Subscribe
Share
Share
Embed
AI is the biggest technology shift of our lifetime. This show is about how to profit from it together.
Each week I talk with the founders and CEOs closest to AI and Content, the ones figuring this out in real time.
I’m also building an AI content business myself and share the lessons I learn along the way.
WHAT WE COVER
The Titans -- How companies like OpenAI, Anthropic, Google, Meta, and xAI are moving, and why their decisions matter.
The Incumbents -- How content giants like Disney, News Corp, Universal Music Group, and Reddit are responding to AI, and what it means for creators and publishers.
The Playbook -- Real lessons on AI business models, content strategy, creativity, IP licensing, distribution, and getting paid.
Family & Our Future -- Every episode ends with me asking my guest what AI means for our jobs, our families, and the next generation.
ABOUT YOUR HOST
Rob Kelly has interviewed Steve Jobs and Bill Gates, helped pioneer early web content licensing, and built multiple companies with more than $100 million in total sales. His work has appeared on CNBC, CNN, TIME, and Entrepreneur.
Thanks! -Rob
I'm Rob Kelly, this is Media and the Machine, a show about the biggest technology shift of our lifetime and how to profit from it. Each week, I talk with the founders and CEOs closest to AI and content, the ones figuring this out in real time. I'm also building an AI content business myself and share lessons of what I learned along the way. You know, life's funny. I began my career lucky enough to interview leaders like Steve Jobs and Bill Gates.
Rob Kelly:I Then went on to be a three time founder and CEO, driving a $100,000,000 plus in revenue and some failures too. And now I'm back at the table, interviewing this new world's current and future leaders. This isn't only a business story, it's a human one. So every episode ends with me asking my guest what AI means for our jobs, our families, and the next generation. We'll figure this out together from the inside.
Rob Kelly:Welcome to Media and the Machine. My guest today is Dan Steinee, who advises content companies on AI deals. Dan has spent nearly twenty five years in licensing, including leading content partnerships at Soundhound AI. Today, he helps content and data companies figure out which AI companies to approach, what kind of deals to pursue, and why chasing only OpenAI and Anthropic may be a mistake. Dan built Nexus, a database that tracks several 100 AI companies.
Rob Kelly:For one book publisher, his process surfaced 49 potential partners, including Pearson, Chegg, Perplexity, Coursera, and several emerging content marketplaces. We also discussed why training an AI model can be like putting a banana into a smoothie, why rag deals may give publishers more control, and his belief that quote, people make content, content makes AI, and AI shapes people. Away from business, Dan's a songwriter, keyboard player, screenwriter, and member of the band Whiskey House, and he even plays a little Grateful Dead for us in the intro. This is Dan's first podcast appearance, which I always love. Special thanks to Denise Garcia for connecting me with Dan many years ago.
Rob Kelly:Please enjoy my conversation with Dan Steinee. Why do you care about content so much and AI content licensing in particular?
Dan Steiny:Well, you know, my entire life, even when I was a kid, I've loved content. I started out when I was really young writing songs and playing in bands, and I really care about music, and I'm also a screenwriter. And I really admire creative people and people that create content because I know how hard it is and how much it matters. And AI, I think, is a particularly interesting area because and it's also very confusing.
Rob Kelly:Are you in your music studio right now?
Dan Steiny:I am actually. This is where I I work each day. So I sort of go from my music life to my business life and back and forth. So I'm standing here right next to my keyboard actually.
Rob Kelly:Alright. I know we both love the Grateful Dead. Can you you're in a band. I know you have played dead tunes. Can you give a couple notes of Ramble on Rose?
Rob Kelly:I watched you play that live.
Dan Steiny:Oh, like like right this moment? I yeah. I think I don't know if it'll I don't know if it'll show up on the mic, but we'll try.
Rob Kelly:Yeah. Yeah.
Dan Steiny:Okay. I'm walking over.
Rob Kelly:Okay. Nice. Alright. That's enough before we get sued by the Grateful by the State.
Dan Steiny:That that's the very beginning.
Rob Kelly:I love it. Alright. I think you know I have a guitar in my usually in my background. I've been asked to strum a song before and I know it's high pressure.
Dan Steiny:You know, it's amazing how many people I I talk to have an instrument sitting behind them. I love that.
Rob Kelly:So on the business side, can you talk about what you've done and what's unique about what you do in the AI content licensing space?
Dan Steiny:I've been doing licensing for almost twenty five years, I think. And in my last full time licensing job, I worked for a company called Soundhound AI, and I was head of content partnerships. And I learned a tremendous amount about the specifics about licensing content and data into an AI company to train the models and other areas. It's a kind of new area and a complex area.
Rob Kelly:Soundhound would be a buyer in that case of content. They needed content to improve their platform.
Dan Steiny:Yeah. Yeah. That's correct. And I was talking to the content companies and working with the content companies in that job. And when I was doing it, I started to realize this whole area of of content and data and AI companies was going to get huge.
Dan Steiny:That was sort of my intuition at the time. And then of course in 2022, ChatGBT came out and the whole thing took off. And immediately we learned that the AI companies were getting a lot of the data and content through scraping it off the internet. So I realized there was a huge opportunity to help content and data companies understand where the opportunities actually lie, help them see who they should be working with, what kind of deals they should be doing, and really provide clarity on how to approach this market.
Rob Kelly:How would you describe your strong suit in the content licensing world?
Dan Steiny:What I think I've done that is really unusual is I tend to be very methodical in the way I think and very structured, kind of the way my brain works. So I started building it's really an internal market intelligence system. I track several 100 AI companies and it allows me to match content and data providers to specific opportunities, allowing them not only to know what companies they should talk to, but how should they should approach them. Like, is the type of data licensing opportunity is going to make sense for this AI company from the content provider?
Rob Kelly:Do you have a name for this thing, this intelligence platform?
Dan Steiny:Internally, I named it Nexus, but that's a name I just use.
Rob Kelly:So can you give an example, maybe a use case of how you use Nexus to help content companies connect with AI companies?
Dan Steiny:Yeah. I mean, maybe the best way is to sort of take you through a quick process of what I do when I work with a content or data company. There's a flow to it. I start out, I've created a thing I call an intake form where the content or data providers respond to some very specific questions. How much content they have?
Dan Steiny:What kind of modality it's in it? Is it text video? Who owns the IP? And many other questions. It doesn't take long.
Dan Steiny:It takes about fifteen minutes to fill out. And then I pull that information into this this system that I've built. And it's a database and a lot of other components. I won't get into the the boring details.
Rob Kelly:And normally with the content company, can you just describe, like, roughly the size of a content company that this is worth doing for? Both worth you doing for and worth them approaching you for to create some revenue?
Dan Steiny:It's not really about the size of the company. It's about where they are in terms of understanding the AI market. And so the ideal company can be larger or smaller. But say it's the BBC and they already have a whole team of people that study the AI market opportunity, that's probably not going be a great fit for me. But if it could be a larger company that they know that they should start focusing on the AI opportunity but they haven't really done their research yet, that would be a very good fit for me.
Dan Steiny:But it can also be a smaller company that just doesn't have the resources to understand this market but they have content and data. Does that make sense?
Rob Kelly:Yeah. Perfectly. So a content company fills out this intake form, fifteen minutes, and you've got this nexus matchmaking database of content companies and AI companies. So what happens next? Can you pick maybe an example of a type of content company and just walk through how that leads to some matchmaking opportunities for them?
Dan Steiny:A recent example that comes to mind is I was talking with a company and they had millions of books that were available. And their question was like, how do we approach the AI market in general? And this is something I see a lot where it's this sort of like, oh, we have content. What do we do with it? And my objective with this is to always bring clarity to these companies about not only the big picture about how they should approach the market, get very specific, as specific as I can.
Dan Steiny:Because I know people are ultimately trying to get licensing deals done and create revenue. And one of the core sections of this brief that I provide during the engagements is what I call priority AI licensing opportunities. And it's a section of the document that is really the heart of it because it matches their specific kind of content, the IP they have with very specific companies and opportunities. I put in different buckets to make it as easy as possible for the content or data company to be proactive. And I break it up into possible direct buyers first, which is the strongest fit, like the most likely commercial fits.
Dan Steiny:For each company I provide, I talk about what they do, why there's a match, and also recommended action. And I provide other information like have they been in a law suit before? Have they done other licensing deals? And information I think that's really helpful to the content or data provider to have some background. And then for example, this book publisher, in this section of the brief, came out the likely commercial fit section, a company called Pearson.
Dan Steiny:They're a major educator publisher. A company called Chegg, they do study support, AI study support, Perplexity AI, and nine other top priority matches. These are the key companies. But after that, I do a second section, which is still a strong fit, but there's probably more friction and perhaps a narrow narrower commercial path.
Rob Kelly:What do you mean by more friction?
Dan Steiny:A great example is companies often go, oh, why don't we just talk into OpenAI and Anthropic. Right? Well, that's great, but they've got a million people trying to ping them every day. Those kinds of deals can take a long time to close and to get the BD team to actually engage with these companies. That's an example of friction.
Dan Steiny:To name a few specific companies, actually, it's funny that you bring that up because in this section of the brief, OpenAI is one of them, a company called Cohere. Cohere builds enterprise focused language models, and a company called Coursera. These are I'm just giving three examples. There's about 15 companies in this section of the brief. And the last part is the infrastructure and marketplace and enablement platforms, and there's about 20 companies.
Dan Steiny:These are companies that compare the content. These are marketplaces that can you can put your content, make it available there, which increases the likelihood that you'll get discovered.
Rob Kelly:What's an example of a marketplace in this case for this book publisher?
Dan Steiny:Yeah. So Microsoft Publisher Content Marketplace, ProRata AI, Prodige AI are some that I'm seeing here listed on this specific brief, a company called Tollbit as well. Those are just a few. And there's and each one of these, like the AI companies, explain why they're recommended, why there's a match, and what specifically this company should do to engage with them to increase their likelihood of success.
Rob Kelly:And so how many total matches in this case for the book publishing company were there if you break it down by the primary, secondary, and infrastructure?
Dan Steiny:Yeah. I think it was 49, including the the likely direct buyers, the secondary, and then the the infrastructure platform companies.
Rob Kelly:Nice. And by the way, one counterintuitive thing there is that OpenAI and even large other large companies like Cohere don't necessarily come up in the primary buyer section because of friction and maybe other challenges to getting a deal with them.
Dan Steiny:Yeah. So many of the content and data companies that I talk to just think about the big players, you know? And I think one of the things that this process reveals that's very valuable is there's a lot more opportunity out there. In fact, some of the opportunity are these these companies that aren't so well known but are eager and need this type of content to make their products work better.
Rob Kelly:Right. I know in my conversation with Marty over at Troveo and Clint at Curiosity Stream that these startup unicorns who got $500,000,000 in fundraising and need to go out and buy some data, in some cases, those are higher quality buyers than in OpenAI or a Google. Is that your experience as well?
Dan Steiny:That's exactly what I'm talking about. It's a very competitive space.
Rob Kelly:What else is in this brief that you generate for, in this case, the book publishing company or any content company?
Dan Steiny:It's got seven sections in it. The first section is the executive summary where it really looks at all the information in it and gives very CEO level recommendations and kinda what it means to them. In addition to the specific buyers, which we talked about, there's a fit assessment which looks at their data and is it ready, is it prepared, why not. There's a whole use case sections section which is really eye opening to me because it talks about like how this content is actually going to be used by these companies and what types of products. A lot of this is information that's not that easy to gleam unless you really study these different companies and what's going on with them.
Dan Steiny:And then there's a section called licensing models, which really gets into the contractual part where you look at the different terms that are most likely going to be successful when they approach the different AI companies, which is can be super helpful. And then I end it with the risk and recommendation section where I I try to be as blunt as I can where there there could be problems with the content that they're providing and also very specific overall recommendations, how to approach it, looking at the AI buyers, the infrastructure companies, and the the whole ecosystem. What do you do? How should you approach it? And what steps do you take first?
Rob Kelly:And if the brief is one deliverable, can you share what other deliverables you provide for a content company?
Dan Steiny:One of the things I help the data or content provider with is taking all this information they receive from this document and then turning it into actual marketing materials. And I like to recommend that they create a one sheet, which is designed to share with the potential AI and companies that they want to work with. It really helps because a lot of these AI companies will have content companies come to them and say, hey, look, I've got a bunch of content. We really want you to license it. But if you can approach them showing that you actually know the market, you know the type of structure that they would like this content to be in, it can save a ton of time and increase your likelihood of success dramatically in my opinion.
Rob Kelly:So the one sheeter you're describing, it's sort of a AI licensing position statement. Is that a good way to describe it?
Dan Steiny:Yeah. Absolutely. It just it lists all the things that AI companies care about. It's basically a sales sheet, a one sheet of, you know, how much content they have, how it's structured, whether it's available for just for training, for example, or is it available for rag licensing or other types of licensing structures? So it basically lays out everything that the AI all the questions the AI companies can already have is in this one sheet or so.
Dan Steiny:They can see it and think, these guys know what they're doing. They're serious about engaging with us, and and we should talk to them, hopefully.
Rob Kelly:If you're a content company, how do you think about whether to go direct to AI companies to license your content to them or through a middleman, like a broker?
Dan Steiny:I think it really depends on what what kind of resources and budget you have in terms of the business development part of it. And if you have somebody inside your company whether it's senior executive or somebody that you've hired to do business development, It's great to be able to do it yourself but there are people out there that have relationships with AI companies already in place and they can be very valuable for you to contact them quicker and easier. But you know, both are great. One's not better than another. It just depends on resources.
Rob Kelly:In terms of the impact on content, can you talk about what's different between AI, this new wave of technology and its impact on content versus, say, downloads or streaming? You went through those waves. Right?
Dan Steiny:Yeah. Yeah. I have watched many different markets develop through the years in relation to content. I've been doing this for over twenty years working with companies originally like Liquid Audio, which was one of the pioneers in streaming and downloadable music. And then I worked in a company called MusicNet in New York City for a while.
Dan Steiny:And that to me was like the early days with content and technology. And I loved it because it was really focused on helping the content reach more people in in new ways. So it was really about distribution. To me, what was interesting about that time versus now is like a song still stayed a song. It was being distributed through just a different thing called the Internet, which was very interesting.
Dan Steiny:But what's happening now, the content can be embedded into it and mixed with lots of other content to create music more easily by using prompts. And in this case, the from a licensing perspective, it gets very complicated because if somebody let's just use a song as an example. If they're licensing a song, it gets blended. If it's a training deal, it's like a banana going into a smoothie. So once it's the smoothie is made, it's very hard to take the content out of the training model.
Dan Steiny:So these types of deals are make a lot of content companies nervous because they don't really have control.
Rob Kelly:You get you can't get the banana back.
Dan Steiny:Yeah. You can't get you can't get the banana back. Exactly. So that's that's the training thing. And that's true with pretty much any AI licensing except there's a whole new area coming in right now, which is very interesting, which is the the retrieval and the rag and these types of licensing deals.
Dan Steiny:And that's where they keep the content separate from the main training model. So if somebody asks for a specific type of content, it is retrieved in a separate part of the database so the content company can have more control over their content because it's not mixed into the main model. And they can also say if they wanna remove it for some reason, if there's some kind of issue with the relationship, they can take it out of the model. And this is the direction I see this whole area moving into and we're seeing more and more deals like that now getting announced.
Rob Kelly:And you had this in one essay you wrote this quote kind of concept is that people make content, content makes AI, and AI shapes people. Can you share what you mean more on that?
Dan Steiny:Yeah. Thank you for reading that. You asked me at the beginning of this podcast, like, why I do this, and part of it is because I'm a musician. But another big part is that I my whole life have just been I love bookstores. I love content, and I really feel like the books that I read, the the teachers I had, and the songs that I heard really shaped me as a person in a profound way.
Dan Steiny:And I believe that's true with everything for everybody. And I also believe that in the future, people are going to get more and more information from AI. And so when I say the content feeds the AI and the AI shapes a person, what I'm talking about is how important I think the content is to the models because ultimately, the model is what the content is, and so that's what I'm talking about. So it's a sort of like interactive thing where people create content, that content goes into the AI, and then the AI ends up shaping those people. So it's a sort of circular thing.
Dan Steiny:And I think it's I I just think that the content is is super important. It's gonna be very, very important to help people think in the future and more so every day.
Rob Kelly:Now being a musician yourself, how do you feel about AI companies like Suno and Udio helping others create a new song based on training on existing music? They could just type in a prompt and generate a song. Right?
Dan Steiny:You know, honestly, it depends on the day of the week, how I feel about it. I kinda go back and forth. I mean, as as a songwriter and putting all the effort into writing a song, there's a part of me that I don't like it because I don't really think it's being creative. I think, you know, writing a prompt and saying I want a song like this and I want it to be about this and it spits it out really using all the other work that has gone into creating the songs that they use to train the model isn't really that creative. And I'm really encouraged to see some of the companies now like I think Deezer's announced it and others where they're separating the AI created songs from the songs that are created by an artist.
Dan Steiny:Yet, I don't wanna be closed minded because technology is always shifting. So when I say it depends on the day of the week, I I don't wanna be closed minded, but I I do have sort of a bit of a bitter taste about it at this point.
Rob Kelly:Do you have a favorite AI tool that you use as a musician?
Dan Steiny:Yes. I actually do. A tool I use almost almost every day when I practice these days. It's from a company called MusicAI, I believe they're called. And it's a tool called Moasis, and it's spelled just because it's kind of a weird word.
Dan Steiny:It's spelled m o I s e s. You can drop an m p three or an audio song from any format, and it'll break up all the instruments in separate components. So you can remove or add instruments. And for me as a keyboard player and harmony singer in our band, I'm able to remove the keyboard parts from songs that I'm trying to learn and practice against the actual song and also do the same with the harmonies. And it also adds a metronome and tells you what key you're playing when you're playing on the app.
Dan Steiny:Super useful and it helps you become a better musician which is very different than some of these other AI tools. I love it. Super helpful.
Rob Kelly:Do you consider yourself an AI optimist or a pessimist or somewhere in between?
Dan Steiny:I would think I would fall in the optimist zone. I've I've watched technology evolve for thirty years and the world hasn't fallen apart yet. There's a lot of doom and gloom, but I think the value is gonna outrun the negativity, but I really don't know what's gonna happen.
Rob Kelly:What are you telling young folks in your life about AI?
Dan Steiny:I guess I would warn, you know, you don't wanna become too dependent on these things because they're not real. And make sure you have relationships with real people because that's way more important.
Rob Kelly:Alright, Dan. Thanks for investing the time with me today.
Dan Steiny:You're welcome, Rob. It was it was a lot of fun. Thank you. I'm right down the street. Let's get together soon.
Rob Kelly:Alright, man. Thanks again. Take care. Well, this is Media and the Machine. A few things about you and me.
Rob Kelly:If you wanna hear about the next new episode, make sure you hit follow on the show in your podcast app. If you wanna go a little deeper, head to mediaandthemachine.com and subscribe. When you share your email with me, can see handcrafted transcripts, read the essays in my newsletter, and be the first to hear about who the guest is on the next show. You can also email me directly from there. Maybe you wanna recommend a guest.
Rob Kelly:I'll give you a shout out if you do. I love paying it forward. From time to time, I also open up office hours and host small meetups for subscribers, just to meet, talk, and build things together. If you're creating something of your own or thinking about it, I'd love to help. Maybe you've got a podcast in you.
Rob Kelly:Finally, I don't have a marketing budget for this show. So if it's finding you and others, it's because someone like you passed it along. I'm genuinely grateful. If you have a moment, an honest rating helps me make this better for you. You can just go to the show page and click one of the stars.
Rob Kelly:And I'd rather you give me a low rating than no rating at all. I mean it. It pushes me to get better. Thanks again, and see you next time.