Founder/operator of QDE-Systems.
I build deterministic execution infrastructure: systems where market data, risk boundaries, execution planning, audit records, and operator review stay visible instead of disappearing into a black box.
My current work is focused on QDE: source-code infrastructure for disciplined, auditable execution workflows. The commercial system is private and application-based. The public repositories show selected architecture ideas, not the full QDE product.
QDE-Systems is built around a simple engineering view:
- decisions should be traceable;
- risk should be checked before execution;
- runtime boundaries should fail closed;
- audit records should survive memory and opinion;
- AI agents should be used as disciplined reviewers, not unsupervised operators.
This is not a signal service, trading room, managed account product, or financial advice project.
| Repository | What it shows |
|---|---|
| qde-systems-infrastructure | Public architecture sample for risk-gated decisions, deterministic order planning, audit trails, and fail-closed execution boundaries. |
More public QDE-Systems material may be added over time, including the public operator-group page for selected licensed users.
- Deterministic execution flows
- Risk-gated runtime design
- Audit-safe system boundaries
- Broker/execution boundary design
- AI-agent review workflows
- Python backend architecture
- macOS operator tooling
The public samples do not include private strategy logic, broker integrations, IBKR execution code, credentials, private market-data configuration, model artifacts, customer data, or commercial QDE source code.
Commercial QDE access is separate and application-based.