researching the foundations of autonomous AI and building what’s next

Hey everyone, I’m Nathan Walker, founder of Ravenhelm, based in Texas.

I’ve spent nearly a decade in enterprise AI architecture and technical leadership. Over the past couple of years, I’ve been pursuing an independent research program exploring a question that I believe will define the next generation of AI:

What does it actually take for an autonomous intelligence to operate independently, responsibly, and verifiably in the real world?

That question has taken me considerably further than LLMs and agent frameworks.

My research spans information physics, thermodynamics, formal verification, distributed systems, cryptographic accountability, agent identity, economic coordination, and the fundamental constraints of autonomous decision-making.

I’m not approaching these as purely theoretical problems. I’m building the infrastructure, developing the mathematical models, running simulations and adversarial experiments, and testing implementations on real hardware.

Some of that work includes:

• Agentropy: My published research, Agentropy: A Conservation Law as a Necessary Condition for Life-Like Dynamics, investigates how resource constraints and conservation laws influence emergent behavior in autonomous systems.
• Yggdrasil: A formal architecture for representing entities, relationships, authority, and verifiable execution.
• Git Ontic Trace (got): A Git-native execution provenance system designed to make autonomous actions attributable, auditable, and independently verifiable.

I’m preparing additional research for publication and exploring the commercialization of got as an initial product for developers and enterprises deploying autonomous AI.

My thesis is that the next generation of AI infrastructure won’t be defined solely by how intelligent agents become, but by whether we can establish what they’re authorized to do, what they actually did, and who is accountable for the outcome.

I’m here to connect with other technical founders, researchers, enterprise AI teams, and investors interested in foundational AI infrastructure, developer tooling, and the emerging autonomous systems economy.

I’d particularly welcome conversations with potential design partners and people who’ve taken deep technical research from prototype to commercial product.