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 Duration 14 hours

Course Outline

Ownership in FDE Leadership

  • Prioritizing outcomes over utilization
  • Managing the tension between delivery and product
  • Defining mandate, reporting lines, and sponsorship

Pod Design and Staffing

  • Pod structure, size, and autonomy
  • Skill mix across engineering, data, and domain expertise
  • Rotation and continuity between engagements

Hiring and Assessing FDEs

  • Identifying signals of deployment aptitude
  • Designing interviews and work samples
  • Onboarding into live engagements

Engagement Economics

  • Scoping, effort estimation, and margin
  • Comparing time and materials versus outcome-based pricing
  • Portfolio mix and concentration risk

The Internal FDE Playbook

  • Codifying stages, gates, and deliverables
  • Defining 'done' and quality standards
  • Maintaining and updating the playbook

Vendor FDE versus Internal Capability

  • Identifying where vendor teams add the most value
  • Contracting for knowledge transfer
  • Building capabilities that outlast the engagement

Reusable Accelerators and Blueprints

  • Reference architectures and starter repositories
  • Pre-approved security and integration patterns
  • Governance of shared assets

Adoption and Outcome Governance

  • Adoption metrics and executive reporting
  • Steering groups with genuine decision rights
  • Intervening in stalled engagements

Risk, Escalation, and Failure Patterns

  • Failure modes by engagement stage
  • Escalation paths and stop rules
  • Post-engagement reviews that drive practice improvement

Building the Practice

  • Career paths for forward deployed engineers
  • Standards, community, and knowledge sharing
  • A twelve-month capability roadmap

Requirements

  • Experience managing engineers or technical delivery teams
  • Involvement in customer-facing engagements
  • Exposure to commercial decisions such as scoping and pricing
  • No coding is required, though technical fluency is beneficial

Audience

  • Engineering managers of forward deployed teams
  • Delivery directors and practice leads
  • Heads of applied AI or solutions engineering
  • Transformation leaders building internal deployment capability

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