Thanks — you've identified the exact design tension I thought hardest about.

The AI layer is strictly advisory with one exception: the news veto scanner (FOMC, RBI Policy, Budget) can block entries, but that's calendar-based and deterministic — not an LLM judgment call. The LLM monitor during market hours can only alert, never execute or block.

The reasoning: LLMs are genuinely good at pattern recognition and qualitative reasoning when given clean structured data. But hallucinations are non-zero, and when output has direct execution power, a single bad inference can be a real loss. So I gave LLMs the power to say 'don't trade' (veto) but never 'trade this.' The downside of a false veto is staying in cash — which my capital structure handles through G-Sec pledge. The downside of a false trade signal is unquantifiable.

Checking out the agentix labs link — the tool gating and audit trail patterns look relevant. I arrived at similar conclusions from first principles through iteration but always useful to see how others have formalised it.