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Persistent Systems

3 cohorts  ·  0 feedback entries  ·  0 open actions
Programme record · Persistent Systems

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

Pooled NPS
too few to report
n=12 D2 · need ≥20
Cohorts attended
3
CohortCityDatesD1 nD2 nNPSProg avgGapP/Pa/D
C15San FranciscoJune 16-1796+83+55+28
P 83%/Pa 17%/D 0%
C20San FranciscoJuly 14–15, 202665+80+35+45
P 80%/Pa 20%/D 0%
C21San FranciscoJuly 16–17, 202611+100+24+76
P 100%/Pa 0%/D 0%
Capability Profile
Persona mix
Developer 56%Architect 38%T.Lead 6%
AI proficiency
Learning 6%Applying 69%Independent 12%Frontier 12%
Seniority mix
Sr Prac 88%Mgr 12%
Content depth
Too basic 19%About right 75%Too advanced 6%
Pace
Too slow 6%Well paced 88%Too fast 6%
Relevance (mean)
4.2 / 5
D1 confidence (mean)
4.5 / 5
Confidence Δ (D1→D2)
n=12 · too few
Confidence growth by domain
Build Δ
n=1 · too few
Design Δ
n=1 · too few
Commercial Δ
n=1 · too few
Persona × Seniority
PersonaIndividual ContributorSr PractitionerMgr / Sr MgrDirectorSVP / C-Level
Architect1
Developer7
Transformation Lead
Persona × AI Proficiency
PersonaLearningApplyingIndependentFrontier
Architect141
Developer711
Transformation Lead1
Satisfaction by Persona
Developer
n=6 · too few
Architect
n=4 · too few
Feedback log · Persistent Systems

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 · Persistent Systems

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

No open action items.