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Tom Wilkie, CTO of Grafana, recently said, “Open source is the cheat code for AI.” Because LLMs are trained on open source software (OSS), agents can naturally discover, operate, and extend it. Simply put, agents prefer open source.
We've seen this play out across OCV's portfolio. Mermaid's OSS gravity made it the default diagramming framework for AI tools. Its syntax-saturated developer training data got embedded in GitHub, GitLab, and every major doc platform, and became the lingua franca for "diagram as code." It is now the fastest-growing code-based format in the world, and has driven Mermaid's exceptional commercial growth.
But the relationship runs both ways. AI is also a cheat code for OSS. AI enables people who are not professional developers to contribute to OSS for the first time. As of early 2025, there were around 35 million professional developers and another 10 million amateurs. Until now, well under 1% of the global population is responsible for all software being built and maintained. But that is rapidly changing. Over 36 million new developers joined GitHub between September 2024 and September 2025, the fastest absolute growth in the platform's history, and monthly active OSS contributors doubled from 84K to 175K, driven largely by AI adoption.
This trend reached a fever pitch in March 2026 with OpenClaw, which became the fastest-growing open source project in history. Its contributor guidelines explicitly welcome "AI/vibe-coded PRs," and the community reflects it: the vast majority of contributors are not classically trained developers. At NVIDIA's GTC, Jensen Huang called it "the operating system of agentic computers," comparing it to Linux, HTTP, and Kubernetes. Five years ago, the idea of non-developers contributing to foundational computing infrastructure would have been unthinkable.
The most durable OSS projects are what Jean Lafleur, co-founder of Airbyte, calls federation-style: where the user persona and the contributor persona are the same. That's why the most successful open source projects have historically been devtools and infrastructure; the feedback loop between using and building is tight, and the product compounds with every contribution. The alternative is stadium-style OSS, where a small core team builds while the community watches. This is why OSS has historically struggled at the application layer: even if users are smart and opinionated, the bar to contribute has been out of reach.
There's a growing consensus that building application-layer software is a dangerous proposition, as the cost of software development trends toward zero. "AI will kill vertical SaaS" is the new refrain. I'd sharpen that: AI + COSS will kill closed-source vertical SaaS.
AI + COSS will kill closed-source vertical SaaS
Consider Electronic Health Records (EHR), the OG vertical software. An EHR manages patient medical records and the administrative workflows of a medical practice, including scheduling, billing, and clinical documentation. Any EHR vendor will tell you no two practices are alike. They are deeply opinionated and require significant customization to support their particular workflows and requirements.
Epic owns ~40% of the U.S. hospital market and generates $5B+ in annual revenue, a substantial portion of which comes from implementation and customization services. Ask any practitioner how they feel about Epic, and the answer underscores the persistent gap between the people building the software and the people who live in it every day.
Epic will be around for a long time. But I believe it will gradually be displaced by an open core solution. Healthcare organizations won't vibe-code their EHRs, but they will build and customize workflows within a framework that understands the regulatory environment, the clinical context, and the data model. An open core EMR is a platform for AI-powered customization, workflow automation, and agent orchestration, grounded in the patient and provider data that it protects.
OSS has always been a knowledge-compounding machine: contributors improve the software, which attracts more users, which improves the software. When domain experts who were previously locked out can finally join that loop, the flywheel spins faster and reaches further. This dynamic is true across verticals, but especially powerful in healthcare, where knowledge-sharing is hardwired into the professional ethos.
This is the thesis behind our investment in OpenCoreEMR, which is commercializing the most popular open source EHR in the world—a project built by and for healthcare providers. For most of its history, contributing to OpenEMR required clearing a technical bar that most physicians couldn't reach. AI is rapidly changing that, and the project is growing exponentially.