Open source is widely used but hard to monetize.

The Open Core model solves this by keeping core features free and selling enterprise features.

This article explores its origins, revenue model, and inherent tensions. This episode contains an AI-narrated version of the original blog post.

How can a multi-billion-dollar company be built on free software?

Red Hat turned Linux and GPL software into a business by selling trust and support, not code.

This article explores RHEL, subscriptions, CentOS, and IBM’s $34B acquisition—the most successful open source model. This episode contains an AI-narrated version of the original blog post.

Open source powers global software infrastructure, yet most projects fail to make money. Despite widespread use, many rely on individual effort and unpaid labor. This article explores why open source succeeds technically but struggles economically—and the structural reasons behind it. This episode contains an AI-narrated version of the original blog post.

How does freely available software make money? This series explores open source not as technology, but as a business model—why most projects fail to monetize, how Red Hat became a giant, and what the Elastic vs AWS conflict reveals about the economics of open source. This episode contains an AI-narrated version of the original blog post.

In the age of AI-generated code, we have gained more than a new tool.

Copyright, open-source licenses, and software supply chains are all being questioned.

This final piece explores the choices we must make between AI-created code and human-made rules. This episode contains an AI-narrated version of the original blog post.

AI code generation is changing how we build software, but also creating a new supply chain. Code from models trained on vast data is hard to trace in origin, licensing, and security. This article explores how AI compresses the open-source ecosystem into a new dependency layer. This episode contains an AI-narrated version of the original blog post.

The rise of AI-generated code is challenging the foundations of GPL and Copyleft. In an era where code can be produced infinitely, does Copyleft still matter? This article explores its origins and the new legal and technical questions AI introduces to its future. This episode contains an AI-narrated version of the original blog post.

Does AI-generated code have copyright? U.S. courts’ Human Authorship principle suggests it may not be legally protected. If so, who owns AI code, and what meaning do licenses still have? This episode contains an AI-narrated version of the original blog post.

Clean-room implementation is not just rewriting code—it is a structured process to legally isolate information from the original source. Born from IBM PC BIOS reverse engineering, it became a key standard in software copyright disputes and now raises new questions in the age of AI-generated code. This episode contains an AI-narrated version of the original blog post.

If AI learns from GPL code, is its output also GPL? This article explores the new legal questions arising from the clash between generative AI and Copyleft—covering learning vs. reproduction, AI code copyright, and the future of open source licensing. This episode contains an AI-narrated version of the original blog post.