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Fractional AI / Ode

1 cohort  ·  0 feedback entries  ·  0 open actions
Programme record · Fractional AI / Ode

Quantitative data from post-programme surveys. NPS, participation, and benchmark against programme average across all cohorts attended.

Pooled NPS
too few to report
n=10 D2 · need ≥20
Cohorts attended
1
CohortCityDatesD1 nD2 nNPSProg avgGapP/Pa/D
C21San FranciscoJuly 16–17, 20261810-30+24-54
P 10%/Pa 50%/D 40%
Capability Profile
Persona mix
Developer 89%T.Lead 11%
AI proficiency
Learning 6%Applying 44%Independent 17%Frontier 33%
Seniority mix
Sr Prac 93%Mgr 7%
Content depth
Too basic 61%About right 33%Too advanced 6%
Pace
Too slow 44%Well paced 50%Too fast 6%
Relevance (mean)
3.8 / 5
D1 confidence (mean)
4.1 / 5
Confidence Δ (D1→D2)
n=10 · too few
Confidence growth by domain
Build Δ
n=10 · too few
Design Δ
n=10 · too few
Commercial Δ
n=10 · too few
Persona × Seniority
PersonaIndividual ContributorSr PractitionerMgr / Sr MgrDirectorSVP / C-Level
Developer13
Transformation Lead11
Persona × AI Proficiency
PersonaLearningApplyingIndependentFrontier
Developer1636
Transformation Lead2
Satisfaction by Persona
Developer
n=8 · too few
Strategic Insights
Advanced readiness: 33% at Frontier level — partner is ready for complex implementation engagements
Feedback log · Fractional AI / Ode

Anecdotal feedback from partner reps, stakeholders, and other sources. Each entry is sourced and benchmarked against survey data where available. Hearsay entries are flagged — weight accordingly.

No feedback logged yet. Run org_intake.py to add entries.
Action items · Fractional AI / Ode

Org-specific actions arising from survey data and feedback. Programme-wide actions are tracked separately in programme-actions.yaml.

No open action items.