A focused course, tailored for you
Staff ML Engineer Customer Conversation Playbook
A field-conversation playbook for Staff ML Engineers shipping Now Assist and peer features in 2026: model-card framework, EU AI Act high-risk classification, customer-side AI governance integration, customer-side audit-trail integration.
Staff ML Engineers shipping features find the customer ML lead asking for the model card. The internal Slack thread is not it. The course delivers the field-conversation playbook.
$199 one-time
Tailored to your situation. Access within 24 hours. 30-day money-back.
Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.
Why this course
Staff ML Engineers shipping AI features at platform vendors (ServiceNow Now Assist, Salesforce Einstein, Microsoft Copilot for Business, Workday AI, SAP Joule, IBM watsonx) face customer ML engineering leads who ask one question: show me your model card for the feature you are shipping next quarter. The default response pulls up an internal Slack thread. The customer ML lead closes the laptop. The feature adoption stalls.
The course delivers the field-conversation playbook. The model-card framework. The EU AI Act high-risk classification framework. The customer-side AI governance integration framework. The customer-side audit-trail integration. The customer-side compliance integration. The customer-side observability integration. The customer-side identity-federation integration. The customer-side workforce integration. The customer engagement structure. Twelve modules with deliverables. Plus a hand-built playbook for your specific feature mix.
The 12 modules
Module 1. The 2026 platform-vendor AI feature landscape
Walkthrough of the 2026 platform-vendor AI feature landscape. The ServiceNow Now Assist landscape. The Salesforce Einstein landscape. The Microsoft Copilot for Business landscape. The Workday AI landscape. The SAP Joule landscape. The IBM watsonx landscape. The customer-side AI governance committee profile. The strategic decisions a Staff ML Engineer faces. Plus the integration with the customer's existing programme cadence and the worked example for the customer's typical operating model.
Module 2. Model-card framework
Build the model-card framework. The model-card structure. The model-card content framework. The model-card review framework. The model-card publication framework. The customer-side model-card-requirement framework. The integration with the customer-side model risk management framework. Plus the worked example for the customer's first three model cards.
Module 3. EU AI Act high-risk classification framework
Build the EU AI Act high-risk classification framework. The Annex III high-risk use-case framework. The use-case-classification framework. The high-risk-obligation framework. The customer-side conformity-assessment framework. The customer-side post-market-monitoring framework. The integration with the customer-side AI governance framework. Plus the worked example for a customer's first three high-risk AI use cases.
Module 4. Customer-side AI governance integration framework
Build the customer-side AI governance integration framework. The customer-side AI governance committee integration. The customer-side AI risk-classification framework integration. The customer-side AI transparency framework integration. The customer-side AI human-oversight framework integration. The customer-side AI bias-monitoring framework integration. Plus the worked example for the customer's first three high-risk AI use cases.
Module 5. Customer-side audit-trail integration
Build the customer-side audit-trail integration. The decision-log structure. The override-log structure. The model-version-log structure. The integration with the customer's existing audit-trail infrastructure. The integration with the customer's existing SIEM. The integration with the customer's existing GRC platform. Plus the worked example for the customer's typical audit-evidence response.
Module 6. Customer-side compliance integration
Build the customer-side compliance integration. The customer-side SOC 2 framework integration. The customer-side ISO 27001 framework integration. The customer-side ISO/IEC 42001 AIMS integration. The customer-side NIST AI RMF integration. The customer-side EU AI Act integration. Plus the worked example for the customer's typical multi-framework compliance landscape.
Module 7. Customer-side observability integration
Build the customer-side observability integration. The customer's existing Datadog integration. The Splunk integration. The Microsoft Sentinel integration. The Prometheus integration. The Grafana integration. The OpenTelemetry integration. Plus the worked example for the customer's typical observability stack and the metric-and-log routing framework.
Module 8. Customer-side identity-federation integration
Build the customer-side identity-federation integration. The customer's existing IAM platform integration (Okta, Entra ID, Ping Identity). The SCIM provisioning pattern. The role-based-access pattern. The session-policy pattern. The customer-side audit-trail integration. Plus the worked example for the customer's typical user population and the integration framework.
Module 9. Customer-side workforce integration
Build the customer-side workforce integration. The customer-side ML-engineer role evolution. The customer-side data-scientist role evolution. The customer-side AI governance committee member role evolution. The customer-side training framework. The customer-side competency-assessment framework. Plus the worked example for the customer's first 12 months of workforce integration.
Module 10. Customer engagement structure
Build the customer engagement structure. The discovery phase. The reference-architecture phase. The pilot-workload phase. The full-rollout phase. The sustainment phase. The renewal conversation. The customer-side programme-governance committee integration. Plus the worked example for a 12-month customer engagement and the pricing framework.
Module 11. Customer adoption pattern
Build the customer adoption pattern. The customer-success-led adoption pattern. The customer-implementation-services-led adoption pattern. The partner-led adoption pattern. The customer-self-service adoption pattern. The pattern selection for the customer's organisational maturity. Plus the worked example for a large customer adoption over 6 months.
Module 12. Your 10-week build plan
Week by week. Weeks 1-2: landscape and model-card framework. Weeks 3-4: EU AI Act high-risk classification framework and customer-side AI governance integration framework. Weeks 5-6: customer-side audit-trail integration and customer-side compliance integration. Weeks 7-8: observability, identity-federation, workforce integration. Weeks 9-10: customer engagement structure, customer adoption pattern. Deliverable: a structured field playbook for the next customer ML lead conversation.
How this addresses your situation
Specific modules that map to what you said you are dealing with.
Customer ML lead asks for model card → Module 2.
Customer compliance team asks about EU AI Act → Module 3.
Customer AI governance committee → Module 4.
Customer audit trail → Module 5.
Customer compliance framework → Module 6.
Customer observability → Module 7.
Customer adoption → Module 11.
Who it is for
For Staff ML Engineers shipping AI features at platform vendors, principal ML engineers at peer platform vendors, senior ML engineers at customer organisations.
Who this is NOT for. Pure non-ML-engineering practitioners. Practitioners with no customer-facing AI feature context.
How it arrives
Text-based course via LMS, plus downloadable templates and worked examples and the hand-built playbook.
Time investment. Roughly 18 hours of reading and 60 to 120 hours of build effort across the 10-week plan.
Why $199 is the right number
External Staff ML Engineer enablement programmes charge from 100,000 to 500,000 USD. 199 USD buys the focused playbook and the implementation document for your specific feature mix.
FAQ
Does this cover Now Assist for ITSM specifically?
Module 1 covers Now Assist for ITSM as a primary anchor.
What about Now Assist for HR Service Delivery?
Module 1 covers Now Assist for HRSD as a primary anchor.
Does this cover Now Assist for Customer Service Management?
Module 1 covers Now Assist for CSM as a primary anchor.
What is in the implementation playbook for me specifically?
Field playbook tuned to your specific feature mix.
30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.
