speaker 3: we've we've we've mapped and started to kind of understand
Speaker 3: their characteristics. Greens, especially a arugula early on was was
Speaker 3: pretty difficult to dispense. It would just start wrapping around
Speaker 3: these these kind of paddle wheels or augurs, and you know,
Speaker 3: I think we designed about seven hundred and fifty prototypes to.
Speaker 1: Get to the design that we have now.
Speaker 3: We three D print when we test, so we can
Speaker 3: do it in about a day and then test the
Speaker 3: next morning.
Speaker 2: Was there a moment when you sort of solve the
Speaker 2: leafy greens problem?
Speaker 3: Yeah, I mean it was just through rapid iteration. There
Speaker 3: was no one thing. It was just you know, these
Speaker 3: micro improvements we made along the way. And then the
Speaker 3: case of like black beans, where you get like that
Speaker 3: pulled up juice, you know, sometimes it's pretty unpleasant.
Speaker 1: You know, we effectively had to build.
Speaker 3: An auger that would basically push the ingredients out while
Speaker 3: you know, effectively letting some of that black bean juice
Speaker 3: kind slide into almost like a gutter and a kind
Speaker 3: of a septic tank in the back there.
Speaker 1: And so you do get some liquid, but not not
Speaker 1: that pool.
Speaker 2: I like that, although not to give you on solicit advice,
Speaker 2: I'd suggest avoiding the septic tank metaphor with the make line,
Speaker 2: especially with the beans.
Speaker 1: Great.
Speaker 3: Yeah, and I'd say, like the trickiest thing that we
Speaker 3: haven't solved yet is fand avocado. So we can do guacamoley,
Speaker 3: we can do like you know, the goofs and mounds,
Speaker 3: but getting that beautiful fan avocado slices like quite difficult
Speaker 3: to do.
Speaker 1: Yes, Slicing fish filets things.
Speaker 3: Like that can be quite difficult when they're you know,
Speaker 3: very sensitive.
Speaker 2: So do you give up, like it's fandavocado off the table?
Speaker 3: Yeah, there are some ingredients like fand avocado that you know,
Speaker 3: the operator on the line, because they're just kind of
Speaker 3: waiting for balls on the line, they can just add
Speaker 3: It's called expo, but they basically would just add the
Speaker 3: the avocado or those last final finishing items at the
Speaker 3: end there.
Speaker 1: That we can do today.
Speaker 2: So you've been working on this for what a little
Speaker 2: more than three years now. I know you've got an
Speaker 2: investment from Chipotle last year and you're sort of building
Speaker 2: a version of your line for Chipotle. Now, where is
Speaker 2: your line your product in the world now? Like, is
Speaker 2: it in restaurants now?
Speaker 3: Yeah, it's it's in a few and we have a
Speaker 3: lot actually coming in Q four of this year.
Speaker 1: We're just kind of starting to ramp up production.
Speaker 2: How many restaurants is your machine in now?
Speaker 1: About a dozen? Okay?
Speaker 2: And what's happening with Chipotle? Like, so Chipotle made an
Speaker 2: investment in your company last year, right, So like that
Speaker 2: seems significant? Like is that I don't know, that seems
Speaker 2: like a big deal. And what's happening with that?
Speaker 3: Yeah, and they're actually investing in the second time too.
Speaker 3: We're just wrapping that up right now, so we'll have
Speaker 3: some stuff to announce also.
Speaker 1: And Q four of this year with Chipotle, is.
Speaker 2: It likely that your machine will be in Chipotle next year?
Speaker 1: Yes?
Speaker 3: The CEO of Chipotle, you know, I think Believe has
Speaker 3: publicly stated, you know, he wants to all this out
Speaker 3: fleet wide, So you know, I think they have like
Speaker 3: thirty five hundred stores today.
Speaker 2: I mean you're saying there are thousands of Chipotlas in
Speaker 2: the world and they want your machine and all of them.
Speaker 3: Yes, they to have all of their digital orders. Yes,
Speaker 3: front of house you know, will always be front of house.
Speaker 2: Oh that's interesting. So the idea is your machine would
Speaker 2: be in the in the back of the restaurant, and
Speaker 2: when people order on their app, the robot your machine
Speaker 2: would make it, and when people walk in, a person
Speaker 2: would make it.
Speaker 1: Is that is that the idea precisely?
Speaker 3: And having that you know, that staff that's friendly and
Speaker 3: providing that hospitality is super important if you're ordering in person, right,
Speaker 3: But if you're ordering from your phone, you know, you
Speaker 3: just want your food to be fresh, fast and you know, accurate, ideally,
Speaker 3: and that's where we help. I mean, right now we're
Speaker 3: really focused on just getting these lines to produce and
Speaker 3: plate you know, perfect food every time.
Speaker 2: How far are you from them? Like, I guess it's
Speaker 2: not binary when you say like every time. I mean
Speaker 2: it's never going to be every every time, right, But
Speaker 2: there's some percentage liability presumably where it like, if you
Speaker 2: get above X, then it makes operational and economic sense. Right,
Speaker 2: What is X in terms of the uptim or reliability
Speaker 2: or whatever the metric is.
Speaker 3: Yeah, I mean, like you want to be at ninety
Speaker 3: nine percent up time, ideally ninety nine point nine percent
Speaker 3: up time. In the event that you don't, you know,
Speaker 3: it's just like when your Internet goes down or you know,
Speaker 3: your slack goes down, right.
Speaker 2: And what are you at now?
Speaker 1: Ninety five?
Speaker 2: Okay?
Speaker 3: Going from ninety five to ninety nine is really hard,
Speaker 3: and going from ninety nine to ninety nine point nine
Speaker 3: is even harder.
Speaker 2: So in a sense, the first ninety five percent, like
Speaker 2: you've done the easy part, in the last four percent
Speaker 2: is hard, and then the last zero point nine percent
Speaker 2: is killer is in order it might be harder? Yeah,
Speaker 2: And that's where that like one weird kale leaf just
Speaker 2: screws you, right, Ah, that fand avocado, right, fand avocado.
Speaker 2: We gave up on fand avocado and you're still at
Speaker 2: ninety five to get So do you just have to
Speaker 2: keep iterating to get from ninety five to ninety nine?
Speaker 1: So that's a really great question.
Speaker 3: So right now we are going through we're basically doing
Speaker 3: in DFMA, so design for manufacturing assembly, and as we
Speaker 3: do that, we start to injectionable parts, we start to
Speaker 3: kind of get you know, production ready materials that will
Speaker 3: drastically improve.
Speaker 2: Going from prototype to production basically.
Speaker 1: Yeah, we're also doing a lot of accelerated life testing.
Speaker 1: So we actually, you know, we did this system.
Speaker 3: We started in November on this new system, and we
Speaker 3: you know, we launched in April, so pretty quick, right,
Speaker 3: But you know, doing accelerated life testing, we have to
Speaker 3: run thousands of times. So I think we have like
Speaker 3: we've clocked like ten years on our subsystems. But through
Speaker 3: that type of testing and knowing where the failure points
Speaker 3: are and the hardware is how we get to that
Speaker 3: ninety nine percent. Yeah, it's just those types of iterations, right,
Speaker 3: and just micro improvements on the actual design itself.
Speaker 2: So okay, So if we imagine this future where there
Speaker 2: is a much more highly automated, fast casual sort of
Speaker 2: restaurant universe, I mean one question is it cheaper? Right? Like,
Speaker 2: one of my favorite things about technology is it makes
Speaker 2: things cheaper. I try and bring my lunch to work,
Speaker 2: but I do end up buying the fifteen dollars salad
Speaker 2: once or twice a week and feeling like a chump
Speaker 2: for spending that much on a salad, though it is
Speaker 2: a good salad, Like, will it get my fifteen dollars
Speaker 2: salad to a nine dollars salad.
Speaker 1: Maybe even cheaper? Right?
Speaker 3: Because again, you know, the two primary drivers of that
Speaker 3: price is the food, the quality of the foods, and
Speaker 3: then labor, right is this second. And so if you
Speaker 3: can make the marginal cost of producing food near zero,
Speaker 3: you know, you can drastically reduce that price, right, and
Speaker 3: you could get that you know, nine dollars five dollars salad.
Speaker 1: Five.
Speaker 2: I like that, You're going for five five dollars salad. Really,
Speaker 2: that's big for me.
Speaker 1: You like that?
Speaker 2: Now it's time for an ad that It'll be back
Speaker 2: in a minute. Okay, the ad is over. Back to Stephen.
Speaker 2: Stephen has this long term dream for Hyphen. He wants
Speaker 2: the company to open up its own make lines in
Speaker 2: cities around the country, and then he wants to let
Speaker 2: anyone who wants to to create their own basically virtual restaurant.
Speaker 2: So whatever I could go online, I could design Goldstein bowls,
Speaker 2: sell them for nine dollars a bowl, list them on
Speaker 2: Uber eats and seamless, so I would look like a restaurant,
Speaker 2: but Hyphen would be doing the actual food part. They'd
Speaker 2: be buying the ingredients making the bowls, and they would
Speaker 2: just charge me a fee for each bowl that I sold.
Speaker 2: So that is a universe where you have a sort
Speaker 2: of automated ghost or virtual kitchen. Right, Like, there's no
Speaker 2: restaurant as we think of it in that universe. There's
Speaker 2: not like a sign outside or whatever, but it exists
Speaker 2: on your phone, and it can make any number of
Speaker 2: kinds of food, presumably cheaply and quickly.
Speaker 3: I mean, that is what excites me. My sister in law, Sathara,
Speaker 3: she's in Brooklyn. You know, she's always wanted to start
Speaker 3: her own restaurant. I always just imagine her, you know,
Speaker 3: in her apartment, you know, developing a recipe on HERKMS
Speaker 3: on our Hyphen Kitchen management system, taste testing it on
Speaker 3: a nearby make line, and then launching her brand on
Speaker 3: door Dash or uber eats, right and getting it fulfilled
Speaker 3: that way. Why Hyphen you know, can scale when she's ready.
Speaker 3: So I kind of actually see it now. I think
Speaker 3: about it kind of like you know what happened in
Speaker 3: the beer industry where you had you know, Budweiser and
Speaker 3: Anaheuser Bush and then you had all these craft beers
Speaker 3: right and from Portland, Oregon, so IPAs and things like that.
Speaker 3: I see a similar movement happen where you go from
Speaker 3: overly processed food like McDonald's to you know, more of
Speaker 3: the artisanal meals that are you know, local to you.
Speaker 1: Huh.
Speaker 2: And then if it's like the beer industry, all those
Speaker 2: artists and all craft of bowl makers will get acquired
Speaker 2: by Chipotle, right, just like all the craft beer maker
Speaker 2: it's got acquired by AB and BEV.
Speaker 1: That is true.
Speaker 2: That could happen, and so that happens in this new
Speaker 2: universe because the startup costs are lower, essentially, because the
Speaker 2: startup costs can be very low where you don't even
Speaker 2: have to start a restaurant. You just go to you
Speaker 2: and say I want to start selling balls, and you're like, okay,
Speaker 2: you're not selling very many, so we're going to charge
Speaker 2: you three dollars a bowl. And I'm like, whatever, that's fun.
Speaker 2: I'm just sitting here at my computer. And if nobody
Speaker 2: it's like, you're like the Zazzle Shop, but for salad
Speaker 2: bowls exactly.
Speaker 3: And if we're doing that for so many people where
Speaker 3: they can do three or four bowls and they you know,
Speaker 3: it's again are like maybe a better example is like
Speaker 3: a Spotify or square space, right, Like they're designing their
Speaker 3: menu on the website, but it's effectively that easy to run.
Speaker 3: They're not making the food, they're not driving the food,
Speaker 3: they're not you know, having to buy real estate, right,
Speaker 3: they can do it all from their own dormer.
Speaker 2: Apartment in that universe. The sort of ghost kitchen restaurant,
Speaker 2: it's really a marketing question, right, Like, I mean, sure
Speaker 2: you want the food to taste good, but it's like
Speaker 2: a fixed set of ingreded against the Food's not going
Speaker 2: to be that different. What's going to be different is
Speaker 2: like whatever can you get everybody on TikTok to buy
Speaker 2: the brand salad with your name on it?
Speaker 1: Right?
Speaker 3: Yeah, it's like TikTok becomes like QVC meets the Food
Speaker 3: Network or something right where people are like you know,
Speaker 3: selling their meals on TikTok.
Speaker 2: And then what do you see happening with traditional restaurants
Speaker 2: where you you know, sit down and a waiter comes
Speaker 2: to your table and you order food from that person
Speaker 2: and there's a chef in the back cooking the food. Like,
Speaker 2: what's going to happen with that.
Speaker 3: Yeah, I think it's going to be bifurcated. It kind
Speaker 3: of already is like the food experience are eating is
Speaker 3: quite bifurcated, right, You have there are times when you
Speaker 3: want to have these types of conversations, got to a
Speaker 3: fancy dinner, drink wine, have a som kind of you know,
Speaker 3: tell you about that selection, and you know, really really
Speaker 3: experience the food and enjoy the conversation.
Speaker 1: And then there's times when you.
Speaker 3: Just did you get to your desk, or like your
Speaker 3: kids are at home and you know the house is
Speaker 3: busy and you just need food like fuel. Are you
Speaker 3: love food and you don't want it to be fuel,
Speaker 3: but like you just don't have the bandwidth at the time.
Speaker 3: Are the money? I think that's where you know automation
Speaker 3: can help.
Speaker 2: And so do you think that like classic restaurant isn't
Speaker 2: going to be any different than it is today? You
Speaker 2: think it'll be the same.
Speaker 1: I don't think it.
Speaker 3: Will change much because it's just like coffee, right, It's
Speaker 3: kind of built around this kind of artisanal kind of
Speaker 3: craft experience and it's really conduit to culture.
Speaker 1: Right, So you have a lot of folks that are
Speaker 1: going there for more than just the food.
Speaker 3: They're going there for the hospitality, and they're going for
Speaker 3: that entire experience. I don't think you can automate that
Speaker 3: experience ever, So I don't see that changing much at all.
Speaker 3: But again, the rest, the other side, the other fifty percent,
Speaker 3: is going to change massively.
Speaker 2: We'll be back in a minute with the lightning round.
Speaker 2: Back to the show. Okay, let's do the lightning round. Okay,
Speaker 2: do you cook? Oh yeah, what's a go to weeknight
Speaker 2: dinner that you cook.
Speaker 1: It's gonna sound silly. We love salads.
Speaker 3: My salad that I love it's kind of like a
Speaker 3: caesar salad, but it's it's it's kind of got a twist.
Speaker 3: We borrow the recipe from John and Vinnie's, which is
Speaker 3: a pizza pizza company out here in La where it's
Speaker 3: kind of a spicy caesar. So you got a lot
Speaker 3: of uh, you know, spice and zing to it and
Speaker 3: some some breadcrumbs on top. I'm a pretty simple guy
Speaker 3: when it comes to my salads, though.
Speaker 2: What's something you think should not be automated.
Speaker 3: Any guest interaction, like any anytime, even concierge at a
Speaker 3: hotel like which could be automated. You know with a iPad.
Speaker 3: I think it's like anytime that you're interacting with a guest,
Speaker 3: you can't take that magic away or you've lost your
Speaker 3: value proposition. So I'd say like that front of house
Speaker 3: or you know, front facing roles or types of tasks
Speaker 3: would be terrible to automate.
Speaker 2: Yeah, long term, you ran a frozen yogurt chop in college,
Speaker 2: so I got a couple questions about that first one
Speaker 2: flavor or.
Speaker 1: Swirl swirl Come on, it's more fun.
Speaker 2: Swirls a little confusing to because you end up getting
Speaker 2: like it's not like you're eating the one and you're
Speaker 2: eating the other. You're kind of eating both the all
Speaker 2: the time.
Speaker 1: I like a little spice, a little little interest in
Speaker 1: my life.
Speaker 2: Worse stopping.
Speaker 1: Chocolate sprinkles.
Speaker 2: Yeah, I think I agree. My kids like them, but
Speaker 2: I think I don't even get what's going on. How
Speaker 2: will you know it's time to do something else for work?
Speaker 3: You know, I'm pretty persistent, but just like if I
Speaker 3: bang my head and I'm not moving forward, and how
Speaker 3: I I eating for it? You know, like measuring everything
Speaker 3: and kind of seeing how it's progressing. You know, it's
Speaker 3: it's pretty demotivating and that's usually a good time. You know,
Speaker 3: if you're not waking up in the shower and thinking about,
Speaker 3: you know, what you're working on for the day, that's
Speaker 3: usually a good signal too, because usually when you have
Speaker 3: something like Hipeenner, you know, an idea that really compels you,
Speaker 3: like it's occupies your brain, share your brain space, and
Speaker 3: you can't get it out of your mind.
Speaker 1: When you lose that feeling or that thought, probably tend
Speaker 1: to leave.
Speaker 2: Stephen Klein is the co founder and CEO of hyphen
Speaker 2: Today's show was edited by Sarah Nix, produced by Edith Russolo,
Speaker 2: and engineered by Amanda k Wong. You can email us
Speaker 2: at problem at pushkin dot fm. I try to read
Speaker 2: every email I'd love to hear from you. I'm Jacob
Speaker 2: Goldstein and we'll be back next week with another episode
Speaker 2: of What's Your Problem