[[09-27|25-09-27]] [[checklist]] 1. ์„œ๋ก ์— ์•ฝ์†์ˆ˜์ค€์— ๋Œ€ํ•œ ๋‚ด์šฉ์ด ์—†์–ด๋„ ๋˜๋Š”๊ฐ€? 2. how explicit i should be about my choice to focus on precision, but less on aspiration. 3. 1. todo๐Ÿท๏ธ๋ฆฌ์ŠคํŒ…ํ•˜์ž. ํ˜„์žฌ ๐Ÿท๏ธ1: - ์ œ๋ชฉ: ๊ธฐ์—ฌ์žฌ์ •๋ฆฌ Endogenizing P and V via entrepreneurial quality control, Heterogeneous learning and rational vision-keeping, Thresholds, policy rules, and operating levers - ์œ„์น˜: \subsection{Three Contributions}\label{sec:intro-contrib ๐Ÿท๏ธ2: - ์ œ๋ชฉ: A high initial ฯ„ (narrow, specific promises) locks in designs, partners, and processes before information is digested, destroying option value when I is material. Better Place chose such a high-ฯ„ path around battery swapping and struggled to update ฮผ as evidence arrived. Tesla kept ฯ„ low early (Roadsterโ†’Model Sโ†’Gigafactory), earning precision as V rose and I fell via capability building; when Vโ‰ฅ4I held near cโ‰ˆ1, scaling and tighter commitments were justified. - ์œ„์น˜: \subsection{Prescriptive: Grow with Earned Precision}\label{sec:dpp-presc} ๐Ÿท๏ธ3: ์‹๋ณ„ ๊ฐ€๋Šฅ์„ฑ/๊ฒ€์ฆ ๊ณ„ํšโ€ ๊ตฌ์ฒดํ™” ๊ธฐ์—ฌ 1 ๊ฒ€์ฆ ํžŒํŠธ: ์‹œ๋ฎฌ๋ ˆ์ด์…˜โ€“๋ณด์ •โ€“์ตœ์ ํ™” ํ™œ๋™(ํ’ˆ์งˆ๊ด€๋ฆฌ) ๊ฐ•๋„๊ฐ€ ๋†’์€ ํŒ€์ผ์ˆ˜๋ก P์˜ ์‚ฌํ›„์ƒ์Šน๋ฅ ์ด ํฌ๋‹ค๋Š” ํŒจ๋„ยท์‚ฌ๋ก€ ๊ธฐ๋ฐ˜ ํ…Œ์ŠคํŠธ ์ œ์‹œ. ๊ธฐ์—ฌ 2 ๊ฒ€์ฆ ํžŒํŠธ: I์˜ ๋Œ€๋ฆฌ๋ณ€์ˆ˜(์กฐ์ง ๋ณต์žก๋„, ์˜์‚ฌ๊ฒฐ์ • ๊ณ„์ธต, ๋™์‹œ ํ”„๋กœ์ ํŠธ ์ˆ˜)์™€ ์—…๋ฐ์ดํŠธ ๋นˆ๋„/ํญ์˜ ์Œ์˜ ์ƒ๊ด€, ๊ทธ๋ฆฌ๊ณ  ์„ฑ๊ณผ์˜ U์ž/์ž„๊ณ„ ๋ฐ˜์‘ ํƒ์ƒ‰. ๊ธฐ์—ฌ 3 ๊ฒ€์ฆ ํžŒํŠธ: ์‚ฌ๊ฑด์—ฐ๊ตฌ๋กœ ์Šค์ผ€์ผ ์„ ์–ธ ์‹œ์  ์ „ํ›„ V ๋Œ€ I์˜ ๋น„์œจ ๋ณ€ํ™” ์ถ”์ •, ๋˜๋Š” ์ฝ”ํ˜ธํŠธ๋ณ„ ์ดˆ๊ธฐ ฯ„(์•ฝ์†์˜ ๊ตฌ์ฒด์„ฑ ์ง€ํ‘œ)์™€ ํ”ผ๋ฒ—๋ฅ ยท์ƒ์กด๋ฅ ์˜ ๊ด€๊ณ„ ์ถ”์ •. - ์œ„์น˜: \subsection{Prescriptive: Grow with Earned Precision}\label{sec:dpp-presc} 2. ๋„ค๊ฐ€ ์ฒจ๋ถ€๋ฅผ ์—ฐ๊ตฌํ•˜๋Š” ๊ฒฝ์˜๋ถ„์•ผ ์ „๋ฌธ๊ฐ€๋ผ๋ฉด information integration cost ์„ ์–ด๋–ป๊ฒŒ ์„ค๋ช…ํ• ๋ž˜? ๋Œ€์ฒดํ•  ๋” ์ข‹์€ ์šฉ์–ด ์ƒ๊ฐ๋‚˜๋Š”๊ฑฐ ์žˆ์–ด? 3. ๐Ÿท๏ธ1์˜ ๊ธฐ์—ฌ์žฌ์ •๋ฆฌ ๊ด€๋ จ, ๋ฌธ์ œ ์ •์˜ ํ›„ ํ•ด๊ฒฐ์ฃผ์ฒด๋ณ„๋กœ ๊ทธ๋ฃนํ•‘ํ•˜๋Š” ๋ฐฉ์•ˆ์„ ์ƒ๊ฐํ•ด๋ดค๋Š”๋ฐ, ๋งŒ์•ฝ ๊ทธ๋ ‡๋‹ค๋ฉด ํ˜„์žฌ 3๊ฐ€์ง€๋กœ ์ •๋ฆฌํ•œ ๊ธฐ์—ฌ 1. ํ’ˆ์งˆ๊ด€๋ฆฌํ†ตํ•ด p, v๋‚ด์ƒํ™”, 2.I,V๊ด€๋ฆฌ, 3.growth ์ „๋žต๊ณผ ์šด์˜๋ฅผ ์–ด๋–ป๊ฒŒ ํšจ๊ณผ์ ์œผ๋กœ ์žฌ๊ตฌ์„ฑํ• ์ˆ˜ ์žˆ์„๊นŒ? ## ๐ŸŽฏ Problem-Solution Framework: High Precision Trap |Step|Substep|High Precision Promise Trap in Venture Capital System| |---|---|---| |**1. Problem**||ํ˜„์žฌ ๋ฒค์ฒ˜ ์ƒํƒœ๊ณ„๋Š” ์ฐฝ์—…๊ฐ€์˜ ์กฐ๊ธฐ ๊ณ ์ •๋ฐ€ ์•ฝ์†(high ฯ„)์„ ์กฐ์žฅํ•˜์—ฌ ํ•™์Šต ํ•จ์ •์„ ๋งŒ๋“ ๋‹ค| |**2. Root Cause**||| ||**2.1 Nature**|Computational irreducibility, aleatoric & Knightian uncertainty๊ฐ€ ์ฐฝ์—…/ํ˜์‹ ์˜ ๋ณธ์งˆโ€ข ๋ฏธ๋ž˜ ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅ์„ฑโ€ข ์ธ๊ณผ๊ด€๊ณ„์˜ ๋†’์€ ๋ฐ€๋„| ||**2.2 Individual**|์ฐฝ์—…๊ฐ€๋“ค์ด Optimal Ignorance Level(OIL)์„ ์ค€์ˆ˜ํ•˜์ง€ ์•Š์Œโ€ข "Fake it till you make it" ์••๋ฐ•โ€ข ํ•™์Šต ๋Šฅ๋ ฅ๊ณผ ์ž์› ๋™์›์˜ trade-off ๋ฌด์‹œ| ||**2.3 Institution**|์‹œ์Šคํ…œ์ด premature precision (unearned high ฯ„)๋ฅผ incentivizeโ€ข VC์˜ focal point ํ˜•์„ฑ ๋ฉ”์ปค๋‹ˆ์ฆ˜โ€ข "Mind reading the mind readers" ๋™ํ•™โ€ข Better Place ๊ฐ™์€ ์‹คํŒจ ๋ฐ˜๋ณต| |**3. Solution**||์ฐฝ์—…๊ฐ€ ์ฃผ์ฒด์  OIL ๊ธฐ๋ฐ˜ ์ •๋ฐ€๋„ ๊ด€๋ฆฌ| ||**3.1 Nature**|๋ถˆํ™•์‹ค์„ฑ์„ ์ธ์ •ํ•˜๊ณ  ๋‹จ๊ณ„์ ์œผ๋กœ ๊ด€๋ฆฌโ€ข ฯ„*=max{0,โˆš(V/4i)-1} ๊ณต์‹ ํ™œ์šฉโ€ข Nail(V<4i) vs Scale(Vโ‰ฅ4i) ๊ตฌ๋ถ„| ||**3.2 Individual**|Earned OIL ์›์น™ ๊ต์œกโ€ข ๋ณต์žก์„ฑ(c)๊ณผ ํ†ตํ•ฉ๋น„์šฉ(i) ๋จผ์ € ๊ฐ์†Œโ€ข ์ดํ›„ ์ ์ง„์  ฯ„ ์ฆ๊ฐ€| ||**3.3 Institution**|Investment ๊ตฌ์กฐ ๊ฐœ์„ โ€ข High identification cost ๋ฐฉ์ง€โ€ข Staged OIL (ฯ„* trajectory)์„ ํ‰๊ฐ€ํ•˜๋Š” ์ƒˆ๋กœ์šด ์ง€ํ‘œโ€ข ๋ชจํ˜ธํ•จ์˜ ์ „๋žต์  ๊ฐ€์น˜ ์ธ์ •| |**4. How solution addresses root cause**||OIL์€ ๋ถˆํ™•์‹ค์„ฑ ํ•˜์—์„œ ํ•™์Šต๊ณผ ์ž์›๋™์›์˜ ๊ท ํ˜•์„ ์ œ๊ณตํ•˜๋ฉฐ, "mind reading" ๊ฒŒ์ž„์—์„œ ๋ฒ—์–ด๋‚˜ ์‹ค์งˆ์  ๊ฐ€์น˜ ์ฐฝ์ถœ์— ์ง‘์ค‘ํ•˜๊ฒŒ ํ•จ| |**5. Production plan**||โ€ข OIL ๊ธฐ๋ฐ˜ ์ฐฝ์—… ๊ต์œก ํ”„๋กœ๊ทธ๋žจ ๊ฐœ๋ฐœโ€ข ฯ„ ์ธก์ • ๋„๊ตฌ ๋ฐ ๋Œ€์‹œ๋ณด๋“œ ๊ตฌ์ถ•โ€ข VC-์ฐฝ์—…๊ฐ€ ๊ฐ„ shared world model ํ”Œ๋žซํผโ€ข Staged OIL ํ‰๊ฐ€ ์ฒด๊ณ„ ๋„์ž…|