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10_Wiki/Topics 대규모 정리: - 오류 캡처/미완성 stub 문서 227개 제거 - 교차폴더 중복 43클러스터 병합 (63파일 → redirect) - 링크명 정규화: 깨진 링크 수정·redirect 직결·개념 매핑 ~2,400건 - 카테고리 MOC 6개 신규 생성 - Graph 섹션 미해결 related-keyword 링크 10,058건 제거 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
197 lines
6.8 KiB
Markdown
197 lines
6.8 KiB
Markdown
---
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id: wiki-2026-0508-improvisation
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title: Improvisation
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [Improv, Adaptive Response, Spontaneous Decision-Making]
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duplicate_of: none
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source_trust_level: B
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confidence_score: 0.85
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verification_status: applied
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tags: [meta, decision-making, agentic, exploration]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: python
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framework: general
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---
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# Improvisation
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## 매 한 줄
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> **"매 plan 의 die 매 first contact, 매 improv 매 take over"**. Improvisation 매 real-time adaptive decision-making 매 incomplete information 매 unfolding situation. 2026 LLM agents 매 nontrivial improv capability 의 exhibit — 매 tool failure / unexpected output 의 recover 가능.
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## 매 핵심
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### 매 Components of improv
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- **Situation awareness**: 매 current state 의 fast read.
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- **Repertoire**: 매 prelearned moves / patterns.
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- **Risk gauge**: 매 reversible vs irreversible 의 distinguish.
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- **Commitment**: 매 hesitation 의 X — 매 decide 의 act.
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### 매 Plan vs Improv spectrum
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- **Pure plan**: scripted, deterministic, fragile.
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- **Plan + improv**: skeleton plan + adaptive details (best for most tasks).
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- **Pure improv**: jazz solo, emergency response.
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- 매 majority production system 매 plan-with-improv-edges.
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### 매 LLM agent improvisation
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- 매 tool returns unexpected error → reformulate vs fail.
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- 매 user gives ambiguous instruction → ask vs guess vs proceed.
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- 매 token budget 매 exhaust → compress vs truncate vs delegate.
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### 매 응용
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1. Incident response (production outage).
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2. Live coding session (pair programming).
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3. LLM agent error recovery.
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4. Customer support edge cases.
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## 💻 패턴
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### Pattern 1: Repertoire of moves
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```python
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from typing import Callable
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class ImprovKit:
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"""매 prelearned moves — 매 situation 의 match 의 dispatch."""
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def __init__(self):
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self.moves: dict[str, Callable] = {}
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def register(self, situation: str, move: Callable):
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self.moves[situation] = move
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def respond(self, context: dict):
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for situation, move in self.moves.items():
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if matches(situation, context):
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return move(context)
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return self.default_move(context)
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def default_move(self, context):
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return {"action": "ask_for_clarification"}
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```
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### Pattern 2: Reversibility check before commit
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```python
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def is_reversible(action: dict) -> bool:
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irreversible = {"delete_file", "send_email", "db_drop", "git_push_force"}
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return action["type"] not in irreversible
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def improv_decide(action: dict, confidence: float) -> str:
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if is_reversible(action):
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return "act" # 매 try 의 cheap
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if confidence > 0.95:
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return "act"
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return "pause_and_verify"
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```
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### Pattern 3: LLM error recovery loop
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```python
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def call_with_improv(client, prompt: str, max_retries: int = 3):
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history = [{"role": "user", "content": prompt}]
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for attempt in range(max_retries):
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try:
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return client.messages.create(
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model="claude-opus-4-7",
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max_tokens=2000,
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messages=history,
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)
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except RateLimitError:
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time.sleep(2 ** attempt)
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except OverloadedError:
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# 매 fallback 매 smaller model
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return client.messages.create(
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model="claude-haiku-4-7",
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max_tokens=2000,
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messages=history,
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)
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except Exception as e:
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history.append({
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"role": "user",
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"content": f"Previous attempt errored: {e}. Try a different approach.",
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})
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raise RuntimeError("매 improv 의 exhaust")
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```
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### Pattern 4: Yes-and (improv principle)
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```python
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def yes_and(user_input: str, context: dict) -> str:
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"""매 improv 'Yes, and' — accept premise, build on it."""
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return f"Acknowledged: {user_input}. Building on this: {extend(user_input, context)}."
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# 매 LLM system prompt 의 embed:
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SYSTEM = """매 user 매 partial information 의 give. 매 yes-and 의 follow:
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1. Accept what they said as fact (yes).
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2. Add useful structure (and).
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3. Avoid 'no, that's wrong' unless 매 hard contradiction."""
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```
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### Pattern 5: Bounded improv (safety rail)
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```python
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class BoundedImprov:
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def __init__(self, max_actions: int = 5, allowed_ops: set = None):
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self.max_actions = max_actions
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self.allowed_ops = allowed_ops or {"read", "search", "summarize"}
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self.actions_taken = 0
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def attempt(self, op: str, *args):
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if self.actions_taken >= self.max_actions:
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raise RuntimeError("매 budget exceed — escalate 의 human")
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if op not in self.allowed_ops:
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raise PermissionError(f"매 {op} 매 not in improv allowlist")
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self.actions_taken += 1
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return execute(op, *args)
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```
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### Pattern 6: Postmortem of improv
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```python
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def improv_log_entry(situation: str, move: str, outcome: str) -> dict:
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return {
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"ts": time.time(),
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"situation": situation,
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"move_chosen": move,
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"outcome": outcome,
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"would_repeat": outcome in ("success", "partial_success"),
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"alternatives_considered": [],
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}
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# 매 weekly review 매 add successful patterns 의 ImprovKit.
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```
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## 매 결정 기준
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| 상황 | Approach |
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| Reversible action, < 1min | Pure improv. |
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| Irreversible, high stakes | Plan first — improv 의 X. |
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| Ambiguous user request | Yes-and + clarifying question. |
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| LLM tool error | Bounded retry + reformulation. |
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| Production incident | Plan (runbook) + improv on edges. |
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**기본값**: 매 80/20 — 80% plan, 20% improv 매 unforeseen edges. 매 irreversible 매 strict plan only.
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## 🔗 Graph
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- 부모: [[Decision-Making]]
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- 응용: [[Pair-Programming]]
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- Adjacent: [[Risk_Management|Risk-Management]] · [[Bounded_Rationality|Bounded-Rationality]]
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## 🤖 LLM 활용
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**언제**: Tool error recovery, ambiguous user input handling, edge cases not covered by training data, multi-turn agent self-correction.
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**언제 X**: Compliance-critical workflow (deterministic pipeline only), safety-critical irreversible action.
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## ❌ 안티패턴
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- **Improv on irreversible action**: 매 prod DB drop 의 wing 의 X.
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- **No repertoire**: 매 from-scratch every situation — slow + inconsistent.
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- **No reversibility check**: 매 acted 매 then-realized too late.
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- **Ego improv**: refuse 의 ask for help — 매 stuck-but-improv-ing.
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## 🧪 검증 / 중복
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- Verified: Keith Johnstone "Impro" (1979), Karl Weick "Organizing for Reliability" (1987), OODA loop (Boyd).
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- 신뢰도 B (academic-soft + applied agentic literature).
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — full content with LLM agent improv patterns and reversibility framework |
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