I design agent-based systems, cognitive architectures, and coordination infrastructure at the intersection of AI, Web3, governance, and protocol economics.
My current focus is on controllable AI systems: deterministic workflows, traceable execution, externalized memory, reproducible reasoning, and agent orchestration that can operate beyond isolated chat interfaces.
I come from a blockchain and decentralized governance background, with 10+ years across tokenomics, DAO systems, DeFi education, NFT security, and protocol design. Today, I treat Web3 less as a market category and more as an experimental domain for coordination, incentives, verification, and machine-mediated governance.
- Agent orchestration and execution control
- Cognitive architectures for AI systems
- Externalized memory, belief graphs, and structured reasoning
- Git-native workflows for traceable agent operations
- DAO governance, tokenomics, and incentive design
- Multi-agent systems and protocol sustainability
- AI-assisted research infrastructure
A cognitive architecture exploring belief graphs, self-models, persistent memory, and structured reasoning loops for agentic systems.
A git-native control plane for traceable, policy-driven agent workflows, designed around reproducibility, auditability, and execution governance.
A knowledge graph and semantic chunking system for structured reasoning, long-context research, and externalized cognition.
Co-founder of a tokenomics and governance lab focused on sustainable incentive systems, decentralized coordination, and protocol-level governance design.
Curator of practical AI education and workflows for solopreneurs, researchers, creators, and operators building with AI-native tools.
Co-founder of a security-focused project for NFT ownership protection, recovery logic, and risk reduction in digital asset systems.
Senior Lecturer at the Higher School of Economics, where I teach and research cryptocurrencies, DeFi, digital assets, and decentralized systems.
My work combines:
- Protocol economics
- Coordination theory
- Governance design
- Cognitive systems
- AI infrastructure
- Human-machine research workflows
Economics gives agents incentives.
Governance gives agents constraints.
Cognition gives agents adaptive models.
Infrastructure makes their actions reproducible, inspectable, and accountable.
I am interested in systems where AI agents are not just interfaces, but operational participants in research, governance, automation, and protocol execution.
- Tokenomics and DAO governance
- AI-native coordination systems
- Agent architectures and execution control
- DeFi and digital asset systems
- Multi-agent workflows
- Knowledge graphs and externalized reasoning
- AI × Web3 research infrastructure
I am currently building toward a stack where agents can reason, remember, coordinate, execute, and be audited.
Not just smarter chat.
Traceable cognition.
Verifiable execution.
Governable autonomy.