Open-Source Playbooks: From Linux to DeepSeek

DeepSeek reminds me of a "side project" from the 1990s called Linux. Both are open-source, and both were initially dismissed by giants like Microsoft. Yet they illustrate a timeless truth: the real value in technology accrues to those who build ecosystems, not just foundational tools. Today, Linux underpins 90% of the cloud, and companies like Red Hat—built on top of open-source code—turned it into a $34B business by selling support, not software. DeepSeek follows a similar playbook: it allows anyone to run, tweak, or embed AI locally. Concerned about data security, such as sensitive information being routed through foreign servers? Simply disconnect your internet—DeepSeek still functions. This demonstrates that the true market value lies not in the model itself, but in the vertical solutions and workflows built around it.

Wall Street's Pivot: From Hardware to Ecosystems

Wall Street's focus is shifting. Investors once chased GPU manufacturers like NVIDIA, but now they're more interested in inference costs and developer ecosystems. When Meta open-sourced Llama 2, its valuation rose—not because it "won" AI, but because it positioned itself as a platform for others to build on, similar to how Android captures value in mobile. Hugging Face, now valued at $4.5B, operates on the same principle: they monetize community, rather than hardware.

Historical Parallels: Value Climbs the Stack

This trend parallels the evolution of the cloud. IBM dominated mainframes in the 1980s; Dell ruled PCs in the 1990s. By the 2000s, value had migrated to platforms like AWS and apps like Salesforce. Today, companies like Snowflake and Databricks capitalize further by adding efficiency atop existing clouds. The lesson? Value always travels up the stack, shifting from raw materials to refined systems—just as steam engines led to railroads, factories, and global trade.

Enterprise Opportunity: Own Workflows, Not Algorithms

For enterprises, the big opportunity is in vertical solutions. Silicon Valley startups aren't building models from scratch; they're adapting open-source AI for specialized industries like healthcare compliance, supply chains, or customer service. The true winners won't be those who own the algorithms; they'll be the ones who own the workflows.

Conclusion: Agility Over Ownership

Rather than asking whether "R1" or "O1" is superior, consider how quickly your company can build AI-powered products that deliver operational value. If "R2" or "O2" launches tomorrow, can you pivot easily? This is not a new phenomenon: since the start of the industrial age, true competitive advantage stems not from owning technology itself, but from how efficiently you can build on top of it.