The Future of Content is Here with Generative AI ft. Dave Rogenmoser, CEO & Co-Founder @ Jasper

Authored by Kenny Denton

Silicon Valley is buzzing with excitement around the advances in Artificial Intelligence (AI), as it continues to make a groundbreaking operational impact on businesses at scale. Generative AI specifically is disrupting the way companies operate and transforming what they are capable of. It is no longer the technology of the future, but the technology of right now, as more and more companies are turning to AI-powered solutions for a variety of use cases.

Dave Rogenmoser, Co-Founder & CEO of Jasper, is showing businesses just how impactful AI can be. Coming off of their recent $125M Series A funding round and an acquisition of AI startup Outwrite, Jasper is poised to take the market by storm in 2023. Dave joined us to discuss his journey as a founder, his thoughts on the current state of the industry, and his strategies to stay ahead of the curve thanks to Jasper’s breakthrough technology.

For those of us who are unfamiliar with Jasper, can you give us a high-level overview of the company?

Jasper is a content platform that uses cutting-edge AI technology to curate high quality original content and imagery. We’re mostly focused on marketing use cases, such as blog posts, emails, website content, and social media copy, but we plan to expand into more teams to the point where every person at every company in every function uses Jasper.

You co-founded Jasper with your two close friends, J.P. Morgan and Chris Hull. Can you bring us through your journey as founders and how you ultimately ended up starting Jasper?

J.P., Chris, and I started working together around eight years ago, and all we wanted to do was build a business together as friends. Our focus was to help people do better marketing, and our first endeavor as a group was a marketing agency that turned into a coaching program for marketers. That shifted into creating a software company called Proof, which helped B2B companies increase conversion rates on their websites.

A few years into Proof, I came across a blog called “Wait But Why,” and one of its posts was about how AI was going to change the world. I was completely sold on the technology and knew I wanted to get into that space. At that point, Proof had really flatlined, and we didn’t see a way to go forward with it anymore. We saw an opportunity to create a product that would perfectly merge what we already knew how to do well (marketing) with an emerging technology that would change the world (generative AI), and that is how Jasper was created.

V1 of Jasper was created to help people write Facebook ads, and when we got it in front of some early users in January 2021, the response was just visceral. The people who saw what we created told us that this product was life-changing, something they had never seen before. After those initial reactions, we knew we were onto something. The product market fit was there early on, and we had an existing community that could validate that. From there, we naturally pivoted the rest of the Proof team into Jasper, and everything just took off after that.

AI is buzzing right now. It’s an exciting technology in an emerging market and people are enthusiastic about it. What are your thoughts on the current state of AI and where does Jasper fit within the broader software landscape?

What we’re seeing now with AI is similar to what we saw with the boom of web3 — people are trying to figure out what it is and how to use it. But as far as utility goes, generative AI is all the things that web3 was not. It’s not nearly as ambiguous and has the ability to be useful in the near term. It’s truly the biggest shift in technology since the iPhone, and all of Silicon Valley is on fire and energized by it.

Going forward, I think you’re going to see a lot of companies adopt different generative AI applications into their tools whether it’s text generation, audio generation, or image generation. I also think you’re going to see a lot of AI-first companies pop up with various use cases. Industries will be disrupted and category leaders will be beat out by AI-first companies if they don’t adapt to this type of workflow from the ground up.

For Jasper specifically, our focus is on staying really close to the end user. It’s easy to get sucked in by all the noise, the exciting research and breakthroughs coming out, but we want to maintain a grounded view of what our customers want. Our customers don’t care about the models, they don’t care about tokens and temperature ratings. They’re just trying to write their blog post, draft an email, or create a landing page a little bit faster so they can clock out and get home to their kid’s birthday party. And that’s the beat we’re trying to drum internally. Our real focus is on being the best at what our customers need us to be: the tool that they use to get their jobs done faster.

Looking ahead to the next 12 or so months, what are you most excited about in this space?

There are several things I’m excited about. The first is getting Jasper everywhere. We recently launched a Chrome extension to provide access to Jasper functionality all across the internet and plan to build more integrations and roll out an API of our own for people to plug into.

We also want to move up in the market. We’ve got a lot of bigger companies and teams that want to use us, so we want to have more trained models that can satisfy the list of requirements that these kinds of companies want, which takes time and expertise to build.

Lastly, we want to invest further in the community. We recently announced that we’ll be hosting Gen AI, the first user conference dedicated to generative AI. We plan to do more to lead the conversation on generative AI, the ethics surrounding widespread use, and its application to business use cases.

We can’t ignore how fast Jasper’s grown over the last 18 months, going from 15 to over 140 employees, and the most impressive part is that you’ve had 100% employee retention. What do you attribute the success of your employee satisfaction to?

With our previous ventures, we struggled to create the work culture that we wanted and we struggled to make the right hires, and that experience served as a really tough but invaluable learning lesson for us. Now with Jasper, our approach is different. We’ve made a conscious effort to build a culture that is allergic to people with ego, where everyone has this chip on their shoulder that nobody has made it yet. Our priority is to hire the best of the best — top talent that wants to work with other top talent. We don’t cut corners, we hold ourselves to a high bar, and everyone here looks around and sees each other as their peers who are just as smart, talented, and driven as they are. It really does start at the top, and if you can get great executive leaders on board early, even if it’s a bit of a stretch financially, it makes a huge difference in the long run as you grow and scale your business.

We’re also just in an incredibly exciting space. If you’re in tech, you want to be in generative AI, and if you’re in generative AI, you want to be at Jasper. It’s a fast running company with the best technology, a strong mission, great people, tons of autonomy, and I think that’s what gets people to stay.

Building a large-scale content creation platform certainly comes with its own challenges. What are some of the obstacles you are facing in the market and how are you hedging against them?

With AI, the number one question I get from VCs and those in this space is, “where is the moat?” And on a macro level, I don’t think the moat is in the AI, at least not in the models. I think there is a moat around the data. There could be 15 models or so that come out next year that all write language decently well, and all of them will allow you to fine tune them only if you have a large enough data set to do so.

At Jasper, we have our own proprietary data set that our customers create for us through their feedback on what works and what doesn’t as the app generates content. That gives us data sets on high quality inputs and outputs which we can then take to any model in the world and say, “hey, we want more of this,” and then that model can presumably make it better. But if you don’t have that data set, you’re going to be stuck with a base model that is not finely tuned and is not going to work as well. So on the product side, our goal is to make sure that our research is accurate and our data is cleaned up.

That rolls into our goal of building out a strong AI team internally. At the end of the day, we just have to execute. Like most companies, we need to find a problem, solve it really well, and then build a team that can keep solving it better and faster. And we’re getting there. We have a great product, we have the right people, and now we just need to bridge the gap and get everyone in sync on how we want to continue to build this great product.

What advice would you give other startup founders in this space looking for top talent?

I think the biggest tip I could give is be authentic and share your story when you can. You can have the store, the valuation, the fast growth, the stock options with the low strike, but what will get people across the finish line is your authentic self. There is power in sharing your story, your values, your ‘why’, and I think that can often be overlooked by founders in the startup community.