/home/techb158/cosmic.abdallabala.com/docs
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00-design-study.md36780666editdlrm
01-uml-class-diagram.puml118690666editdlrm
02-use-case-diagram.puml37630666editdlrm
03-sequence-diagrams.puml97320666editdlrm
04-database-entity-model.mmd70510666editdlrm
05-database-schema.sql133720666editdlrm
06-diagram-preview.html50210666editdlrm
07-design-checklist.md32560666editdlrm
08-step-2-storage-layer.md53250666editdlrm
09-step-3-risk-crud-ui.md33800666editdlrm
10-step-4-mitigation-workflow.md39960666editdlrm
11-step-5-deployment-gate-workflow.md22920666editdlrm
12-step-6-multi-pm-integration.md37700666editdlrm
13-step-6-1-microsoft-planner-integration.md23350666editdlrm
14-step-7-reporting-export.md41580666editdlrm
15-step-7-1-oauth-live-connectors.md45450666editdlrm
16-step-8-user-roles-access-control.md32970666editdlrm
17-step-9-production-deployment-security.md42280666editdlrm
18-step-10-final-academic-submission.md31990666editdlrm
19-final-report-draft.md68140666editdlrm
20-instructor-submission-checklist.md36390666editdlrm
21-demo-script.md39480666editdlrm
22-traceability-matrix.md48470666editdlrm
23-testing-evidence.md29610666editdlrm
24-evaluation-rubric-mapping.md29100666editdlrm
25-final-deployment-runbook.md32140666editdlrm
26-known-limitations-and-future-work.md26320666editdlrm
27-final-qa-checklist.md28930666editdlrm
28-demo-rehearsal-script.md36180666editdlrm
29-submission-freeze-report.md27690666editdlrm
30-final-known-issues.md18760666editdlrm
dashboard-spec.md36910666editdlrm
Edit: /home/techb158/cosmic.abdallabala.com/docs/28-demo-rehearsal-script.md (3618B)
# Demo Rehearsal Script Date: 2026-07-04 Target duration: 10 to 15 minutes ## Demo objective Show that COSMIC AI-Risk Dashboard converts a conceptual AI-risk framework into a working software prototype with measurable risk scoring, mitigation tracking, governance gates, project-management integration, reporting, and auditability. ## Demo path ### 1. Introduce the problem, 1 minute Say: > AI projects are difficult to manage because risks emerge from data, models, people, governance, and deployment conditions. The dashboard addresses this by making AI project risk measurable and governable. Show: - Conference presentation slide 2 or infographic section "Why it matters". - Dashboard title and overview page. ### 2. Explain the foundation, 1 minute Say: > The conceptual foundation comes from the AI governance triangle and AI lifecycle governance. The software design is an operational extension that converts the framework into entities, services, API endpoints, and workflows. Show: - UML Class Diagram. - Use Case Diagram. - Database Entity Model. ### 3. Show the dashboard overview, 2 minutes Open: ```text http://localhost:8090 ``` Show: - Overall risk score. - Deployment gate status. - Open risks. - Mitigation completion. - Governance dimensions. Explain: > The dashboard uses normalized scores so that risk can be compared across projects and phases. ### 4. Demonstrate risk CRUD, 2 minutes Actions: 1. Open Risk Register. 2. Add a sample risk. 3. Set probability, impact, and detectability. 4. Save the risk. 5. Edit the risk. 6. Delete or keep the risk depending on demo needs. Say: > Each risk belongs to a lifecycle phase and governance dimension, which supports traceability from framework to implementation. ### 5. Demonstrate mitigation workflow, 2 minutes Actions: 1. Open Mitigations. 2. Add or edit a mitigation. 3. Set progress and effectiveness. 4. Add evidence reference. 5. Return to dashboard and show updated residual risk. Say: > Mitigation is not only a checklist. It changes residual risk and contributes to deployment readiness. ### 6. Demonstrate deployment gate, 2 minutes Actions: 1. Open Deployment Gate. 2. Run gate evaluation. 3. Review failed and passed criteria. 4. Add reviewer decision. 5. Show gate history and audit trail. Say: > The gate converts measurement into a governance decision. Deployment can be blocked, warned, or allowed based on measurable criteria. ### 7. Demonstrate PM integrations, 1 minute Actions: 1. Open Integrations. 2. Show Trello, Jira, Asana, and Microsoft Planner. 3. Show simulated sync. 4. Explain OAuth-ready live connector boundary. Say: > The system uses a shared adapter layer so the risk model is independent from a specific project-management tool. ### 8. Demonstrate reporting, 1 minute Actions: 1. Open Reports. 2. Open executive HTML report. 3. Export risk register CSV. 4. Mention full JSON evidence package. Say: > Reporting creates submission evidence and supports audit-ready governance review. ### 9. Close with validation, 1 minute Say: > The prototype includes tests for the risk engine, storage layer, workflows, integrations, OAuth boundary, reporting, access control, and production hardening. The final submission package freezes the system for evaluation. ## Backup demo path If live server startup fails, use: 1. Final conference PowerPoint. 2. Infographic image. 3. `SUBMISSION-README.md`. 4. `docs/22-traceability-matrix.md`. 5. `docs/23-testing-evidence.md`. ## Demo commands ```bash npm install npm test npm start ``` Open: ```text http://localhost:8090 ```