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The course is a highly niche and genuinely unique initiative potentially the first of its kind globally focused on the Digital Personal Data Protection (DPDP) Act.
The core idea is to vibe-code a live, end-to-end DPDP compliance and violation sandbox, where participants do not just learn the regulation conceptually, but experience it operationally.
Instead of static slides or theoretical walkthroughs, the session will feature:
- A fully simulated DPDP sandbox environment
- Live, vibe-coded demos covering realistic compliance and failure scenarios
- End-to-end flows across data collection, consent, processing, storage, breach, remediation, and regulatory response
- Scenario injection to test edge cases, gray zones, and enforcement consequences
Participants will be able to feel the implications of DPDP decisions by interacting with the sandbox—seeing how design choices, defaults, and failures propagate across systems, governance, and risk exposure.
This approach moves DPDP from “legal text” to lived engineering and governance reality, enabling deeper understanding for leaders, architects, security teams, and compliance professionals alike. We believe this format sets a new benchmark for how privacy regulations can be taught, tested, and internalized.
Day 1(8 Hours): Build the DPDP Operating System
1) Frame the Use Case and DPDP Scope (90 mins)
Objective: Stop treating DPDP like a legal memo; treat it like a system boundary.
Core concepts
- DPDP scope: digital personal data; non-digital only when digitised
- Roles: Data Principal / Data Fiduciary / Data Processor; shared accountability vs delegated processing
- Exclusions: truly anonymised data; what “anonymised” means operationally (vs pseudonymised)
Vibe-coding build: DPDP Scope & Role Classifier
- Input: processing scenario + data fields + who decides purpose/means
- Output: scope decision + role assignment + obligations checklist
Failure injection
- Dataset contains quasi-identifiers that re-identify individuals → tool must flag “not anonymised”
Artifacts
DPDP applicability decision log (audit-ready)
Role map + contract boundaries
2) Data Lifecycle × AI Lifecycle Mapping (90 mins)
Objective: Make DPDP “stick” to AI systems end-to-end.
Core concepts
- Data lifecycle: collect → store → use → share → retain → delete (expand into your org’s steps)
- AI lifecycle: data prep → training → eval → deployment → inference → monitoring/learning loop
- Where privacy breaks in AI: prompt logs, embeddings, vector DBs, telemetry, model feedback loops
Vibe-coding build: AI Data Lineage & DPDP Obligation Mapper
- Drag-drop pipeline stages → auto-assign obligations + risk flags
- Produces a “DPDP control map” per stage (who, what, evidence)
Failure injection
- RAG store contains HR PDFs with personal data → tool must flag purpose mismatch & retention risk
Artifacts
- AI-DPDP lifecycle map
- Processing inventory (RoPA-lite) aligned to lifecycle
3) Consent Engineering & “Consent UX” (120 mins)
Objective: Convert consent into product + architecture decisions.
Core concepts
- Consent quality: free, specific, informed, unambiguous; anti-bundling
- Withdrawal propagation (downstream systems)
- Consent records + auditability; Consent Managers (where applicable)
- Deemed/legitimate uses vs consent (where the program is designed to avoid over-consenting)
Vibe-coding build: Consent Orchestration Engine
- Consent capture UI (granular toggles)
- Consent receipt JSON + signed audit trail
- Consent withdrawal propagation simulator (marketing → analytics → AI training)
Failure injection
- Bundled marketing consent with account creation → must detect and redesign
Artifacts
- Consent taxonomy (by purpose)
- UX patterns: compliant consent flows + copy patterns
4) Data Principal Rights as Workflows (90 mins)
Objective: Rights are not buttons; they’re workflows with identity verification,logging, and SLA.
Core concepts
- Rights: access, correction, erasure, grievance redressal, nomination
- “Understandable responses” (no unreadable dumps)
- System constraints: backups, logs, legal retention, and operational feasibility
Vibe-coding build: Data Principal Rights Portal
- Request intake + identity verification flow
- Ticketing + SLA + escalation
- Human-readable response generator (policy-guarded)
Failure injection
- Returns raw database dump → participants must redesign to produce understandable responses
Artifacts
- Rights fulfilment SOP + SLA matrix
- Evidence logs for each request
DAY 2 (8 Hours) — Enforcement, SDF Controls, DPIA-as-Code, AI Governance
5) Breach Engineering: Harm-Based Notification (120 mins)
Objective: Train the “notify vs not notify” muscle using DPDP’s harm standard.
Core concepts
- Section 8(6) logic: notify DPB and Data Principals when breach is likely to cause harm
- Decisioning under uncertainty (what counts as “likely harm”)
- Cloud + vendor breaches; processor obligations + fiduciary accountability
Vibe-coding build: Breach Impact Simulator & Notification Generator
- Input: breach type, fields, scale, controls in place
- Output: harm likelihood score + notify/not notify + draft notices
Failure injection
- Partial breach with tokenized identifiers but leaked mapping table → harm becomes likely
Artifacts
- Breach decision matrix
- Notification templates (DPB + Data Principal)
- Incident evidence binder structure
6) DPB Enforcement, Penalties, Appeals (90 mins)
Objective: Remove myths; build a penalty-aware operating posture.
Core concepts
- Administrative monetary penalties; aggravating/mitigating factors
- Repeat violations, cooperation, remediation speed
- Appeals window and governance response playbook
Vibe-coding build: Penalty Exposure & Mitigation Dashboard
- Violation type + severity + recurrence + mitigations → exposure band
- Executive view: “what to fix first”
Failure injection
- Same violation repeats across two business units → must detect systemic control failure
Artifacts
- Penalty exposure register
- Board response strategy playbook
7) Significant Data Fiduciary Controls + DPIA-as-Code (90 mins)
Objective: Make DPIA living, repeatable, and evidence-producing.
Core concepts
- What triggers DPIA: high-risk processing (esp. AI, profiling, large scale)
- DPO responsibilities (where applicable)
- Auditability: risk acceptance, residual risk, compensating controls
Vibe-coding build: DPIA-as-Code Generator
- Questionnaire → scoring → controls mapping → auto-report
- Produces evidence pack: risks, mitigations, approvals, review cadence
Failure injection
- AI feature adds “learning from user chats” post-launch → DPIA needs update and approval workflow
Artifacts
- DPIA template + scoring rubric
- Risk acceptance log + approval trail
8) Capstone: Unified DPDP + AI Compliance Portal (120 mins)
Objective: Integrate everything into a single leadership-grade system.
Capstone build
Teams implement:
- AI system onboarding (purpose, data, vendors)
- Consent engine + withdrawal propagation
- Rights portal + SLA tracker
- Breach simulator + notification workflow
- DPIA-as-code + approvals
- Evidence binder generation (exportable)
Role-based views (must-have)
- Executive: risk heatmap, top obligations, penalty exposure, roadmap
- DPO/Privacy: DPIAs, rights queue, policies, evidence
- Security: breach readiness, safeguards checklist, telemetry controls
- Product: consent UX, feature gating, data minimisation
- Auditor/Regulator: traceability, logs, approvals, artifacts
Elite extensions (choose 2)
- Shadow AI discovery workflow (rogue tools + unapproved datasets)
- RAG corpus privacy controls (PII detection + retention enforcement)
- Prompt-log minimisation + redaction + purpose binding
- Synthetic data governance (re-identification tests + approval gates)
Final outputs
- Working portal demo
- Leadership pitch (3 slides)
- Compliance architecture blueprint
- Evidence binder pack
Speaker Profile: Rammohan Thirupasur is a highly accomplished Technology Leader with over 28 years of IT experience, including 17+ years in leadership roles spanning Hybrid Cloud, AI Security and Managed Services across the EMEA and APAC regions. As a former Associate Director at IBM/Kyndryl, he led global teams of 100+ professionals, earning recognition as a top-rated people manager for his ability to inspire, mentor and drive results.
A renowned technology trainer and coach, Rammohan specializes in Gen AI, ISO 42001, DORA, AI GRC, EU AI Act, ICS/OT Security and Hybrid Multi-Cloud, simplifying complex concepts to empower businesses and professionals in adopting cutting-edge innovations. As a keynote speaker and technology blogger, he leverages Design Thinking and Case-Study methodologies to deliver engaging, hands-on training. With expertise in large-scale ERP implementations for Fortune 1000clients, he is a trusted advisor on Gen AI, AI Security and IT Governance (ISO 42001& 27001) makes him a sought-after expert for organizations navigating digital transformation.
Rammohan is a trusted technology advisor for startups worldwide, helping emerging Gen AI companies shape their strategies and scale innovation. As a member of multiple advisory boards, he plays a pivotal role in driving AI adoption and security best practices across industries
