Letting AI trade a fund with zero human override is a disaster waiting to happen.

Signal generation follows a repeatable structure, but market conditions shift dramatically — flash crashes, earnings surprises, macro shocks — requiring qualitatively different responses each time. The structural similarity is superficial; the judgment required varies enormously.

Success criteria sound quantifiable (returns, Sharpe ratio) but are only measurable in hindsight, often over years. In real time, the agent has no reliable way to know whether a signal is correct until it's too late to reverse the trade.

Market data feeds, brokerage APIs, and execution infrastructure exist and are accessible. However, the agent lacks access to private deal flow, regulatory guidance, and the real-time qualitative context that experienced traders use to filter signals.

A bad signal executed at scale can cause immediate, large, and largely irreversible financial losses. With no human override, there is no circuit breaker — a runaway agent can blow through risk limits before anyone intervenes, as real-world algo trading disasters have demonstrated.

Distinguishing a genuine regime change from noise, navigating regulatory gray areas, and making ethical calls about risk exposure all require human judgment. Removing human oversight entirely eliminates the only safeguard against the agent's known failure modes.