About
Builder, researcher, and founder working where intelligence meets markets.
Mfoniso Jackson builds AI systems that reason about capital, incentives, behavior, and coordination. His work connects reinforcement learning, financial engineering, autonomous agents, Web3 coordination, and the safety questions that emerge when machines learn rituals from noisy worlds.
Operating thesis
Intelligence needs structure.
The site is organized around a simple belief: powerful systems become useful when they are constrained by good representations, explicit incentives, and honest feedback from reality.
In markets, that means agents must understand risk, regime change, liquidity, and the temptation to confuse backtest artifacts with durable signal.
In safety, it means studying the strange persistence of learned proxies and non-causal behaviors before they become invisible architecture.
In product, it means turning research into tools that founders, operators, investors, and communities can actually use under pressure.
Contact
Building an AI system where market logic, agent behavior, and coordination matter?
Bring the hard shape of the problem: ambiguous incentives, moving data, uncertain rewards, brittle workflows, or research that needs to become a product.