Jonathan Reimer on Open Source, Startups, and AI

In this episode of Semaphore Uncut, we chat with Jonathan Reimer—founder of Crowd.dev, long-time open source startup operator, and now VP of Outbound Products at the Linux Foundation.

Jonathan shares his journey from building a data platform used by hundreds of developer-first companies, to joining the Linux Foundation through acquisition, and his latest focus: how open source business models, ecosystem dynamics, and rapidly advancing AI tooling are reshaping developer workflows—and the future of software delivery.

Disclaimer: This interview was recorded in May 2025.

From Open Source Startups to Crowd.dev

Jonathan has spent his entire career inside open source companies. Four years ago, he founded Crowd.dev, a platform built around a challenge nearly every OSS startup faces:

“Developers adopt your project bottom-up, but you often have no idea who is using it or which companies are evaluating it.”

Crowd.dev unified signals across the entire developer ecosystem:

• GitHub stars, issues, and contributors
• Twitter/X and Reddit engagement
• Newsletter and community activity
• CRM and product usage data

By consolidating these touchpoints, teams could finally understand which accounts were showing real intent, where community traction was forming, and when to trigger sales outreach.

This visibility is essential for dev-first PLG motions—especially when the first “user” is often a developer inside a Fortune 500 company.

Joining the Linux Foundation

The Linux Foundation quickly became Crowd.dev’s largest customer. With 1,000+ open source projects across 60+ sub-foundations, they needed deeper insight into:

• Who is engaging with each project
• Which companies are participating
• How fast each ecosystem is growing

Jonathan explains:

“Rolling this out across the Linux Foundation meant dealing with enormous data volumes and technical complexity. At some point it became clear the product had to live inside the Foundation.”

Crowd.dev was acquired a year ago, and Jonathan now leads outbound products across the Linux Foundation’s broad OSS landscape—from CNCF to new AI & Data initiatives.

The Three Types of Open Source Companies

After interviewing 400–500 founders, Jonathan sees open source startups falling into three categories:

1. Hobby Projects that Become Businesses

A developer builds something useful, it blows up, and only later becomes a company.

2. Strategic OSS Companies

Founders deliberately target markets to commoditize—an approach that accelerated around 2018–2019.

3. Ecosystem Builders

Teams build proprietary services on top of major OSS platforms (like Kubernetes) where the underlying project is maintained elsewhere (often by Big Tech).

Each category has success stories—and graveyards. Kubernetes, for example, spawned hundreds of startups, but many struggled as cloud providers “featurized” their offerings and commoditized entire product lines.

What Metrics Actually Matter?

GitHub stars? Helpful but misleading.

“Stars are intent signals—but they’re still a vanity metric.”

Instead, Jonathan recommends tracking Google Search Volume for your project’s name:

• Easy to measure
• Difficult to game
• Strongly correlated with real adoption

Once a project reaches ~100–200 monthly searches, the curve tends to map to genuine community growth.

When Does Open Source Make Business Sense?

Jonathan gives founders two critical “checkmarks”:

1. A Large Existing Market

Open source works best when competing with established, high-cost tools—not when creating categories from scratch.

2. Developers Must Be the Primary User

If your buyer is a marketer, salesperson, or operations team, open source loses many of its distribution advantages.

Developer-first companies, however, have a clear monetization path:

• Managed SaaS
• Enterprise support
• Consulting
• Multi-tenant hosting
• Compliance & risk management

“Open source gets you into the building. Developers will bring your product into Fortune 500 companies.”

The Open Source + AI Intersection

Jonathan is still forming his conclusions—but he sees both opportunity and risk.

On one side, AI may make it easier for teams to build internal tools that replace lightweight OSS solutions. On the other, LLMs are trained heavily on open source code, and AI dramatically expands the number of people who can build software:

“We used to have 20–25 million developers. I wouldn’t be surprised if we’re heading toward 100 million people writing software with AI.”

AI is already accelerating open source activity: simple bug fixes, issue triage, and doc updates are increasingly automated. Complex systems (like the Linux kernel) remain far beyond current capabilities—but not forever.

Proprietary Models vs Open Source Models

Jonathan’s prediction is bold:

Open source AI will win at the model layer.

Why?

• LLMs (e.g., DeepSeek, Llama) are rapidly commoditizing
• Switching between models is trivial
• Prices—and margins—are falling fast
• Real value moves to the application and data layers

“The model layer is being commoditized. The value will be in proprietary data, customer access, and applications.”

Companies like OpenAI and Anthropic will remain strong due to enterprise distribution, but widespread adoption will favor accessible OSS models.

And hosting?

Running models on-prem or even at home is already common—something unimaginable just a year ago.

Darko recalls a moment:

Reviewing their full codebase with an LLM used to cost $7–8k. Now it’s within reach—or can be run locally.

Follow Jonathan Reimer

🔗 Website: https://rymer.me
🐦 Twitter/X: @jonathimer
💼 LinkedIn: Jonathan Reimer