# 2025-08-08 promise-precision-evolution āš”TOLTOL: Map 5-model progression to 3D space (stateƗdepthƗaction) šŸ§²ZULZUL: Freedom evolves from levelā†’limitationā†’flexibilityā†’precision ā†’ $/time test: Deliver? 3D visualization Ɨ Model clarity = āœ“ Sell? Management Science Ɨ Rigorous progression = āœ“ **Learning**: External dimensions (3D plot) reveal internal evolution (decision freedom) ## Integration from Existing Knowledge: ### From [[āš”toltol/people_analysis/]] (External patterns) - Related person: [[āš”toltol/people_analysis/šŸ—ŗļøatom(PCOā¬†ļøā¬‡ļø)/charlie_fine.md]] - systematic optimizer - Quick pattern: Number models 1-5, not creative names ### From [[šŸ§²zulzul/ops4entrep/]] (Internal frameworks) - Theory connection: [[šŸ§²zulzul/ops4entrep/joker-framework.md]] - balance exploration/exploitation - Deep principle: Promise precision = f(level, limitation, flexibility) ### From [[3_šŸ…professionalize-processify/]] (Operations) - Academic backing: [[3_šŸ…/šŸ«€bayes/optimal-stopping.md]] - Method: [[3_šŸ…/āœ‹operations/šŸ¤™prior(promise)/]] ## 8 TODO Items (from brown numbers): 1. [āš”] Fix notation: Ļ† not "five", consistent throughout 2. [šŸ§²] Map GaNS baseline clearly as Model 1 foundation 3. [āš”] Draw 3D progression plot: (0,0,0)ā†’(1,0,0)ā†’(2,0,0)ā†’(2,1,0)ā†’(2,1,2) 4. [šŸ§²] Solve Model 3: Ļ†* = {1 if VSD=max, 0.5 if VSDā‰«} 5. [šŸ§²] Solve Model 4: Ī¼* convergence when Ļ„ā†’āˆž 6. [āš”] Add convex d(Ļ†) for Model 3b analysis 7. [šŸ§²] Prove Model 5: optimal Ļ„* = f(Ī¼, c, VSD) 8. [āš”] Create table: Decision variables by model (0ā†’Ļ†ā†’Ļ†ā†’Ī¼,Ļ†ā†’Ī¼,Ļ„) ## Model Evolution Summary: ### Model 1: Freedom-Level (ģžģœ -ģˆ˜ģ¤€) - State: (0,0,0) ā†’ No decision variable - P(success) exogenous ### Model 2: Freedom-Level Extended - State: (1,0,0) ā†’ Ļ† āˆˆ [0,1] - Promise level affects success ### Model 3: Finite/Limited (ģœ ķ•œ) - State: (2,0,0) ā†’ Branching: Sell vs Deliver - Trade-off: d(Ļ†) = delivery probability ### Model 4: Flexible (ģœ ģ—°) - State: (2,1,0) ā†’ Added depth dimension - Ī¼ = prior mean for promise ### Model 5: Discrete/Precision (ģ“ģ‚°/ģ •ė°€ė„) - State: (2,1,2) ā†’ Added action dimension - Ļ„ = sample size optimization - Cost: cĀ·ln(Ļ„)