April 18, 2023

Beyond the Hype: Understanding Generative AI and Jasper AI's Innovations with Austin Distel

Beyond the Hype: Understanding Generative AI and Jasper AI's Innovations with Austin Distel
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Generative AI has been a hot topic in the tech world in recent years, and Austin is staking its claim with Jasper AI, a local unicorn making waves in the industry. Today, we had the pleasure of talking to Austin Distel, Senior Director of Marketing at Jasper AI, to shed some light on the topic. During our conversation, we discussed where Jasper AI fits in the tech stack, how Austin's tech ecosystem is playing a role in this area, and what the future holds for generative AI as a vital part of innovation.


Episode Highlights

  • Austin Distel believes that generative AI is a growing industry and that collaboration among companies is beneficial.
  • The responsible use of AI and mindful consideration of ethical concerns in content creation is a growing area of discussion.
  • Jasper AI is focused on creating new, unique, and original content based on data-driven insights to help businesses make decisions.
  • Jasper's goal is to augment human creativity, not replace it.
  • There is potential for the technology to impact industries beyond e-commerce and advertising, such as fashion and entertainment.
  • The generative AI ecosystem is still growing and there is a lot of potential for innovation.
  • What’s next Austin? “Today the generative AI is the smallest it'll ever be. It's growing. It's gonna be part of our ecosystem more and more and more. And so that just means that there's more opportunity. I think we're all gonna make each other better. So that's why I would love to get into the same room. Let's have conversations, let's make our products better together, and maybe team up.”

Episode links

Austin Distel:Twitter,LinkedIn

Jasper AI:Website,Twitter,LinkedIn



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Austin Next Links

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Michael Scharf LinkedIn 

Jason Scharf LinkedIn


Our music is “Tech Talk” by Kevin MacLeod. Licensed under Creative Commons 4.0 License


ANP Jasper AI [00:00:00] Jason Scharf: You might have heard that buzzword generative AI once or twice in the last year. Jokes aside, it is everywhere. And Austin is taking a claim in the space with our own unicorn Jasper AI. Today we're talking with Austin Distel, the senior director of Marketing for Jasper. Wanna get beyond the hype, understand where Jasper fits in the tech stack, and how our ecosystem will play a role in this increasingly vital part of our innovation economy. [00:00:22] Jason Scharf: Austin Distel is a local tech entrepreneur whose content is bookmarked by other entrepreneurs to learn how to build reoccurring income. From SaaS marketing to Airbnb tips, Jasper's Y Combinator-backed startup helping over 50,000 companies write amazing content with the help of ai. Austin, welcome to Austin next. [00:00:40] Austin Distel: What's going on? Good to be here. [00:00:42] Jason Scharf: I'm sure the Austin living in Austin's never been happened to you before. [00:00:46] Austin Distel: When I first moved here five years ago, that was certainly like how every Uber driver welcomed to me into their cab, Austin, from Austin, how long you've been here, and I ended up trying to come with a few punchlines, but they always fell short. [00:01:01] Jason Scharf: All right. Generative AI has just slightly exploded into the mainstream over the last couple of years and even more so over the last six months we were at South by and it was absolutely everywhere, including the Jasper AI panel. So let's start with what is Generative AI and is it different than the AI we've been talking about over the last 15 or 20? [00:01:28] Austin Distel: It's interesting because we've all been using AI for most of our adult life. It's just been running in the background. It's what powers your Google Maps, it's what gets all your smart devices talking together. We all kind of take this background AI for granted. Yet it wasn't until roughly three years ago that AI started to become entering the creative space and visual, language, imagery. And that's when it really caught our attention and our amusement as well. As you've seen even this past winter, Lensa AI app, our whole Instagram feed was full of weird AI-generated selfies. [00:02:09] Jason Scharf: may have used the Lensa app, and my kids were having all sorts of fun with picking out the pictures they liked the best, so yes, I've seen it. [00:02:18] Austin Distel: Yeah. For the first time ever, we've seen a new intelligence start to take commands from us and solve some of these problems. And what's even more interesting is that AI has come for the work of a knowledge worker faster than the work of a manual worker. [00:02:42] Austin Distel: And we used to have this. It was kind of a headline news that AI was coming for your jobs, but it was aimed towards the manual workers. And now today we can see like a lot of people are asking AI for advice and asking it to solve problems like accounting problems and finance and marketing. [00:03:01] Austin Distel: It's just really interesting to see how fast that's happened as well where [00:03:00] information, knowledge has become the main talking point of AI. [00:03:12] Jason Scharf: I knew there was a different moment. This was like two or three days ago. My oldest, who's nine was working on the Constitution and we were talking about the 11th Amendment, which I still don't fully understand, all the rest I can understand. [00:03:27] Jason Scharf: The 11th is still a little bit fucking to me. And he goes, “Dad, just ChatGPT it.” And we actually were debating what age we should tell ChatGPT to explain it to. He's like, okay, I'm gonna explain it to you. No, no, have it explain it to an 11 year old. That's the level I wanna understand it at. [00:03:46] Jason Scharf: I'm like, okay, we're in a different world now if that's his go-to way of thinking about it. [00:03:53] Austin Distel: Well, I grew up in an age where we Google. And maybe this is the extension of that. We used to think how dumb it is that teachers didn't allow us to have calculators in class because we all knew it was on our iPhone in our pocket. [00:04:11] Austin Distel: And that was always going to be with us. And so there's kind of this like level of expectation that kids realize the tools that are already available and they're so used to using tools. You give a kid an iPad and it naturally knows how to use it. That's crazy. I think that we're more self-serving than ever. [00:04:34] Austin Distel: We don't like questions unanswered, and we as a human species are figuring out ways to solve it, whether through our own experience or by watching YouTube videos on figuring it out. And what's really cool is I view AI as a way to consolidate or even quicken our time to result. I was just trying to figure out what TV to buy and rather than going and reading like five blog posts in all these YouTube videos, I can just really tell the AI what my specifications are, what my needs are, and then it gives me the best results. Cuz it's already read all of those articles. [00:05:14] Jason Scharf: Right. So you said it, in the last three years, it entered the creative kind of mainstream, right? So was it a technical thing that happened differently? Is this different than deep learning neural net scans? Is that what happened? Or is this just really the next evolution of that technology? What happened from a technical perspective with LLMs and the Image generators? [00:05:38] Austin Distel: I think it works on many levels. The machine learning, the actual computers, are now at a capacity and at a level of technology, the hardware's able to calculate and learn and have this memory, but then the data set is now growing and so it's learned the natural language of humans. [00:05:59] Austin Distel: It's consumed enough data to understand how we think, how to take commands, and how to give us the result of those commands. And I would also say we're maybe at a time in our own evolution, not just technology's evolution, but the human's evolution to interact with this kind of technology in a way that's helpful. [00:06:18] Austin Distel: And I would even say, over the course of my time, since the beginning of Jasper two and a half years ago, the conversation has evolved. Our ability to work with AI has evolved, so the overall consciousness of humans is evolved. This is what's interesting is it was almost like a magic trick. [00:06:41] Austin Distel: When we first started marketing Jasper. It was like, Hey, come on and sign up for our tool and we will have this mythical AI thing. Create your ad copy. And now everybody recognizes that that's like a normal thing. Now through ChatGPT, which just shows you how fast this has really taken off even in the last six months. [00:07:01] Austin Distel: Now we're figuring out how to be prompt engineers. How do we give directions to an AI in a way that it understands our direction, and then we figure out how to formulate it in a way that's better received and increases the quality of output. Now this [00:07:00] is like basically training humans how to be great directors of their own life, but directors in their company, directors for other people. [00:07:27] Austin Distel: We've always said, this is not just a new AI thing. The worse your directions, the worse your team's output. Now that's being applied to AI. If you give your assistant really poor directions, your assistant's not gonna do a good job. And that's not their blame, that's your blame as a boss. And so now what we've kind of developed is this, how to give directions in a way that's received well and understood through written word. It's both training the AI but also training us. [00:07:58] Jason Scharf: I think it's interesting also that the language itself if I think of like the say ChatGPT versus the Image generators, right? And my background is in writing and so I've always had a lot better in working with ChatGPT than getting the usage that out of like Dall-E or Stable Diffusion, I can never get the images that I want out of it. [00:08:21] Jason Scharf: And it's been interesting, as you said, kind of training. Cause I know there're starting to be like those guides and those booklets that have come out. And so now if I ever try to create image, I have got the booklet open right next to me saying, okay, I want it to kind of be this. And oh great, that's the words I wanna be using. [00:08:35] Jason Scharf: And so those tool sets are starting to be more helpful and being out there. And something I do think is interesting also, as you said, kind of is we're seeing this kind of explosion being this kind of director. I see that Generative AI coming on so quickly is happening in two very distinct ways. [00:08:51] Jason Scharf: Like one is this whole broad-scale adoption, right? We've seen all the graphs and so forth of gen of ChatGPT, you know, 10 million, a hundred million users at, you know, five days or a hundred or whatever these mind numbingly, fast adoptions. The other is actually producing product and solution revenue. [00:09:10] Jason Scharf: So actually real money being made because people want it and actually being able to use it. What do you think is actually, and this is not me being negative on these, but just a different, what do you think makes this moment different than say, blockchain and metaverse? You know, the last kind of big waves we were seeing that didn't necessarily see that level of adoption or that level of revenue versus now. [00:09:32] Austin Distel: I think it works on a few fold. First is it's visual. Can you visualize the blockchain? I'm a big believer as well in blockchain, crypto, all of that. Yet this was so much easier for me to grasp. I get it, I can get it in seconds. In fact, my mom can get it in seconds. She can understand the value of it. [00:09:53] Austin Distel: She can't understand the value of blockchain despite me setting up her Coinbase like four years ago. She still doesn't understand why I need it, how it works, and so we instantly understand the value of it as well. I get that I answer that question concisely, well-roundedly and through a lot of intelligence, a lot of understanding from multiple sources kind of combined together to give me this grand output. [00:10:20] Austin Distel: It also is impressive. As a professional copywriter and marketer in general, I'm impressed with the copy that AI can generate. And we can have influence over that and we can give it direction so I can ask it to do for copywriting formulas that I know of, that are known in advertising really. [00:10:42] Austin Distel: And it can deliver that cuz it knows the formulas. What ends up happening is I just have to be able to prompt it to give me that formula so it's kind of turned language into a programming tool like it's understood. It's math equation, which is really cool. It's also the time to value. [00:11:05] Austin Distel: If something takes a long time for us to receive value from it, it's hard to get it sticky and make it a part of our routine in our lives. This is as easy as signing up and within two minutes you can give it a prompt within the second. It'll reply. Look at the UI/UX experiment of ChatGPT because look OpenAI has been around for years. [00:11:33] Austin Distel: And has never caught the headwind, the tailwind that it has today, it's because they turned it into a chat. We've even been around, for two years, two and a half years, and it wasn't until a chat, the time to value was near immediate. Instead of using a template, instead of being inside of a document, it was the UI/UX of a chat that made humans understand I'm having a conversation. [00:12:02] Austin Distel: And so that is such an interesting design principle is the time to value is just the framing. I'm gonna have a conversation with something that's an AI. So I will send one message and it'll reply with a response. To summarize, I think there's three reasons why it's taken a big title wave of attention. [00:12:23] Austin Distel: One, the time to value is very fast. We're talking two minutes or less. There's no signing up and learning an API or anything like that. Two, it's practically useful and everybody can understand instantly why it's useful in their daily life. It's broadly applicable because, whether you're in marketing, whether you're a creative, whether you're even in finance. [00:12:47] Austin Distel: I asked it to do cash on cash return for my Airbnb here and in Austin, and I uploaded my Airbnb earnings and it gave me a CAC return so it can understand these directions. So it's instantly useful as well. I think there's so many things going for it, and here's the amazing thing. Generative AI is at the worst it's ever going to be. [00:13:09] Austin Distel: This very moment. It's the worst it's ever going to be. It's only getting better. It's only getting smarter. It's only getting easier to use. It's coming everywhere, and it's going to be a part of our daily lives. Not always like where you have to sign up for it, but in the background of the tools, you already use. [00:13:27] Michael Scharf: Austin, I think you're absolutely right. It's clear that ChatGPT delivers answers in a format that us humans are used to taking them, as opposed to the typical search engine, which gives you the list of other websites where you could then begin to go and find it out. But I wanna turn a little bit towards Jasper specifically because you guys have an interesting company with an interesting history. [00:13:53] Michael Scharf: So tell me the origin story about Jasper AI. [00:13:57] Austin Distel: Jasper, the origin team started eight years ago. Dave, Chris, and JP were running their marketing agency, so they are professional marketers and they understood what great marketing looks like. And then they started to solve that same problem in other ways. [00:14:17] Austin Distel: They created courses, then they built a community and so that's kinda where I entered. And then they've created three other software companies focused on helping marketers and over time continuing to serve the same audience. We discovered through Y Combinator, OpenAI, and all of this. [00:14:36] Austin Distel: And eventually we started teaching the AI how to do great marketing. Following David Ogilvy's principles, the Copywriter's Handbook, teaching at formulas, and ultimately all of our example work of our best stuff. Here's what converted after spending millions on advertising. Here's our winning ads, our winning emails, blog posts, et cetera, and creating basically, so examples, frameworks, rules, and then it started performing really well for us. [00:15:09] Austin Distel: We had a Facebook group where we basically would help create copy with AI for other people. And then they said, well, I need it to write our Amazon listing copy. Cuz we're an e-commerce store or we need an email follow up sequence. We need social media content, a blog post. And so that developed the use cases. [00:15:32] Austin Distel: And every single one of these use cases was unique and different, different rules, different judgments on what's good and what's not good. And so over the course of now two and a half years, we've developed the best AI for business with a wide range of use cases and all those we just mentioned, plus like 50 more judged against performance. [00:15:55] Austin Distel: So SEO, performance, originality, creativity, brand and capacity for your uniqueness. So generative AI with Jasper doesn't have to be generic. It can be in your tone of voice with your brand, and you can teach it knowledge and specialized information. That remains private for your company, but it's like basically your knowledge base on what do your products do, what makes them different, how you stand out against the competition. [00:16:23] Austin Distel: And so now your personal assistant, Jasper, can write intelligently about your company. With performance in mind, with like still really creative eye, eye-popping, jaw-dropping copy [00:16:00] that gets people to click, engage, buy. And then we look at collaboration. You want not just to go to an app and chat with it, but you would rather have it integrate into all your tools and you would want it available inside of Salesforce gmail. If you are using a WordPress or Webflow to build your website, you wanna be able to write copy in those tools. If you're writing blog post, you want it inside a Google Docs, and so Jasper works inside of all of those, of course. We just really take like a team first approach naturally seamlessly integrated into all your tools and it's on brand for your company. [00:17:19] Michael Scharf: That was one of the interesting things. A while back, many moons ago, of course, I did a lot of work in direct marketing and I loved the fact being numbers oriented that we could test these things. Now with what you guys have developed, you are kind of turning that on its head because you're putting the formulas in first and then deriving the product coming out of it, which is great. [00:17:42] Michael Scharf: You mentioned there's a lot of other problems that Jasper AI can be applied to. What are some of the, I don't wanna say most popular problems that you guys are seeing your customers. [00:17:54] Austin Distel: Yeah, so the most popular is content improvement. So you come in with your own copy that you've written, and sometimes that's really just a content brief. [00:18:06] Austin Distel: It's not even like high resolution. It's kind of raw. And when you enter using the ai, you're more thinking, I either wanna get the ball rolling, I'm lost for thought, I'm facing writer's block and I need to get the ball rolling. Or I've already gotten the ball rolling and I've hit a wall, a creative wall, or I need an assistant to review my work, to give critical feedback, to improve it in many capacities. Something that I'll do, for example, I'm a guy in a busy startup, got a lot of work on my plate and I'm trying to get written copy for all these campaigns and review my teammate's performance and things like that. With someone who's strapped for time, you could do is just write the email kind of frankly as you would want to say it, and then say, “Hey Jasper, can you make this more empathetic?” Or, “Hey, Jasper, can you make this more creative, more funny?” I'll do my emails in the tone of voice of Jerry Seinfeld. And that tends to go over well. It's not like humor that's outright funny, but it's enough to like get you to be like, that's clever. [00:19:21] Austin Distel: That was fun to read. [00:19:22] Michael Scharf: Oh, come on. As a writer, humor is the hardest thing in the world to write. It just is. How does Jasper offer their products to their customer base? Is it subscription model? Is it by the interaction? What's your model? [00:19:38] Austin Distel: Yeah, so the model is basically you pay per user and the more people you add on your team, the more licensed to the seats that you get. [00:19:48] Austin Distel: And there's features that are like more for enterprise and really just focused on like, they're kind of goals, but there's a really easy entry point, price point. I think it starts as low as 29. The most popular is 59 bucks a month, and then there's like business plans and stuff, but it's really accessible and it's focused though on the practical business use cases. When you use Jasper, you're looking for an ROI. When you use Jasper, you're looking for the admin control and the creativity and like the on point brand functionality that you would expect out of a business tool. This is not where you're gonna create your own family recipes. [00:20:28] Austin Distel: This is not where you're going to ask it to generate a workout routine or to summarize your private journal. This is for business. [00:20:37] Michael Scharf: Okay. A lot of what you've talked about in describing the story and how you guys got here sounds to me, and I'm not the greatest expert in the world on generative AI, but a lot of it sounds like your customers are creating their own training material to train Jasper on their brand voice and their specific issues. [00:21:00] Michael Scharf: So I guess the easy question is how much of what I would bring to the table as a customer is going to be me training Jasper to do the work. And how are you guys connected to existing, you know, open AI and other LLM-type models to at least come up with a starting point? [00:21:21] Austin Distel: Yeah, so the Jasper AI engine actually has a lot of layers to it. And so OpenAI, we are very fond of them. They're one of our biggest, most important models that help Jasper. And we have a multi-year contract with them. We help understand how to use the AI. We bring awareness of practical use cases. And so it's really hard to train like a large language model. On these individual, how do you write a viral tweet thread or what would success look like for a direct response Facebook ad? And so we are genuinely partners in that way. We have a Slack channel that we're always talking with them in. And so it's a very friendly relationship. It's non-competitive. [00:22:08] Austin Distel: But we're not fully reliant on them. We have like a pretty large AI team ourselves. And so building that model, we also have our other partners, philanthropic, cohere and between them. if you look at Jasper's uptime, it's very high because we're not reliant on one AI to have that stability that companies are looking for. [00:22:28] Austin Distel: They're looking for that always on AI that they can have their app rely on. So if you're using the Jasper API, it's not only relying on OpenAI, there's the whole Jasper AI engine is a mixture, as you could say. They're an ingredient in the recipe. Among that AI engine, you would also [00:22:00] have your language translation. [00:22:54] Austin Distel: So we work in over 30 languages. So let's say that you have a team all around the world. They can either write in their own native tongue that's easier, and then translate that. Or they can, write in English and export in a new language. And so you're trying to go and enter a new market. Like I'm trying to open up the German market. [00:23:15] Austin Distel: How do I write a landing page in German? And so that's like an example of another layer of the AI engine. Then you have comprehension, conciseness, originality. We have plagiarism checker built in grammar. We acquired OutRight, which is a very well-known Chrome extension. You add to your browser and it helps correct and improve your grammar. [00:23:36] Austin Distel: So there's that involved in the AI engine and then ultimately your brand voice level. Now that level of the pie is for your account only. So when you think about like, if I were to upload all of our documents for a company so it understood all about us. No one else's AI is going to learn from that. It's only yours. [00:24:00] Austin Distel: Okay. Makes a lot of sense. This is your AI, there's a base understanding, and then when you're logged in your account and you're on a business plan and you're uploading all your company information, your brand style guide, your products, and each of your audiences, now it's starting to learn and starting to cater content. Reading that before it writes. [00:24:25] Jason Scharf: I have a quick question though on that though. So there's the brand style, like obviously I don't want to be sharing that amongst the different customers and you have the underlying of OpenAI and philanthropic, but how does Jasper set learn across the customers? [00:24:44] Jason Scharf: Obviously there's the federated data and you wanna be able to learn from what they're doing to be able to offer better tools kind of across the board. So how do you balance those pieces? [00:24:56] Austin Distel: Yeah, so a Jasper, like your data is not the product. It doesn't get distributed, sold, or even used to influence the other customers on our platform. [00:25:05] Austin Distel: Your usage is kind of contained to, to your account. When you look at what OpenAI and maybe these based AI's are, they are gonna have their own privacy policy, and I won't speak for them, but the content used within Jasper is trained only for your account. There are AB tests, that are run where the model is always being trained on for performance to say, was this version of the model more or less effective? [00:25:38] Austin Distel: Did it get the result you wanted? More or less? Those are the kind of training data that you could say, but it's not learning information like knowledge. What it's doing is programming the tolerance of the model. To perform better for you. And so that's how you know the quality of the output of Jasper is really high, is because we're running a lot of AB tests all the time. [00:26:03] Austin Distel: And so when you give that thumbs up or thumbs down on the output that says, Hey, model good behavior or bad behavior, if you did not copy, the output, which is a sign of that you're about to use it. If you didn't like copy and paste it, that's bad behavior. Like the model didn't perform, it didn't give you the output that you wanted, but if you did copy it, that means that, hey, I liked that enough that I'm gonna save it to my clipboard. [00:26:28] Austin Distel: I'm about to use it, bring it into another tool, or something like that. Use it as a working point to continue on with. [00:26:36] Michael Scharf: All right, so now I'm gonna hit you with the hard question. [00:26:39] Austin Distel: Okay. [00:26:40] Michael Scharf: Couple of months back, Dave was talking about your raise. You guys raised a hundred million dollars, and he says, well, we're sitting on, I'm not gonna quote him directly. [00:26:50] Michael Scharf: He's like, we're sitting on this big stack of cash and we've looked to acquire some great companies or some great people, so come on down. Now the question I guess is twofold. One, what are the pieces that you're looking at? What should we expect next outta Jasper? And now that OpenAI has started talking about an API and plugins and lots of room for others to be playing in the same lake, if you will, does that put you more in competition, at least for companies and people? Talent basically to start building these add-ons and these new capabilities. [00:27:34] Austin Distel: Yeah, it's a great question. So we raised 125 million at a 1.5 billion valuation that was raised this past summer. And since then Jasper had a ton of growth and we've grown the team as well. So when we first raised, I think we're a little less than 50 people, and now we're well over 200. [00:27:54] Austin Distel: Many of these are engineers, support team, a mix of like mostly product, so Frontend product and Backend product AI engineers. So you're looking at a lot of output coming out soon, if not already. Like you look at our shipped and it's like every day there's something new shipped. The rate of innovation is really insane in the industry right now. [00:28:17] Austin Distel: We had a call yesterday with my team and I was like, this is insane. It's hard to even feel like you're in the now when you're in like the fastest growing ai company right now, it's hard to even stay in the now when you're in the now, and that's what's crazy. Every day there's like five headlines of even like keeping up with the whole Microsoft and Google, battle that's happening. [00:28:40] Austin Distel: It's hard to get a grasp on like all of that unless you're like a journalist and that's your job to like every day just be reading and consuming. When we're heads down, we're building. With that said, a few innovations that you can look forward to are really like threefold. There's three pillars Jasper is focused on over the next 12 months, building our brand voice capabilities, making it basically marketing and sales campaigns seamless. [00:29:10] Austin Distel: We wanna think in the mind of marketers when you go and if you were to hire an agency, a lot of agencies use Jasper. It's like one of our biggest audiences. They consume their client info, or if your brand upload your client, upload your own info, and now you can train the model once in your account and it generates high-quality on-brand outputs. [00:29:35] Austin Distel: Layer two. Jasper does not need to be contained in its own ecosystem, its own tab. Now Jasper can be everywhere with the browser extensions. You can now add Jasper to Chrome and use it inside of Gmail or any other tab, like I was using it, in HubSpot yesterday. And so yes, now it's available on the other side of your keyboard. [00:30:02] Austin Distel: Just do command J and write your prompt, and then you look at collaboration, admin, all of that stuff, the things you would need to scale, saving projects and performance and all of those things. You look at our API comes out in the next 10 days, and so look at that. A lot of companies will be building on that. [00:30:22] Austin Distel: We're building a tech partner, ecosystem. It's a mixture of many AI's as I said. So we're agnostic to any particular ai and we are building a performance layer on top of the existing AI's that you see today, making it for business. So those are our three pillars of what Jasper's gonna be all functionality revolves around those. [00:30:50] Austin Distel: And we just did a hackathon. I'm excited to see what came out of that. Basically, we had like 80 engineers in Salt Lake City. They were actually building within like 48 hours all of the ideas that they've kind of been sitting on. And they just went and built 'em, blindfolds on and just like go and do it. [00:31:08] Austin Distel: And that's really exciting to see just the energy that's kind of happening inside the company. It's infectious. It's fun. I feel like I'm on the fringe of innovation every day. [00:31:18] Jason Scharf: Well, there's an interesting thing you just said that just kind of, I realized when you said you were using it in HubSpot. You and your team probably are in a unique position at a company like Jasper, because obviously as the head of marketing, you're obviously trying to get it out there, but at the same time, you represent the customer in a way that, unlike other companies, like, yeah, I probably wanna be using Jasper AI to be marketing Jasper. [00:31:43] Jason Scharf: And so this is a real unique case of eating the dog food. So I'd be curious how that role is probably very different than in other companies. [00:31:50] Austin Distel: Yeah. A core value of Jasper's brand, and that goes into our marketing. It goes into our customer service, it goes into our product and development is that Jasper is the practical business version of AI. [00:32:09] Austin Distel: And so every day we are building our own practical use cases for, in our daily workflow, we're coming up with a campaign. Great. Where does AI fit into this, and when is human involvement versus AI involvement? When does the baton get passed? And sometimes it's more like a soccer field instead of a relay race. [00:32:31] Austin Distel: So the soccer field is, I dribble pass, the AI dribbles passes back to me. And so that's really this kind of dance that we're discovering. We're also able to give feedback on our own product, and so our engineers interview our team internally and say, Hey, is this, does this prototype solve the need? And so we're able to have that kind of fast turnaround time, which is why you see our development so fast. [00:33:02] Austin Distel: We also have a huge community of marketers. Like a hundred thousand people are in the group, and their voice is pretty loud. In our product development. This is how we've always built product, is that they help inspire the ideas. And needs from the product team and our engineers are in that group. [00:33:20] Austin Distel: They're listening, they're reading the comments. And so a customer-first approach, instead of like being all fancy about AI technology, we're all about like fancy AI outputs. We want the outputs to be cool. We are really good. However, we get there doesn't quite matter. Of course, it matters, but like we don't need to get caught up in the steak. [00:33:42] Austin Distel: We want the sizzle. We want to know that it performs. And so, That's kind of how we like think about it internally in our own team, in our marketing team, because we do eat our own dog food. [00:33:54] Michael Scharf: So Austin, I gotta ask you a question that ends with a question about Austin. You guys just did like four weeks ago, five weeks ago, a great ai, a generative AI conference, and everything we read about it says was smashing success and it was in the bay area. [00:34:14] Michael Scharf: Austin, why wasn't this in Austin? [00:34:17] Austin Distel: Well, you know the amount of technology that's built in Silicon Valley and just kind of the ecosystem is currently there and we are one. We built that conference in 60 days. Kind of insane from a conversation with an investor, like, don't do it in six months from now. Do it in six weeks from now kind of thing. [00:34:38] Austin Distel: We did it on Valentine's Day because that was the only day that the venue in San Francisco had. It's not like we wanted that, but it was what was available. [00:34:48] Jason Scharf: We're sure there were a lot of significant others that were upset about that. [00:34:51] Austin Distel: They were, but we had Jasper write 'em love letters, so that worked out well. [00:34:55] Jason Scharf: There's a new found use case. [00:34:57] Austin Distel: And so yeah, I mean we are actually right now in conversation with venues about next year's conference, but basically we are just thinking how can we create a sold-out conference and not a meetup. I'm talking and 1200 people showed up on an inconvenient day on a Tuesday Valentine's Day. [00:35:17] Austin Distel: So we had to make sure that travel wasn't part of the plan. It's a one-day event. And so where does you know it look like on the map that 1200 people can show up on an inconvenient day and talk about Generative AI? Also, what's unique about that conference is? Who was it for? It was for people interested in the subject, and that's a wide range of audience. [00:35:40] Austin Distel: So among the audience, 10% were our current employees. We had roughly 20% were customers, another 10% were journalists, and then maybe 20% were perspective companies coming to learn about the AI space. So like for example, LinkedIn's executive team was there, and so then there's like a lot of conversations that we're having from enterprise value, looking at us as a secured solution. [00:36:08] Austin Distel: Then you have developers and product people that are interested in the generator of the AI space. We had a lot of perspective employees. So like Jasper's, just this magnet for amazing talent right now. And with all the layoffs happening in like non-AI sectors, we kinda look at it as like, this is a yard sale. [00:36:27] Austin Distel: This is amazing. The people that we're attracting to our company are like dream all-stars and like I just got to hire my own boss. She's incredible. Megan was at HubSpot, a VP there, and so like getting to be in a place today where we're surrounding ourselves like the core, the original team is surrounding ourselves with like the most successful, talented multi-year veterans in the B2B SaaS software world and understand how to build this machine to be practical for large companies. [00:37:03] Jason Scharf: So I want to kind of step back a minute now and think about Jasper as being one of the unicorns in the Austin ecosystem and kind of look at that from the lens of how we think about the innovation in the region. [00:37:18] Jason Scharf: So you are not alone in creating the application or that kind of abstraction layer on top of deep tech, whether it be ai, quantum, or genomics, or just a couple of the examples that are going on here. How do you think that positions our ecosystem as being that kind of abstraction layer rather than the developer of that deep technology? [00:37:41] Austin Distel: Well, something I know about Austin Texas is it is pretty great weather year round, and a lot of people here are family oriented. It's like almost like lifestyle and family. Tend to, as a core value come before work in a good way, in a healthy way. Yet there's a level of ambition and intelligence that is magnetized to this city as well. [00:38:11] Austin Distel: And so what you get is a really interesting culture. The culture of our startup ecosystem. As of right now, we are also attracting a lot of Californians and people from New York and Miami right now as well. Like there's an influx of new personas coming to Austin, but I think there's a lot of like marketing creative focus in Austin. [00:38:36] Austin Distel: A lot of that second layer of using deep tech with like usable, functional, the business, like application on top of Deep Deck. I think that if we are trying to be more like Silicon Valley, it'll be. Well, remote work culture has really helped that. I would say. We are lucky that that has kind of happened where Silicon Valley kind of got broken up. [00:39:04] Austin Distel: New York kind of got broken up where you don't have to be there to be super successful as a developer and now you can kind of be anywhere and you can buy a house and you can build a family and that's honestly why after Y Combinator, we moved to Austin Texas instead of staying in the valley. [00:39:20] Austin Distel: Because we wanted all those things I just mentioned. Yet, when I look at, our own team at Jasper, we have about 225 employees. Austin is home to 40 to 50 of them. So one-fourth of the company. A lot of them, I would say 50 to 60, are in Salt Lake City. Then you look at the Bay Area and then kind of spread all over. [00:39:45] Austin Distel: And then we have, via acquisitions, our team in Sydney. Yeah, so kind of just growing throughout the US but core would be those three, Austin, Salt Lake, and San Francisco. [00:39:58] Jason Scharf: And that's a great kind of segue into the kind of the next question I was looking at here, in terms of talent. What is it, what's the core that's here? [00:40:05] Jason Scharf: What are you guys getting from Salt Lake? And then what is the strength from a talent that you guys are seeing here, and what do you think we need more of? [00:40:14] Austin Distel: I think we need more in Austin of Backend engineers, that are very developed and focused. A lot of them live on Jasper's team in Salt Lake City, or they're just purely remote and they're kind of spread all over the whole US like all throughout the east coast and kind of random cities, which is interesting like things I wouldn't expect, after all of this. [00:40:40] Jason Scharf: Not that I'm telling you to poach from here, and I'm just, this is my own back, but back like, are Dell and Apple and Google, like the big texts that are here, is that not, and this is my own, is that not the talent that's here? And it may not be. I don't know. That's why I'm asking. [00:40:55] Austin Distel: Well, it depends on what kind of, what level of company that you're building. I think that it takes a unique energy to be in a fast-paced startup, especially like ai, it takes an agility that has to be like part of your nature to be agile. And if you're looking for a stable, large company, like they're here, like Dell. [00:41:17] Austin Distel: Go to Oracle, go to Indeed, or any of those like big companies, if you're looking for an exciting new project and something launched yesterday and now you have to react today and you have to build something and you're kind of expected to tinker and you're expected to like be on the fringe of innovation that requires a different per type of a person. [00:41:41] Austin Distel: And it's more of an inventor. And so Austin Texas is very entrepreneurial as a city. And so I think that's where a lot of startups you see kind of popping up, but I don't know how many, because I'm just not even there. I'm not even in the ecosystem of a large company. So I haven't seen, what level of developers are in Austin for that type of company cuz we're not really attracting the corporate type of talent. [00:42:11] Michael Scharf: Well, Austin, that makes a perfect segue into our last question. Austin Distel of Jasper AI, really appreciates you coming on and what's next for Austin? [00:42:24] Austin Distel: Well, I just built a home near South Congress and so this has been exciting. Right now as this interview's happening, Infrared Sauna is getting built in my backyard, so I'm excited to do that in a cold plunge this summer. [00:42:37] Austin Distel: So I'd be on Ladybird Lake, paddle boarding. And outside of that I wanna be hosting AI meetups and bringing together this community of people that are really interested in Generative AI. Whether we go and meet up at Lazarus on the East Sixth Street, or we host a conference and we choose an Austin local venue. [00:42:56] Austin Distel: I was just over at Soho House during South by Southwest and we had a panel on Generative AI and what it means for advertising. So these are the kind of things that we can be really together, like we can grow the ecosystem. I think right now it's fragmented. I would like to see more glue happen. [00:43:16] Austin Distel: I'm happy to raise my hand to help make that happen and reach out to me on Instagram, Austin Distel and if you're in Austin Texas, let's throw something. And either the Jasper HQ right off of B Caves by Zilker Park, like any of this, we have like a cool community we can build together. [00:43:34] Austin Distel: What's interesting about the Generative AI ecosystem is everyone's innovating together, but privately they're coming outta stealth mode. They're tinkering at night, and so nobody really understands like, are we competitors? Are we partners? Are we not even related? And really, I think it can be all Jasper's always thinking, do we buy or build or partner and like it could be any of those. [00:44:03] Austin Distel: And like we're super open to all conversations. And I also believe this is a wave that's only growing. Today’s generative AI is the smallest it'll ever be. Like it's growing. It's gonna be part of our ecosystem more and more and more. And so that just means that there's more opportunity. It's not like us growing is taken from their growing or them growing is taken from us growing. [00:44:28] Austin Distel: I think actually we're all gonna make each other better. So that's why I would love to get into the same room. Let's have conversations, let's make our products better together and maybe team up. [00:44:38] Michael Scharf: That kind of collaboration is exactly what Austin needs and has done so well in the past. Austin Distel Japer AI, thank you so much for being on the Austin Next podcast. [00:44:47] Austin Distel: Thanks for having me. [00:44:50] Jason Scharf: So what's next Austin, we're glad you've joined us on this journey. Please subscribe at your favorite podcast catcher. Leave us a review and let your colleagues know about us. This will help us grow the podcast and continue bringing you unique interviews and insights. Thanks again for listening and see you.