The Convergence
Two trends are colliding: AI agents are becoming capable enough to make financial decisions, and onchain infrastructure is becoming robust enough to execute them. The result is a new category of financial system where software doesn't just assist human traders - it operates autonomously.
This isn't high-frequency trading with a neural network bolted on. It's fundamentally different architectures for how capital gets allocated, managed, and governed.
What's Actually Working
Automated yield optimization: Agents that monitor DeFi protocols, identify yield opportunities, and rebalance positions. This works because the decision space is well-defined and the feedback loop is fast.
Portfolio rebalancing: Given a target allocation and a set of constraints, agents can execute rebalancing trades more efficiently than manual processes. They handle the complexity of multi-protocol positions and gas optimization.
Risk monitoring: Agents that continuously evaluate portfolio risk and trigger alerts or protective actions. This is where the "never sleeps" advantage of AI is most valuable.
What's Hype
Fully autonomous fund management: The idea that an AI can completely replace a fund manager. We're nowhere near this. The agents are good at execution and monitoring, but strategic allocation still requires human judgment about macro conditions, protocol risks, and tail scenarios that don't appear in training data.
AI-generated alpha: The notion that AI can consistently find market inefficiencies that humans can't. In crypto markets, this is partially true for structural inefficiencies (cross-exchange arbitrage, gas optimization), but less true for fundamental value assessment.
What's Next
The interesting frontier isn't replacing human judgment - it's augmenting it. Systems where:
- Humans set strategy and constraints
- Agents handle execution, monitoring, and optimization
- Both humans and agents have clear authorities and boundaries
- The system is auditable end-to-end
This is harder to build than pure autonomy because the interface between human and agent decisions must be precise. But it's the architecture that actually works for managing real capital.
The Infrastructure Gap
The biggest bottleneck isn't AI capability - it's infrastructure. We need:
- Better execution layers: Current DEX infrastructure isn't designed for agent-driven trading patterns
- Risk primitives: Onchain risk management tools that agents can compose with
- Audit frameworks: Ways to verify that autonomous systems behaved correctly
- Governance models: Decision frameworks for when agents should defer to humans
These are infrastructure problems, and infrastructure is what I spend my time building. The teams that solve these problems will define how capital markets work for the next decade.
The Opportunity
The traditional finance industry manages $100+ trillion in assets with systems built on decades-old infrastructure. The onchain economy is a fraction of that, but growing fast.
The opportunity isn't to rebuild traditional finance onchain - it's to build financial systems that couldn't exist before. Systems that are transparent by default, composable by design, and autonomous where it makes sense.
That future needs better infrastructure. That's what I'm building.