A tailored course, built for your situation
Mastering NIST CSF for Prompt Engineers in High-Velocity AI Environments
Build security-first AI systems with confidence, grounded in NIST CSF and designed for real-world deployment
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Most AI governance training is either too technical or too abstract, leaving prompt engineers without a clear path to influence, budget, or mandate.
The situation this course is for
Engineers build intelligent systems. But when security, compliance, or risk teams question their designs, they often lack the structured, standards-aligned language to defend or scale their work. This creates missed opportunities, not because the technology fails, but because the narrative doesn't stick.
Who this is for
Senior AI/ML engineers, prompt architects, and technical leads working in high-velocity environments who need to align cutting-edge AI systems with enterprise-grade security frameworks.
Who this is not for
Entry-level developers, non-technical compliance staff, or consultants looking for generic ISO/NIST overviews without implementation depth.
What you walk away with
- Architect AI prompt systems that align with NIST CSF Core Functions (Identify, Protect, Detect, Respond, Recover)
- Position your AI governance work as a premium engagement with documented risk alignment
- Lead internal reviews without escalation delays by speaking the language of security and compliance
- Access bigger-budget AI security projects by demonstrating NIST CSF implementation fluency
- Build repeatable, auditable prompt design frameworks used across teams
The 12 modules (with all 144 chapters)
Module 1. The NIST CSF Core in AI Context
Map Identify, Protect, Detect, Respond, and Recover to AI lifecycle stages. Understand how each function applies to prompt engineering and model behavior design.
12 chapters in this module
- NIST CSF overview for AI practitioners
- Identify: Asset management for AI systems
- Protect: Safeguarding prompt integrity
- Detect: Monitoring for drift and misuse
- Respond: Incident playbooks for AI failures
- Recover: Restoration strategies post-incident
- AI-specific control mapping
- Crosswalking CSF to internal AI policies
- Integrating CSF into design sprints
- CSF documentation patterns
- Security team alignment tactics
- Proving coverage without overengineering
Module 2. Prompt Systems and the Identify Function
Define AI assets, data flows, and roles clearly. Establish ownership models and inventory practices that satisfy auditors and engineers alike.
12 chapters in this module
- Defining AI system boundaries
- Data classification for prompts
- User roles in prompt workflows
- Third-party model dependencies
- Model behavior inventories
- Ownership models for generative AI
- Risk tolerance by use case
- AI asset tagging standards
- Version control integration
- Audit trail requirements
- Stakeholder alignment on scope
- Documenting system purpose
Module 3. Protect: Hardening Prompt Architectures
Apply access controls, input validation, and output filtering aligned with NIST CSF. Build defenses into prompt logic, not as bolt-ons.
12 chapters in this module
- Role-based prompt access
- Input sanitization patterns
- Output filtering pipelines
- Authentication for AI endpoints
- Encryption of prompt logs
- Model sandboxing techniques
- Adversarial prompt resistance
- Secure API gateway patterns
- Token-level access controls
- Jailbreak mitigation frameworks
- System boundary enforcement
- Zero-trust prompt design
Module 4. Detect: Monitoring for Prompt Drift
Set up real-time detection of prompt degradation, misuse, and model drift. Build alerts that trigger before incidents escalate.
12 chapters in this module
- Behavior baseline definition
- Drift detection thresholds
- Anomaly scoring for outputs
- User behavior monitoring
- Prompt reuse tracking
- Sentiment deviation alerts
- Context window overflow detection
- Rate-limiting abuse patterns
- Model confidence monitoring
- Feedback loop telemetry
- False positive reduction
- Incident triage workflows
Module 5. Respond: AI Incident Playbooks
Create structured responses to AI failures. Align engineering, legal, and compliance teams on escalation paths and containment.
12 chapters in this module
- Incident classification tiers
- Response team activation
- Communication protocols
- Prompt rollback procedures
- Legal exposure assessment
- User notification workflows
- Regulatory reporting triggers
- Post-mortem frameworks
- Containment automation
- Vendor coordination steps
- Public statement templates
- Lessons learned integration
Module 6. Recover: Restoring Trust and Function
Rebuild systems post-incident with improved controls. Document recovery for auditors and stakeholders.
12 chapters in this module
- Root cause analysis methods
- Prompt version rollback
- User trust restoration
- System revalidation steps
- Updated safeguards implementation
- Audit trail supplementation
- Stakeholder debrief structure
- Process improvement backlog
- Training updates post-incident
- Vendor SLA reviews
- Public update cadence
- Compliance evidence packaging
Module 7. Governance Integration
Embed NIST CSF into daily workflows. Link prompt reviews to broader security and compliance calendars.
12 chapters in this module
- Security review checklists
- Compliance alignment matrix
- Cross-team coordination rhythms
- Documentation standards
- Audit preparation cycles
- Risk committee reporting
- Policy update workflows
- Training refresh schedules
- Executive summaries drafting
- Vendor assessment integration
- Continuous improvement loops
- Regulatory horizon scanning
Module 8. Risk Assessment Alignment
Conduct and contribute to enterprise risk assessments using NIST CSF as the backbone. Speak the language of CISOs and compliance leads.
12 chapters in this module
- Risk register integration
- Threat modeling for AI
- Likelihood scoring methods
- Impact assessment frameworks
- Control effectiveness rating
- Risk treatment options
- Risk acceptance documentation
- Third-party risk linkage
- Emerging threat monitoring
- Scenario planning sessions
- Board-level risk summaries
- Regulatory change tracking
Module 9. Vendor Management in AI Supply Chains
Evaluate and manage third-party AI providers through a NIST CSF lens. Ensure compliance across the ecosystem.
12 chapters in this module
- Vendor due diligence checklist
- Model provenance tracking
- API security assessment
- Data handling review
- Subprocessor audits
- Compliance alignment verification
- Incident response coordination
- Contractual control mapping
- Performance benchmarking
- Exit strategy planning
- Security rating integration
- Continuous monitoring setup
Module 10. Compliance Evidence Generation
Produce audit-ready artifacts. Turn prompt system designs into demonstrable compliance with NIST CSF.
12 chapters in this module
- Evidence collection workflows
- Control mapping templates
- Audit trail curation
- Policy alignment statements
- Testing documentation
- Remediation tracking
- Executive attestation drafting
- Third-party validation paths
- Continuous monitoring proof
- Regulatory submission prep
- Internal audit support
- Evidence retention policies
Module 11. Scaling Frameworks Across Teams
Replicate success across organizations. Build shareable, maintainable prompt governance systems.
12 chapters in this module
- Framework documentation
- Cross-team onboarding
- Centralized control registry
- Local adaptation rules
- Feedback integration
- Version control strategy
- Training material development
- Metrics for adoption
- Center of excellence model
- Change management process
- Knowledge sharing rituals
- Governance maturity assessment
Module 12. Strategic Positioning for Impact
Position your work as mission-critical. Gain influence, budget, and recognition by speaking the language of enterprise resilience.
12 chapters in this module
- Business impact storytelling
- ROI calculation for governance
- Executive communication tactics
- Budget justification frameworks
- Project prioritization
- Cross-functional influence
- Thought leadership development
- Internal speaking opportunities
- Publication pathways
- Industry participation
- Standards body engagement
- Career trajectory planning
How this maps to your situation
- When launching a new AI product
- During internal security audits
- Before regulatory reviews
- After an AI incident or near-miss
Before vs. after
Before
AI systems designed without clear alignment to security frameworks , leading to rework, limited scope, and reactive compliance.
After
AI systems built with NIST CSF integration from day one , enabling faster approvals, larger budgets, and strategic recognition.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 4 hours per module , designed to fit around full-time engineering workloads.
If nothing changes
Without structured alignment to NIST CSF, even the most advanced AI systems face delays, budget cuts, or rejection during compliance reviews , not because they fail technically, but because they lack the governance narrative to scale.
How this compares to the alternatives
Unlike generic AI ethics courses or high-level NIST overviews, this course is built specifically for prompt engineers who must deliver secure, auditable, and strategically valuable AI systems , with concrete implementation tools, not just theory.
Frequently asked
Is this course only for security teams?
No. It's designed specifically for AI engineers, prompt architects, and technical leads who need to align their work with security and compliance expectations.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this cover other frameworks like ISO 42001?
Focus is on NIST CSF implementation, but key linkages to ISO 42001 and COBIT are included where relevant.
$199 one-time. Approximately 4 hours per module , designed to fit around full-time engineering workloads..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours