I’ve seen a lot of change in Silicon Valley. I’ve built and sold two companies, RemoteTeam and MovieLaLa. I’ve also been fortunate enough to be an early investor in over 200 companies, including some of the foundational AI companies of our time like Anthropic, OpenAI, Scale AI, and Hugging Face. And I’m telling you, we’re on the cusp of another massive shift. The way we build and sell software is about to be completely transformed. The era of traditional SaaS is ending, and the age of the AI model marketplace is dawning.
For the last decade, SaaS has been defined by a specific model: monolithic applications, seat-based pricing, and slow, incremental innovation. We’ve all gotten used to it. But it’s a model that’s starting to show its age. It’s too rigid, too expensive, and too slow for the world we live in today. I remember when I was building RemoteTeam, we were constantly frustrated by the limitations of the SaaS tools we were using. We were paying for features we didn’t need, and we were locked into long-term contracts that didn’t make sense for a fast-growing startup. It felt like we were trying to build a rocket ship with a wrench.
The End of SaaS as We Know It
The traditional SaaS model is broken. It’s a one-size-fits-all approach in a world that’s increasingly demanding customization and flexibility. The problem is that most SaaS companies are still selling software like it’s a physical product. They’re selling a box, and you have to take the whole box, even if you only need one thing inside it. This is especially true for AI-powered features. Companies are trying to shoehorn AI into their existing products, and it’s not working. It’s like trying to put a jet engine on a horse-drawn carriage. It’s not just inefficient; it’s a fundamentally flawed approach.
I’ve seen this firsthand as an investor. I get pitched by SaaS companies all the time, and they’re all telling me the same story. They’re all talking about their new “AI-powered” features, but when I dig in, it’s usually just a thin veneer of AI on top of the same old monolithic application. It’s not true AI-native innovation. It’s a marketing gimmick, and it’s not going to be enough to survive in the new world that’s coming.
The Rise of the AI Model Marketplace
So what’s the alternative? The AI model marketplace. Think of it like an App Store for AI. Instead of buying a monolithic application, you can now buy individual AI models as a service. These models are built by specialized teams of researchers and engineers, and they’re trained on massive datasets. They’re also constantly being updated and improved. This means you can now get access to state-of-the-art AI without having to build it yourself. You can simply plug into the marketplace and start using the models you need.
This is a huge paradigm shift. It’s moving us from a world of monolithic applications to a world of modular, API-driven services. It’s a world where you can assemble your own custom software stack using the best-of-breed AI models from a variety of different vendors. It’s a world where you only pay for what you use, and you’re not locked into long-term contracts. It’s a world that’s more flexible, more powerful, and more affordable than anything we’ve ever seen before.
We’re already seeing the beginnings of this shift with marketplaces like AWS Marketplace, Lyzr AI, and the AI Agent Store. These platforms are making it easier than ever for developers to discover, evaluate, and integrate AI models into their applications. And it’s not just startups that are getting in on the action. Even the big players like Google and Microsoft are starting to embrace the marketplace model.
My Journey into AI Marketplaces
My own journey into AI marketplaces started with my investments in companies like Anthropic, OpenAI, Scale AI, and Hugging Face. I saw early on that the future of software was going to be built on top of these foundational AI platforms. These companies are not just building AI models; they’re building the infrastructure that will power the next generation of software. They’re building the picks and shovels for the AI gold rush.
When I’m evaluating an AI-native company, I’m not just looking at their technology. I’m looking at their go-to-market strategy. I’m looking at how they’re leveraging the power of the marketplace to reach a wider audience. I’m looking at how they’re building a community of developers around their platform. Because in the world of AI marketplaces, the best technology doesn’t always win. The company with the strongest ecosystem does.
The New SaaS Stack
The rise of the AI model marketplace is also changing the way we think about the SaaS stack. The old stack was all about monolithic applications. The new stack is all about modular, API-driven services. It’s a stack that’s built on top of a foundation of AI models, and it’s a stack that’s constantly evolving. This is a huge opportunity for developers. They can now build new applications and services that were never possible before. They can now create custom solutions for their customers without having to build everything from scratch.
We’re also seeing a shift in business models. The old world was all about seat-based pricing. The new world is all about usage-based pricing. This is a much more efficient and equitable model. It means you only pay for what you use, and you’re not penalized for growing your business. It’s a model that’s better for customers, and it’s a model that’s better for vendors.
How to Win in the Age of AI Marketplaces
So how do you win in this new world? Here are a few things I’ve learned from my experience as an entrepreneur and investor:
- Focus on data. In the world of AI, data is the new oil. The companies that have the best data will be the ones that build the best models. This means you need to have a clear strategy for collecting, cleaning, and labeling your data. It also means you need to be thinking about how you can use your data to create a competitive advantage.
- Build a strong developer ecosystem. In the world of AI marketplaces, your developers are your most important asset. You need to make it easy for them to build on top of your platform. This means you need to have great documentation, a robust set of APIs, and a thriving community of developers. The more developers you have building on your platform, the more valuable your platform will become.
- Embrace new business models. The old world of seat-based pricing is dead. The new world is all about usage-based pricing. This is a huge opportunity to create new and innovative business models. Don’t be afraid to experiment. The companies that are willing to take risks will be the ones that win in the long run.
The Future is Modular
The future of software is not monolithic. It’s modular. It’s a future where you can assemble your own custom software stack using the best-of-breed AI models from a variety of different vendors. It’s a future that’s more flexible, more powerful, and more affordable than anything we’ve ever seen before. The AI model marketplace is the key to unlocking this future. It’s the new frontier for SaaS, and it’s going to change everything. The only question is, are you ready for it?
Frequently Asked Questions
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.