[99] The Business of Open Source
[Open Source, Business Models, Open Source and AI]
GM Readers!
Sharing an essay from our Evolving Internet Insights Newsletter that dives into the business of open source software. Contrary to popular belief, open source software can also enable lucrative business models.
-LJW
(P.S. For the summary and further breakdown of this essay, follow me on Twitter)
Note: Some sections of this essay were originally released on my Evolving Internet Insights newsletter.
The world of open source is often misunderstood, particularly regarding its potential as a viable business model. When companies hear the words “open source” they sometimes equate it to “free” software. However, open source software has generated substantial economic value for companies.
What Is Open Source Software?
There is a fundamental concept we must explain first—what even is open source software. The one liner for “open source software” is software with source code that anyone can inspect, modify, and enhance.
According to the world’s leading provider of enterprise open source solutions, Red Hat, "’Source code’ is the part of software that most computer users don't ever see; it's the code computer programmers can manipulate to change how a piece of software—a ‘program’ or ‘application’—works. Programmers who have access to a computer program's source code can improve that program by adding features to it or fixing parts that don't always work correctly.
To further contextualize the prevalence of open source software, recent estimates suggest that 96 percent of all software relies upon open source software. A fundamental principle of internet technology itself is open source software.
Successful Open Source Business Models
There have been numerous examples of open source business models that have become businesses.
MongoDB has leveraged its open source document database platform to build a strong business by offering and monetizing premium management tools and support services on top of open source databases.
Databricks provides a “data intelligence platform” on top of Apache Spark and a handful of other AI-focused databases, all of which are open source. Databrick’s products make it easier for businesses to implement complex data analytics and AI solutions without dealing with the underlying infrastructure complexities. Databricks was founded by the creators of Apache Spark.
Android, perhaps one of the most widely recognized examples, is open source. Though, Google has captured tremendous value from Android through its mobile app store called the Google Play Store. As the official app marketplace for Android (which accounts for more than 70 percent of mobile operating system market share globally), the Play Store generates substantial revenue from app sales and in-app purchases – $47.9 billion to $42.3 billion in FY2021 and FY2022, respectively.
The above examples highlight that while the underlying software itself might be free, the ecosystems and services built on top generate and capture billions of dollars of value.
Open Source Business Model Flywheel
The open source playbook looks slightly different from the traditional playbook to build a business. It usually looks something like this:
Develop software that is useful to a lot of people and organizations. The software doesn’t have to solve every problem for everyone, in fact it should look more like a “lego block”—a versatile, foundational piece of software that will drive utility across various domains.
Open source this software “lego block” and make it freely available.
Because the software is useful and freely available, it becomes embedded into numerous technology stacks which fosters widespread adoption and crucially, community engagement.
The more developers that use the open source software, the more these same developers want to contribute to it. The more developers that contribute to it, the more the software improves. The more the software improves, the more other people want to use it in their technical stacks.
Then the flywheel is set into motion. 🎡
As the software becomes more prominent through proven utility and usage, organizations (and, by extension, their most senior technical talent) will also want to use the open source software. As more complex requirements arise within these organizations, the need for additional services and efficient tools arises. This is where monetization comes into picture. As in the examples above, a new company is created where its focus is bespoke support, advanced features, and professional services on top of the open source software.
Crucially, a thriving developer ecosystem is central to this model. Developers not only use the software, but also contribute to its improvement and distribution, creating a virtuous cycle of innovation, refinement, and amplification. This community-driven development ensures that the software evolves to meet the changing needs of its users, keeping it relevant and valuable.
By keeping open source software free, the above flywheel can scale and distribute a product seamlessly. Additionally, since the Internet is used globally, the reach of open source software is incredibly vast.
Open Source in AI
As we covered in 🧠 Brain Food 10, there is a fledgling open source movement in AI. However, since AI is earlier in its lifecycle, there are some open questions around open source.
Building and developing foundational, closed source AI models (like OpenAI’s GPT, Anthropic’s Claude and Google’s Gemini) requires significant investment. Right now, all investment can be considered R&D. But, Big Tech companies, like Google and Meta, and well-funded scaleups, like OpenAI and Anthropic, will at some point also need to figure out a sustainable business model.
The Information reported that some companies are using ChatGPT-4 and other higher end models to fine tune open source large language models (LLMs) for use in their businesses. This behavior questions the long-term value proposition of closed sourced models. As long as there are open source alternatives with strong communities willing to tinker and improve on such models, Big Tech companies will be pressured as they think about monetizing.
Ironically, while the largest AI companies are creating tremendous value building the technology, capturing value from those efforts look a bit more nebulous. Especially, when they are limited by their own headcounts in producing the necessary innovations needed to scale and refine their own LLMs, let alone monetize them.
At some point someone has to foot the bill, as they say in economics, there is no such thing as a free lunch.
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This post is provided for educational and informational purposes only. Nothing written in this post should be taken as financial advice or advice of any kind. The author(s) may own some of the NFTs, art and/or collectibles mentioned in this post. The content of this post are the opinions of the authors and not representative of other parties.
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