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Forgd.AI

5 cohorts  ·  0 feedback entries  ·  0 open actions
Programme record · Forgd.AI

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

Pooled NPS
too few to report
n=5 D2 · need ≥20
Cohorts attended
5
CohortCityDatesD1 nD2 nNPSProg avgGapP/Pa/D
C11San FranciscoMay 26-27, 202622+100+73+27
P 100%/Pa 0%/D 0%
C11San FranciscoMay 26-27, 202620
C20San FranciscoJuly 14–15, 202611+100+35+65
P 100%/Pa 0%/D 0%
C21San FranciscoJuly 16–17, 202622+0+24-24
P 50%/Pa 0%/D 50%
C22LondonJuly 20–21, 202610
Capability Profile
Persona mix
Architect 75%T.Lead 25%
AI proficiency
Applying 25%Independent 50%Frontier 25%
Seniority mix
Sr Prac 100%
Content depth
Too basic 17%About right 83%
Pace
Too slow 17%Well paced 83%
Relevance (mean)
4.6 / 5
D1 confidence (mean)
5.0 / 5
Confidence Δ (D1→D2)
n=5 · too few
Confidence growth by domain
Build Δ
n=2 · too few
Design Δ
n=2 · too few
Commercial Δ
n=2 · too few
Feedback log · Forgd.AI

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 · Forgd.AI

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

No open action items.