George Vagenas
Agentic AI Governance Architect.
Since 1998. Building production systems. No compliance theatre.
28 years in the infrastructure layer. The structural questions that define enterprise agentic AI governance — authority, data boundaries, accountability — are the same questions that appear at every level of distributed systems work.
I have worked in the infrastructure layer since 1998: distributed platforms, real-time communications, cloud-native architecture at scale. The same structural questions kept appearing at every level: who has authority to act, what data may cross a boundary, and who is accountable when something goes wrong. Agent ecosystems are entering that same phase now. The organizations that define their governance architecture first are not doing compliance work. They are setting the terms.
Today I focus on governance architecture for agentic AI systems. Not model capability, not infrastructure scale. The structural layer above them: what agents may commit to, how data boundaries are enforced across agent chains and organizational lines, and where accountability sits when they act. I am the author of the Agentic Governance Framework (AGF), a vendor-neutral model for governing agentic systems in enterprise deployments, built publicly and validated against the authorization and accountability structures enterprise deployments encounter.
I work with enterprises and AI-native companies as an independent, vendor-neutral advisor. I have no interest in which governance platform you buy. My interest is in whether the architecture holds when your legal team, your enterprise customers, and your regulators start asking questions.
Vendor-neutral model for governing agentic AI systems in enterprise deployments. Defines three governance primitives: Delegated Authority, Data Boundaries, and Transaction Commitments. Built publicly and mapped against emerging protocols including Google A2A, Anthropic's model specification, and the MCP ecosystem.
Distributed platforms, real-time communications systems, cloud-native architecture. Enterprise infrastructure work across telecommunications, IoT, SaaS, and financial services. The same structural questions — authority, data flow, accountability — appeared at every level.
No financial interest in any governance platform, AI provider, or tooling vendor. Engagements are fixed-scope or retainer. Recommendations are shaped by your deployment context, not by a commercial relationship with any vendor.
Is your governance
architecture ready?
A single conversation is enough to identify the gaps — and whether there's a problem worth working on together.
Start the conversation