Finding the key to the AI agent control plane

"You can be forgiven for blotting that from your mind, but if you were anywhere near enterprise IT between 2000 and 2020, it's pretty much all we talked about. GNU General Public License, Apache License, MIT License, etc., etc. That was on the vendor side. On the enterprise side, emergency meetings were held because someone found the wrong copyright header buried in a dependency three levels deep. Entire toolchains and compliance teams sprang up to answer a simple question: What are we allowed to ship?"

"It felt critically important at the time. In a way, it was-sort of. We were defining the rules of engagement for how software could be shared, reused, and monetized. We were trying to turn a chaotic bazaar of code into something enterprises could trust and weave into their software supply chain. Surprise! We're doing it again, except the "code" is no longer a library you link against."

"These are good questions. They just happen to be the wrong questions. In the agentic AI era, the "license" is not a legal document. It is a technical configuration that defines what the software is allowed to do. Getting those permissions wrong has expensive, potentially destructive consequences. Getting them right...? Well, that turns out to be a very big deal."

Agentic systems act autonomously and require technical permission controls that determine allowed behaviors rather than traditional legal licenses. Vendor-specific toggles create inconsistent, risky configurations that can produce expensive or destructive outcomes when permissions are wrong. Past licensing debates focused on legal and compliance consequences for code reuse, but agents change the risk dynamics because actions, not just code distribution, cause harm. A standardized, interoperable framework for specifying agent behavior permissions, analogous to Creative Commons, would enable enterprises to understand, audit, compose, and safely integrate agent capabilities while reducing operational complexity and risk.

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