Unlocking the Next Interface with Anthony Azrak, CEO & Co-Founder @ General Magic

Nectar: [00:00:00] Anthony, it's such a pleasure to having you on on the show. I'm really excited for today's conversation, man. I know we, we've spoken a lot offline and wanna dive in all things open sesame. Maybe a more personal question to, to start. I wanna dive into General Magic the round you guys just announced, but what got you into startups?

Anthony: It's probably a mix of a couple of things. I still vividly remember when I was like. Quite young just building stuff. Started building robots when I was probably 8, 7, 8 years old. And I fell in love with that whole process of Hey, find a problem to solve and build a solution for it.

And just I guess show it to my parents. And and so that whole process started off I guess my building journey and then obviously being raised on Shark Tank and jackets then and all that it definitely helps. And I guess on the other hand, you have like my dad who runs his own little, like small business buying and selling steel.

And so I at the dinner table, it was a lot of conversation about business and negotiations and all that stuff. So that makes a [00:01:00] building and business kind of made sense.

Nectar: Yeah. Yeah. It's a great story. I didn't know about your dad. Yeah. Being entrepreneur himself. This is your third startup now, right?

If I under how, what startup would you count this as?

Anthony: I'd probably call it count as like my second.

Nectar: Okay.

Anthony: Yeah.

Nectar: Gives more info on The first,

Anthony: first one was this one man show selling software to hospitals. Terrible business, to be quite honest with you. I don't envy anyone who's in the healthcare space.

It's incredibly hard, especially in Quebec. But it did teach me a lot about the fundamentals of this like selling to enterprises and selling to bigger organizations and. Being faced with reality of what people were using on a day-to-day basis in terms of like software. And so I took some of those learnings and applied them to the company today.

Nectar: Yeah. What like, so I'm gonna geek out a bit. So what was the software and then when did you decide that it wasn't working?

Anthony: Oh it was like an a HR software. Company, essentially we were trying to compete against Epic and Quebec. Because as of a couple years ago, Quebec was doing all of their EHR stuff, like [00:02:00] just all their health records, just pen and paper.

And obviously that causes a lot of like management issues and a lot of patients they feel that the effects of that just because either the administration is too slow to process their files and stuff like that, but. And so when I realized, I was like, okay, like how hard is it to make an EHR realistically?

Turns out that the software isn't the issue. It's more like the sales process and then probably I don't know, six to eight months later. News came out that the government of Quebec signed like $3 billion deal with Epic systems to do their EHR stuff. So I was like, okay, that's probably my cue to close the company down.

And at the same time, I still had to finish my university and. Yeah, kinda made sense.

Nectar: Okay. It's cool. I didn't know you were doing that while still finishing your studies.

Anthony: Pretty sadistic. Yeah.

Nectar: Small parentheses, but I I'm familiar with that space just 'cause my old company we had a customer in the, like a tech software company selling into the Quebec healthcare system.

Yeah. And I've had many conversations about Epic and how it's basically it's like. They decide if they wanna work with you or not? Yeah.

Anthony: They're like they're [00:03:00] so big.

Nectar: They're, yeah, they're oh, this, okay, this what government, and okay, we will, we'll take your order and we'll decide if we wanna work with you.

Anthony: I think it's such this, it's such a weird company. It's based out of like the middle of nowhere. They have this huge campus, literally it looks like a college campus and the whole product is written in some obscure coding language. And so you can't actually reverse engineer it or, I don't know.

It's just these kind of like big companies with like big moats. Quite an interesting study.

Nectar: Yeah, it was an interesting one. I was like, I just, my understanding is that someone should come along, try and disrupt this thing, but it's so hard. Yeah, it's hard. It's hard. Maybe for First start, were you still learning and still studying?

Maybe not. And then, so how'd you get the, the idea, I know you said you, you did mention shutting down your first company. Yeah. But then how did that lead you to then starting Open Sesame?

Anthony: After that I had applied to this incubator program in Toronto. And by pure coincidence I got to reconnect with a guy I met probably a couple months earlier at in Toronto.

Hint, hint, it's my co-founder Jay. And so like I met Jay at [00:04:00] urgently at machine learning competition. He was hosting. At the time we were both, we both had our own businesses and so we're like, Hey, I appreciate you as a person, but there's nothing much we can do there. And then we, when we both got into next three six the incubator we were like, okay let's try this thing out.

Let, and so he had experience in public schools, had experience in healthcare and so we were like both of these verticals, care law about AI safety and hallucination detection. And so the first iteration of Open Sesame was just doing that. AI hallucination detection.

Nectar: Interesting. Yeah. And 'cause I know we've been, we've known each other for a little bit of time and I remember seeing some of the first iterations.

Yeah. And I'm like, I'm not too sure what this company does. It was super clear. So how has it been like, I wanna maybe double click on your co-founder relationship. 'cause I see you guys like being super tight and aligned. How and you said you, you got to know each other at X three six.

So walk us through a little bit of that relationship.

Anthony: Yeah. So the first day when we started working together, or like when we were, when we started to reconnect he was working on [00:05:00] some like ed tech Quizlet AI thing, which, anyways, I won't get into ed tech, but similar to healthcare, it's not the greatest of verticals to go into.

And so I told him Jay, and he never forgets this, but like I told him, Jay, for such a small smart person, why are you working on such a dumb startup? And I guess on the spot he was like, this asshole, like, why are you telling me this? But then I guess that set the tone for the relationship.

I was like, yeah, we don't have to take each other super seriously at all times. It's we can like chill outside of work. And then from then on we we're just like brainstorming and we released our first like demo thing after seven hours after locking us ourselves in one of the meeting rooms in the incubator.

And you're like, let's just go for it. It just, it, we work really well together. We're both technical yet we have like similar strengths and weaknesses and so he's much more extroverted than I am, and so he. He is the life of the party, and so he's great for sales, great for all that stuff.

And I'm much more [00:06:00] focused on the product and strategy and all that, so it kind of compliments.

Nectar: Yeah. That's really cool, man. That's a good that's a really good story. And then, so you mentioned that first iteration of Open Sesame. Yeah. Actually maybe like, how'd you come out, come up with a name?

Like what is it?

Anthony: I guess from day one we wanted to give people a magical experience. And so okay, magical experience. Let's go through what that magical experience looked like in, in stories in the past. And I guess there was also the trend of seeing open ai, open router, open, whatever.

So open, what? Open, open sesame. It kinda works. And yeah, that, that's the name stuck. It's

Nectar: a cool name. It's a super cool name. I find it's yeah, for the, I don't know if it's like an age thing. It's like it's, it is this notion of incantation, right? Of, yeah. Using, and then I guess it's a good, on brandand of, hey, using technology to Inca something.

Anthony: Yeah.

Nectar: And opening something. So and then so how did the current. We could talk about L ui. Sure. And Louis, I dunno if that's the right way to call it, but how'd you guys come up with this super cool idea of what you're building on now? Obviously I'll let you explain it then.

Anthony: Yeah. So essentially so we started off with the host nation stuff.

We got [00:07:00] some traction, couple sales, couple customers, whatever. We got the first check into the business and then for a year like a month or a month and a half after that, we were like, okay. Let's expand this. Like five years down the line, are we gonna see more or less hallucinations?

And then the obvious answer was less. And so why are you gonna go after like this shrinking market? It doesn't really make sense. Plus hallucinations detection, just by the nature of a, is like a. It's more of a research problem to solve, and we're not researchers, and I'm sure all the major AI labs are themselves trying to figure this stuff out.

'cause it's super important. And so as a pre sheet startup, like what can you really do in this market? And so when we saw the when we realized that we had to pivot, we kinda looked back at our like individual sort of histories and. We realized a couple things like one when I was in my previous company and in, in Jay's previous company, both of those customers [00:08:00] were kinda stuck with really old interfaces and really old sort of software paradigms that were stuck in like the 1990s.

And at the same time, by, just by pure coincidence, both of our fathers are in import export businesses. And so we're like intimately aware of the challenges there of the really bad software products that they were using. And I think any any young person it can relate to the whole to, it's an anecdote of, my parents always ask me like, Hey, how do I do this?

How do I do that? I'm lost in this software. I don't know what to do. And so you you think back to first principles and you have to realize that we're using the GUI and the graphical user interface. It's been the standard for the past, like 40 years, and it's great. It finally gave computers a new type of, a new face.

Before the gui it was all like a terminal. You had to be like a software engineer to, to understand what you were doing. But finally had like windows you can interact with in a more like human way. But the issue is that it's a one size fits all interface. [00:09:00] It doesn't really adapt to fit the user needs of each individual.

And so by the nature of it, you have to leave a lot of people behind. And so when we realized that not only AI was there to. As a catalyst for change in pretty much every industry, but also in the way that we interact with computers, we kinda realized that nobody else was working on this stuff.

And we found it pretty interesting as like creative technologies for ourselves. And so we just wanted to tackle it ourselves. And so now today, the thesis for Open Sesame is that eventually everyone can, is gonna do most, if not all of their work using natural language. By natural language, I just mean like conversational english or French or whatever language you use. And the way that has to happen, the only way that you can do all of your work using in natural language is one by turning natural language prompts or queries into a chain of actions, sir, chain of APIs. Which is easier said than done. That's actually it's been something [00:10:00] that we've been tackling for the past couple of months.

And the second part is a sort of dynamic, adaptable user interface, which we call the Lui, the language user interface. So yeah. Yeah, it's very cool. But obviously I'm biased 'cause I love what you guys are doing and it just feels like you said, we've currently passed the during test, it came and went and no one noticed.

Nectar: And it's the good way to see it is the way we interact with programmers like monkeys with thumbs like typing on a keyboard, it's does it's does it feel like the optimal way to do it, right? It's like you could just speak to it, right? There's a whole new way of doing it, right?

Speaking into English and language. And so you guys are like, feels like at the cusp of hey, yes. Does it, the old way of doing it doesn't make sense, right? So if we take that concept and then say, okay, let's build a product around this, right? So maybe double click and explain how your product works.

Yeah. How you know who you sell into.

Anthony: So our product is called Sell, and you can imagine sell as. An agent that comes in multiple different form factors. So one of the form factors is an embeddable widget that sits in the bottom middle of a software [00:11:00] product or a surface and it connects into the underlying APIs of that product or any other integration that you might want.

And it allows the end user of that product to do all of their work using natural language. So we offer that as a embeddable widget. We also offer that as a sort of employee facing interface. And then we are going to release an SMS agent as well pretty soon. And yeah. Same backend, but just different user interfaces to interact with the agents.

Nectar: Can you maybe give us like, how do your existing customers use? Yeah, use your product. Give us a use, like one of their use cases.

Anthony: So it depends on the customer. Usually on the enterprise side we deal with a lot of insurance managed financial services, types of companies, even construction. On the enterprise side, it's a lot of the employee facing interface because.

There's some compliance involved. And so you wanna make sure that everyone's safe that everyone's data is safe. [00:12:00] And for example, for insurance some of our customers are using us to essentially when somebody calls in to get an insurance quote, for example the human call agent on the other end right now has to, communicate with, five different software pages and do complex, like step-by-step processes, which.

Maybe for someone that's been working there for years is fine, but it still takes 30 minutes to ask like 29 different questions to the customer and nobody likes to call, right? Nobody enjoys that process. So what we do is that we have our agent listen in on the call, understand the requirements, understand what the customer wants, and we fill in the blanks law of the time for the human call agent.

And sometimes it takes calls from 30 minutes usually to. Down to five minutes. So we're saving people a lot of time, a lot of money naturally. And yeah, so that's how a lot of the enterprises use us on the mid-market side. It's much more as the embedded widget where we live on their product.

And usually these [00:13:00] are, older types of software, not the most elegant out there, pretty complex. And so we want to give an alternative to the end user, if you're happy using the software the way it is, great. But if you want more of an AI unified experience where we learn from the way you work your habits and all that and just make you work in a more natural way.

Then you have that other option as well.

Nectar: Yeah. It's fascinating. So I didn't know that first use case. Yeah. Where it's like, it listens to, it's an assistant slash agent or

Anthony: Yeah.

Nectar: Insert buzzword. That's really cool. So it's like a always on.

Anthony: Exactly.

Nectar: Helping out an agent like a customer service agent in this case.

Yeah. And then, yeah, the second way is cool too, right? Yeah. Where it's instead of trying to figure on your website, you could just speak to the website.

Anthony: Exactly

Nectar: how have you architected a product in the backend? Are you like, you have to, do you have to sit on top of a foundational model?

Do you build your own?

Anthony: Yeah. So we don't have enough money to make our own model right now. No, for each of these use cases it's the same backend, which is the beauty of it. We don't have to, maintain different skews [00:14:00] for different customers. But yeah, we sit on top of, a mixture of different models depending on the use case, depending on the query.

In some cases we might want to use, we might prefer one model over another, depending on, if it's a data related query, if it's more like general.

Nectar: Yeah. Do you have to like, end up building any of the data models for your customers? Is as I imagine you, it's such a you're such a horizontal play.

Yeah. But then imagine the data in the backend pretty clunky. Is that a, is that an implementation challenge you face?

Anthony: Sometimes. Most of the time our customers actually provide us with a lot of the context that we need to answer the questions correctly. Obviously on our end we do extra work in terms of if we know that it's an insurance customer, we'll try to feed it with more insurance data or at least give the agent access to concepts about insurance, the lingo of it.

And so yeah it's this like interesting challenge where. We don't wanna be too horizontal, because I think that kind of dilutes their marketing Ds a lot of the go to market and all of that. But at the same time, the tech is there to serve a lot of these customers.

Nectar: Yeah. [00:15:00] Yeah.

We could talk about your round and what you could just close. And so it's yeah, the pitches probably start with industry X, figure it out. But then, the market is like, the TAM is even like, why even talk about tam? Yeah. Like it's such a new way of interacting with computers.

Yeah. That every company's gonna need to work this way in some fashion.

Anthony: Yeah. And hopefully they do adapt to pretty soon.

Nectar: Yeah. And it's yeah you mentioned the challenges. Have you seen like on the technical side you, because it makes me think a little bit the hallucination challenge.

Sure. Like the initial idea, is that an issue at all? Like in terms of if you have the customers feeding you all this data and then, you have to make sure that the response is adequate, right? Yeah. Especially if it's a customer facing.

Anthony: Yeah. A lot of the challenges there come from.

A lot of the documentation that we get from their APIs, so oftentimes customers just don't have really clean we call them open API Specs, essentially, it's a list of their endpoints. It's not the most detailed or the descriptions aren't that rich. And so it's it's a big challenge because the agent is gonna be only as good as the data that it's given.

And so we have to do an extra job [00:16:00] of getting the best descriptions, the best data that we can from our customers without having them do too much work. And at the same time, you want to, since our goal is to make sure that you do all of your work using natural language, it's not good enough to only be good enough to call a single API.

For example, I would want that any action that I give, any query. Would prompt, not only a single API, but a chain of APIs, maybe like a workflow. And naturally it's like a Chinese telephone. If you start giving, bad data to the first, then the second agent, has worse and worse data, and eventually it just, it's mumble jumbo you, you don't get a good answer at the end. We're improving that day to day and yeah, that's the challenge of ai.

Nectar: Yeah. Yeah. No, I'm not gonna go into the whole AI thing. I think every podcast covers like the ai, what's going on there. Yeah. Maybe I'll keep a question for that on the end.

And then, so you guys were part of E 16 ZP Run. Yep. Congrats. But like, how was that program? I know J Jay's been super passionate to share all the good things and similar, so you should follow Jay on social media. Yes. [00:17:00] Yeah. Yeah. But yeah, curious to hear you what's been it, what's been the value for your company your startup?

Anthony: Oh, it's insane. It's I think it opened our eyes to what the best teams out there, how they performed and what they did. I still remember and Jay and I always talk about this, but like on the first day of Speed Run it was in la and, the first onboarding week was done at the old Snapchat office, and so I, I forgot who it was, but one of the Dispu members came on stage and they're like, okay guys, this is where Snapchat announced their IPO.

We expect the same from Ika. They're like, oh, shit. Okay. No pressure at all. And then you sort with, you started with intros and everyone like, okay who went to Stanford? It's every, like two thirds of the class raised their hands. Stanford, MIT, Harvard, it's and then Jay and I looked at each other, we're like shoot, like I went to McGill and then Jay went to UFT and those armed by any means, like bad [00:18:00] universities, but maybe they're not target schools for all of the Silicon Valley VCs and all that.

And and then he, obviously he had people that, some guy was like a fighter palate for 10 years and then he got bored out of it and he was like, okay, let me just join Andrew and XAI to lead their AI initiatives. It's like we're kids here. I'm 23. Jay's 24, and then we're dealing with this guy we're dealing with some Olympian squash player or, a guy that raced with some current F1 drivers and Formula three are like, wow, okay that's crazy. And so the first week was a lot of that. But then come week two and you start to realize like these are just human beings as well. This perspective of. You're not as good as those guys because they went to X University or they worked at y job is wrong.

Everyone is just a human being. Everyone in the program was accepted for a reason. And then the way that people worked as well was that's the standard. He'd come to the office at. I call it like eight, [00:19:00] eight thirty, around that time. And then you leave when the office closes at, 8:00 PM and yeah, that, that's just, that's how the best teams perform.

And if you're not up to that standard, then you shouldn't be in this industry. It's a lot of work. But it's a lot of fun as well.

Nectar: Yeah. Yeah. If, if you wanted something easy. Yeah.

Anthony: Nothing's easy in life, right?

Nectar: Yeah. No, cool. I, hearing you, it's it's super interesting, especially with my job, it's like thinking about how do you put ambitious teams together?

Yeah. But also demystifying it, like showing what excellence, what high performance looks like, and also while if that person's doing it right. Heard the same, you know why. Yeah. In the same exoskeleton it's I can do this too. There's no

Anthony: difference. Yeah.

Nectar: Yeah. That's it. So it's there's notion of talent density too.

Just putting people together Yeah. Creates this notion of, hey companionship competition.

Anthony: Yeah. No, it was this really interesting mix. We're like, obviously we're all like competitors at heart, but like none of us were actually competing against each other in the marketplace. And so if we needed any help with anything, like there was always someone that was really spiky at something in particular that we could [00:20:00] talk to.

And by spikiness I just mean someone that's top oh 1% in the world. That's something in particular that you wouldn't have access to it otherwise.

Nectar: Yeah. No, total. Totally yeah. So I think as an investor, it's like you wanna find people that again, have that

Anthony: Yeah.

Nectar: One spiky trait, and the weaknesses don't really matter as much. Yeah. Maybe talk to us about the round you guys just announced. Yeah. Congrats. For sure. Whatcha are you gonna do the money with? When can I invest?

Anthony: Yeah, so we recently closed our sheet round total round size was seven to 0.2 million, which is crazy to even say out loud.

And it was led by radical which is a first full circle moment for me, just personally. The folks at Radical were some of the folks that started Mila and Vector and all these AI labs in Canada. And the way that I got into AI in the first place was by attending these little seminars given by Y Bengio, all these, all those years ago at at Mila.

And you're like, wow, okay. Who would've thought, I don't know. And yeah, we've known the rack hole guys for, quite a while now and pretty impressed with their [00:21:00] portfolio. And also like it does help that, the CEO of cohere in Gomez, who also was invested by radical came in as an angel.

And so we felt in good hands that, we would give them the lead for the seed.

Nectar: Yeah. Yeah. Nice. And you also had speed run, participate too, right?

Anthony: Correct. They came in again for the seed rounds. Yeah.

Nectar: Yeah. Congrats man. Very cool. Very well done. There's not that many Canadian companies that are that raise that amount for seed, with the, arguably the best VC as well with Andreessen and Radical, I think is the best.

Maybe Canadian, one of the best Canadian. Whatcha you gonna do with the money? What what's, what are you spending on?

Anthony: We'll go to Monaco and enjoy. I think top priority for us is definitely hiring. We don't wanna hire too big of a team too early. But we wanna make sure that whoever we, we hire we're able to give a very good salary.

I don't know why, but there seems to be this trend in, in Canada where you kinda want to cheap out on all of your salaries. And the perspective that I give is that, an, a player is always gonna run circles around a B player. And so you wanna compensate your A players like really well.

Because they'll be hustlers, they'll work a [00:22:00] lot and. They'll pay back in dividends, right? Plus shred shreds great. You get like 35% of all r and d costs back from the government. It's a win-win situation. So yeah, hiring's definitely the biggest one. I think right now the focus is getting to product market fit.

Obviously it's this mystical thing. All founders wanna get there, and then once we get there, then we want to scale aggressively and take over that market. We wanna have that cash reserve in case that, like, when that happens, and at the same time, like if you wanna learn from history, we wanna make sure that you have enough money in the bank to sustain, if the bubble polyps or anything like that happens.

Nectar: Yeah, for sure. Yeah. So it's, yeah, it's a good war chest for sure.

Anthony: You wanna make sure

Nectar: yeah, we could talk about the AI bubble if there's one or not. By that time release released seven episode, maybe it would've popped. Who knows?

Anthony: Literally, who

Nectar: knows? Yeah. Yeah. No, it's really cool. Yeah, as I imagine like a lot tons of experiments on the go to market side.

Of course, continuing to work on the product. I know. It's, it is really it's really interesting what you guys are doing. Yeah. I wanna say what's I know you, you actually, yeah. Maybe personal question is anything keeping you up at night right now? [00:23:00] It seems like everything's going in the right direction, but what's the CEO's kind of like?

There's no one watching. So

Anthony: yeah, I mean it's, it really just is let's get to this repeatable sales cycle. We could be talking day and night about, what we think in theory would be a good wedge or a good, customer or whatever. But let's get down to the facts.

Okay, who wants this product? How easy is it for us to sell to these guys? And yeah, the metrics and you can correct me if I'm wrong, nectar, is that once you raise your seed, you essentially have 12 to 18 months to raise your series A. By then you need to get to four to 5 million a rrr.

And so like you have to scale quite aggressively and get to that inflection point. And so yeah, it is comforting in a way that I don't have to think about runway as much, but it's this like huge added pressure of. Hey, like you were trusted with this money. I don't take that lightly at all. You're expected to perform [00:24:00] and so perform not like in five years, perform now.

And so you try to do everything you can to get to that, next milestone as quickly as possible.

Nectar: Yeah. Yeah. The loneliness of the CEO, right? What you're describing, it's, yeah, it's hard. It's like you have your responsibility and shit skinny the fan multiple times a day, so it's Hey, brave face.

No, I definitely hear you. Yeah. But at the same time it's if I look just the storytelling perspective, it's like you've got such a great story to tell, right? Like this yeah. There's a nascent market untapped potential so many companies trying to figure out how to do it, and it's no, there's this better way.

Anthony: Yeah. It was funny to see Naval Hans Tweet on being like the UI is pre ai which is I would probably correct it to say like the Gooey is pre ai, but it was just like. That's funny. I don't know.

Nectar: Should be on the homepage of you. Yeah, I, we spoke about this tweet that I'm like, oh my God, this is like opus sse.

I

Anthony: got a quite a few dms after that just being like, you were right. Okay.

Nectar: Yeah. Super cool, man. Super exciting. What's next in the horizon, like for you guys? You mentioned like obviously hiring and growth and everything, but what can we expect to see?

Anthony: Yeah, so we're looking to hire one or two additional [00:25:00] engineers into the team.

The sooner the better. Everyone's in person five days a week at the office. We'll probably have a more formal announcement. We're recording this in December. Probably have a more formal announcement of the fundraising in January. Should be beyond that, we're just I'm personally very excited about our SMS like text agent product.

I think I'm more excited about that one than the two others. To be quite a, to be quite frank, I think text messaging is such an interesting mode of communication. We've all converged into iMessage or whatever, and it's it feels very natural to us, but it feels like the industry is still stuck in, early two thousands like.

Type has to confirm very old, like marketing text messaging, and there really aren't that many people tackling like AI for text messaging in the way that we want to do it. They have a couple of companies, like I think Poke is the main one that got me really interested in that space.

I think what we're [00:26:00] doing is quite interesting. It feels very human compared to every other sort of chat bot that I've used. But yeah, I'm excited to see. You know what the couple of pilot customers that we have for the taxation, how they resonate with that product and if they like it or not.

Nectar: Yeah. I would be remiss to not ask at least one of these dumb AI questions. Like outside of what you guys are doing. Yeah. What's what are you most interested about in this space right now? It doesn't need to be ai, but I'm curious about, obviously in tech that, you live and breathe it.

Anthony: Probably robotics. I think given my past like. I keep a pretty close eye on all the stuff happening in robotics. I think what the folks at Figure are doing is pretty cool. Clone is another one that's this weird exoskeleton type of thing. Like they are like trying to recreate like a synthetic human, which is creepy, but really interesting at the same time.

What's the other company called? Like Happy Robot or something Like, you have so many of these humanoid robots coming along. Obviously like Tesla's take on robotics as well is quite interesting, but it's, it feels like we're getting close to some kind of chay [00:27:00] bt moment there. Oh my god, the neo as well.

They can now purchase for like 500 bucks a month or so. There's so much happening in that space. Now time will tell if how quickly the humans will adopt these humanoid robots. I don't think the tech is there yet. It feels still very like robotic is probably the right word there.

I feel like we're getting close. I feel like we're getting pretty close to something impactful in the next year or two. Probably. Interesting. That's a good timeline. It feels like aggressive. I feel like we're maybe a little bit further away, but Yeah. I don't think

yeah, I like you. You'll, you'll have your adoption wave as well, like early adopters and stuff like are gonna.

Try V one and then it would probably be very quick creepy for the vast majority of people. But then, V two V three comes out, it's whoa, like this is genuinely useful in all cleans my dishes. It also folds my laundry. Whoa. I'm very excited for that stuff as well.

Nectar: Yeah. Like I'm looking forward to it. Cleaning my house as well. Dude, I could bug you for hours. [00:28:00] Okay, so you're like, round, round is closed. People want keep in touch and learn and follow the journey. Yeah. We mentioned you're a social media superstar with Jay, but what's the best way to, to keep in touch?

Anthony: Yeah, we post quite a bit on, on Twitter. So my Twitter handles is Anthony Ara. Not sure what Jays is. Jman. Kanye probably we'll, we also have an open sesame dev. Twitter accounts. We have LinkedIn as well. You can go on a website, opens, es dev and yeah, just, hit us up anytime.

Happy to chat with interesting people.

Nectar: Yeah. Thanks for the chat today. Of

Anthony: course. Thanks. Yeah.