Open-Source is Eating Software
Three new business models for open-source products.
01 | An overlooked, $8.8 trillion industry
Last week, a Harvard Business School paper was circulating, reigniting conversation about the commercial potential of open-source software (OSS).
The authors of the paper estimate that OSS has created roughly $8.8 trillion in economic value.
That figure came from scanning the codebases of tens of thousands of companies, identifying OSS components, and estimating what it would cost to rebuild them from scratch.
The research also highlights just how prevalent open-source is:
“[OSS] appears in 96% of codebases, and some commercial software consists of up to 99.9% freely available OSS.”
OSS is clearly integral to the digital economy. But that hasn’t always translated into commercial success.
There have been a few venture-backed winners. MongoDB hit a $1.9B market cap six months post-IPO. Red Hat sold to IBM for $34B (bigger than Wiz!). Still, the vast majority of OSS projects have struggled to grow into venture-scale companies.
I first explored the HBS paper and questions around monetization a couple months ago. But with the cost of writing code collapsing, and software economics shifting fast, it feels like a good time to take a closer look.
02 | The old OSS playbook
Over the past two decades, 95%+ of all venture dollars went to non-OSS software products built on proprietary, closed architecture. These products create value by owning the code, controlling the data, and locking in users through polished UX and tightly managed integrations.
Open-source projects, on the other hand, give code away for free. These projects typically monetize by charging for extra features — hosting, customer support, and other premium services like enterprise controls and advanced security.
MongoDB is a classic example. Mongo’s core NoSQL database is open-source, free for anyone to deploy and host in their own environment. But customers can upgrade and pay for Atlas, MongoDB’s fully managed cloud offering. Customers will pay for convenience and support — in Q4-2024, Atlas generated a $1.2 billion run-rate, up 34% from the year prior.
This model works – but only under certain conditions.
To succeed, OSS companies have to convert usage into reliance, and reliance into revenue. That usually means becoming essential infrastructure (e.g., databases that become the system of record), a network with very high switching costs, or a central hub that integrates multiple third-party systems.
However, most OSS projects are lightweight and easy to swap out. If your core asset is free and replaceable, building up that defensibility is tough.
But today, that’s changing.
03 | Three new OSS business models
New technical shifts — like AI automation, modular backends, and blockchain systems — are unlocking new ways for OSS to capture value.
There are three commercial paths I see for OSS over the next several years.
A. Open-core (the familiar model, now upgraded)
The classic model – offer the core product for free, charge for premium features – will get supercharged by AI.
Paid tiers will move from static add-ons, like dashboards and hosting, to more intelligent (and valuable) automation – self-healing systems, agents that manage entire workflows, and adaptive interfaces.
For example:
A free documentation generator can offer a paid AI tier that answers developer questions in plain English, citing relevant sections from your own docs and enriching answers with best practices distilled across its entire user base.
An open-source security scanner offers a paid tier where AI automatically flags risky code and makes the fix.
OSS still benefits from community validation and wide distribution. But with AI, the commercial scope of OSS is expanding. In the future, I expect more projects will scale from useful tools to venture-backed platforms.
B. Network management as the product
In the coming years, AI agents will become the primary users of software.
As they take on more tasks — like sending messages, retrieving data, or executing transactions — they’ll need infrastructure to decide which third-party APIs to call and how to route and negotiate those requests.
Take travel booking, for example. An AI agent might query airline APIs, compare prices, email an itinerary, and complete a transaction — choosing different providers based on real-time prices, availability, and user preferences.
This creates a new kind of software marketplace, one where agents navigate networks of interoperable, third-party services.
Open-source can define the standards for these networks — the open protocols, SDKs, and connectors that make them accessible and interoperable across service providers and agents. This open access layer enables broad participation and rapid ecosystem growth.
But the commercial opportunity lies in managing the network — shaping how agents select services, requests are routed, and providers compete to serve agent demand.
Startups building this layer can monetize through:
Paid tools that help service providers manage agent traffic, configure access rules, or target specific types of agent requests.
Fees on transactions between agents and third-party services
Priority access, where providers pay for better placement based on performance guarantees.
In some cases, decentralized infrastructure, like blockchains with smart contracts, may be especially well-suited to this model – enabling more automated network management, pricing, access, and security without the overhead of a central intermediary. These systems offer transparent, programmable, and permissionless access, a natural fit for more automated, agent-driven workflows.
This is a big shift. It moves the OSS business model from selling features to managing networks.
Here, OSS lays the groundwork, creating open access to the network. The business is in orchestrating its flow.
C. Open-source as a data engine
In this model, open-source software becomes a way to collect valuable data.
It works like this: A startup releases a small, free tool (like a code library or SDK) that solves a specific problem for developers. Because it’s useful and free, lots of developers add it to their projects.
Every time a developer deploys the tool, it quietly collects useful information — like how a system is running, or how users are engaging. Over time and across multiple applications, this adds up to a unique, dynamic dataset that customers pay to access.
Langfuse is a good example. Their open SDK that captures LLM performance data, which flows into an observability platform users can pay for.
This model is especially well-suited for the current market. Demand for this type of data is growing, because AI systems need constant feedback to improve. And advances in encryption now make it safe to extract and transmit this data from private environments.
In this paradigm, OSS is the sensor that gets embedded. The business model is in the signal it sends back.
04 | Open-source is eating software
At Timespan, we believe open systems are the next paradigm of software, and we specialize in applications built on these new, open protocols.
Today, coding automation is driving the marginal cost of software development to zero – lowering barriers to OSS adoption and unlocking new distribution and business models where open-source has a natural edge.
Two of the fastest-growing startups today, Cursor and Lovable, started as open-source.
Cursor launched on Github in 2023 as a fork of VS Code, using its open-source base to fast-track adoption and layer in AI workflows – scaling to $100M ARR in under a year. Lovable began as “GPT Engineer” in mid-2023, an open-source app generator that built early traction and evolved into a full-stack paid platform with hundreds of thousands of active users.
I expect to see more open-source projects evolve into venture-scale businesses, powered by intelligent services, agent-based execution networks, and application-native pipelines that generate unique data.
In all three cases, OSS provides a structural advantage. It reduces unnecessary costs, increases transparency, and drives adoption through large, engaged developer communities.
Open-source is eating proprietary software.
Soon, $8.8 trillion will look small.