Work through a high-stakes sovereign-finance case, test what the evidence supports, prepare an internal negotiation-preparation brief, and see how your choices shape the outcome.
As the Debt Management Office in the fictional Republic of Kuvera, inspect the case file, request missing evidence, compare what institutions can authorize, and record what remains unresolved.
Your output is a recommendation that states what is known, unknown, and conditional. You are preparing for negotiation; you are not negotiating or making a sovereign commitment.
Decision support: separate facts, assumptions, and unresolved risks. Negotiation preparation: build a position grounded in evidence and authority.
Strategic intelligence: connect financial, contractual, and institutional signals. Reflection: reconstruct what changed the decision and why.
Facilitators can compare decisions with the evidence available at the time, examine requests and revisions, and lead a structured after-action review. Nothing is scored or ranked.
For institutions, the same record reveals where information gaps, authorization boundaries, or timing pressures affect readiness.
The Research Translation and Learning Framework (RTLF) converts carefully scoped findings into decision questions, constraints, and source-backed learning objectives. The deterministic Decision Engine applies versioned rules; it does not let the AI advisor decide.
Human-readable source titles, classifications, and page references remain connected to the evidence and debrief.
Scenario inputs, rules, and versions are frozen so a material outcome can be replayed and traced to the evidence, authority, and timing that produced it.
That architecture supports facilitator learning, institutional diagnosis, and responsible decision research without turning a workshop result into a claim about individual competence.