Vision Foresight Futures Wheel Basic V1

Sub-skill: Basic Futures Wheel V1

출처: Glenn J.C. (2009 [1971]). Futures Wheel. In J.C. Glenn & T.J. Gordon (Eds.), Futures Research Methodology V3.0, Chapter 06, §III.A + Figures 1·2·3 Wagschal rule 출처: Wagschal P. (cited in Glenn 2009 §III.A, "rule of unanimity") 상위 마스터: vision-foresight-futures-wheel 호출 권한: 마스터 orchestration 전용. 사용자 직접 호출 금지(disable-model-invocation: true).

1. PDF 원전 정의

Glenn(2009) §III.A 핵심 verbatim:

"A group decides to brainstorm about a trend, idea, future event, or value. The subject is written in the middle of a piece of paper, a flip chart, blackboard, on a computer with video projector, or in software."

"The leader of the brainstorming session draws an oval around the item and asks the group to say what necessarily goes with this item. As impacts or consequences are offered by the group, the leader draws short wheel-like spokes out from the central oval and writes these impacts at the end of each spoke."

"Ovals are drawn around each of the primary impacts. A ring can be drawn connecting the primary impacts. Next, the leader asks the group to forget about the original item in the middle of the Futures Wheel and to give the most likely impacts for each of the primary impacts of the first ring of primary consequences. As these secondary impacts are offered by the group, the leader draws two or three short spokes out from each of the ovals around the primary impacts to form a second ring..."

2. 결정론 환원 원칙

아래 연산은 반드시 wheel_engine.py를 호출해 수행한다. LLM이 재계산하면 할루시네이션 위험이 차단되지 않는다.

CLI 호출:

echo '<JSON>' | python3 wheel_engine.py <command>

3. CoER — Chain of Evidence Reasoning 정의

모든 impact는 CoER 3-step을 의무 포함:

검증 (wheel_engine.py check_coer):

echo '{"coer_entries":[{"id":"P1","label":"...","R1_text":"...","R1_citation":"...","R2_text":"...","H_text":"..."}]}' | python3 wheel_engine.py check_coer

출처 없는 R-1 = CoER FAIL → Gate BLOCK.

4. AI Agent 4인 구성

5. 9 Phase 처리 흐름

Phase 1 — Center Definition (T+0)

입력 검증 (wheel_engine.py validate):

echo '{"center_issue":{...},"depth_target":6,...}' | python3 wheel_engine.py validate

Leader Agent가 중앙 이슈를 한 oval로 명시. 4요소 필수:

{
  what: "이슈 정의",
  when: "시점 (e.g., 2028~2030)",
  where: "지리적 범위",
  who: "1차 주체"
}

        ┌─────────────────┐
        │  {중앙 trend/   │
        │   event/idea}   │
        └─────────────────┘

PDF Example: "Increasingly small and less expensive computer communication devices" (Figure 2)

Phase 2 — Primary Ring (직접 영향, T+1~5y)

⛩️ Gate_P1_Pre 자동 호출 (deep-reasoning-engine, blocking):

echo '{"ring_num":1,"parent_count":1}' | python3 wheel_engine.py websearch_count
# → min_websearch: 3

• WebSearch ≥3 강제 (wheel_engine.py 결정)
• evidence 수집 + inline citation 강제
• CoER 검증 (wheel_engine.py check_coer)
• 통과 못하면 BLOCK (재시도 최대 3회)

통과 후 Leader: "What necessarily goes with this item?"

Brainstorm Panel이 5~10개 primary impact 제시. 각각:

• oval로 감싸기 / 중앙과 single spoke로 연결
• CoER 3-step 의무 (R-1[citation] → R-2 → H)
• 부호 + / - 명시 (Phase 6 역전 계산 기준)

PDF Figure 2 Example (computer communication devices):

1. Stores selling such items
2. Increased speed and complexity of daily living
3. More people in communications
4. Increasing awareness of other new technologies
5. Increasing awareness of other cultures and ideas
6. More business transactions in less time

Phase 3 — First Ring Closure

모든 primary 표시 후 ring으로 연결("A ring can be drawn connecting the primary impacts"). 시각적 첫 번째 동심원 완성.

ring count 검증 (wheel_engine.py validate_ring_counts):

echo '{"depth_target":1,"ring_1":[...],"center_id":"Center"}' | python3 wheel_engine.py validate_ring_counts

Phase 4 — Secondary Ring (T+5~10y)

⛩️ Gate_P2_Pre 자동 호출:

echo '{"ring_num":2,"parent_count":<primary_count>}' | python3 wheel_engine.py websearch_count
# → min_websearch = max(3, primary_count)

핵심 전환: Leader가 "forget about the original item in the middle" 지시.

Brainstorm Panel이 각 primary에서 2~3개 secondary 분기. CoER + citation 의무. 부호 명시.

PDF Figure 3 Example:

• "Stores selling such items" → "High-tech sales force training", "Future-oriented customers", "More technologically literate societies"
• "Increased speed and complexity" → "Information overload", "Life more complex"

Phase 5 — Tertiary Ring (T+10~20y)

⛩️ Gate_P3_Pre 자동 호출:

echo '{"ring_num":3,"parent_count":<secondary_count>}' | python3 wheel_engine.py websearch_count
# → min_websearch = max(3, secondary_count)

• historical emergent analog ≥1 강제 (LLM 제공, 출처 인용)
• 각 secondary에서 1~2개 tertiary spoke + oval
• CoER + citation 의무. 부호 명시.

⭐ Phase 6 — Quaternary Ring (T+15~25y, 세옹지마 1차 반전)

⛩️ Gate_P4_Pre 자동 호출 ⭐:

echo '{"ring_num":4,"parent_count":1}' | python3 wheel_engine.py websearch_count
# → min_websearch: 3 (fixed)

• backlash analog 강제 (LLM: 산업혁명→러다이트, 디지털화→디지털디톡스 등, 출처 인용)
• 🔄 SIGN REVERSAL ≥50% 강제 (wheel_engine.py):

echo '{"impacts":[{"id":"Q1","sign":"-","parent_sign":"+","ring_num":4},...]}' | python3 wheel_engine.py check_sign_reversal
# → must show passed: true, fraction ≥50%

• 통과 못하면 Gate BLOCK (최대 3회 재시도)

각 tertiary의 backlash·역방향 압력 발굴. 세옹지마 효과 시작.

산출 형식:

T1 (🔴 위기) → Q1 (🟢 backlash 회복)
T2 (🔴 위기) → Q2 (🟢 적응)
T3 (🟢 기회) → Q3 (🟡 의도치 못한 부작용)

⭐ Phase 7 — Quinary Ring (T+20~30y, 세옹지마 2차 반전·패러다임 전환)

⛩️ Gate_P5_Pre 자동 호출 ⭐:

echo '{"ring_num":5,"parent_count":1}' | python3 wheel_engine.py websearch_count
# → min_websearch: 3 (fixed)

• paradigm shift analog 강제 (LLM: 코페르니쿠스·다윈·프로이트·양자역학, 출처 인용)
• 🔄🔄 SIGN REVERSAL ≥50% 강제 (wheel_engine.py check_sign_reversal, ring_num=5)
• 통과 못하면 Gate BLOCK

Quaternary backlash가 세계관·언어·제도 재구성하는 단계. 반전의 반전.

각 quinary에 재구성되는 세계관·제도·언어 명시.

⭐ Phase 8 — Senary Ring (T+25~50y, 세옹지마 3차 반전·문명 단위)

⛩️ Gate_P6_Pre 자동 호출 ⭐:

echo '{"ring_num":6,"parent_count":1}' | python3 wheel_engine.py websearch_count
# → min_websearch: 2 (fixed)

• civilizational analog 강제 (LLM: 농업혁명·문자혁명·산업혁명·정보혁명, 출처 인용)
• 🔄🔄🔄 SIGN REVERSAL ≥50% 강제 (wheel_engine.py check_sign_reversal, ring_num=6)
• chaos attractor 후보 ≥1 명시: 퀴나리 영역에서 미세 변화가 세나리 결과를 크게 바꾸는 bifurcation point를 식별 (butterfly effect)
• 통과 못하면 Gate BLOCK

각 senary에 civilizational analog citation + attractor amplification mechanism 명시.

Phase 9 — Evaluation Pass + SRS 검증

SRS 계산 (wheel_engine.py compute_srs):

echo '{"lineages":[{"id":"L1","signs":["+","-","+","-","+","-","+"],"path_labels":["Center","P1","S1","T1","Q1","Qn1","Sn1"]},...]}' | python3 wheel_engine.py compute_srs

SRS 기준:

• avg_SRS ≥ 1.5 → EXCELLENT (풍부한 세옹지마 효과)
• avg_SRS 1.0~1.49 → ACCEPTABLE
• avg_SRS < 1.0 → REVISIONS_REQUIRED — Phase 6/7/8 재작업

SRS = 각 lineage(Center→P→S→T→Q→Qn→Sn)에서 연속 부호 역전 횟수의 평균.

이어 PDF 명시 2가지 평가 방식 중 선택:

방식 A — Fast (PDF §III.A 인용):

"At first, this process goes quickly, with participants listing second, third, and fourth order consequences with little or no evaluation. After the group feels its thinking is represented on the wheel, they can evaluate and edit the wheel to be more 'realistic.'"

방식 B — Wagschal (PDF §III.A 인용):

"Alternatively, the impacts of an event or trend can be processed more slowly and deliberately by accepting criticism prior to entering anything on the wheel. In this approach, the group discusses the plausibility of every impact. If an impact is judged plausible by all, then it is entered; otherwise, not. Peter Wagschal refers to this as the 'rule of unanimity.'"

방식 B 선택 시 마스터가 vision-foresight-futures-wheel-quality-control sub-skill 함께 호출.

6. Mind Mapping vs Futures Wheel 구분

Glenn(2009) §III.A 명시:

"Sometimes people may want to pursue sequential chains of impacts radiating out in a linear fashion from the initial trend or event. This variation is referred to as Mind Mapping. The Futures Wheel, in contrast, completes each ring in concentric circles."

본 sub-skill은 Futures Wheel 방식 강제. Mind Mapping 명시 요청 시에만 linear chain 전환 — 마스터 알림.

7. 입력 검증 명세

전체 검증 (wheel_engine.py validate):

echo '{"center_issue":{"what":"...","when":"...","where":"...","who":"..."},"depth_target":6,...}' | python3 wheel_engine.py validate

8. 출력 표준 형식

8.1 Mermaid Mindmap (전체 6차까지)

mindmap
  root(("**{중앙 이슈}**"))
    P1["Primary 1"]
      S1a["Secondary 1a"]
        T1a1["Tertiary 1a1"]
          Q1a1a["Quaternary 1a1a 🔴→🟢"]
            Qn1a1a1["Quinary 1a1a1 🟢→🔴"]
              Sn1a1a1a["Senary 1a1a1a 🔴→🟢"]
      S1b["Secondary 1b"]
    P2["Primary 2"]
      S2a["Secondary 2a"]
        T2a1["Tertiary 2a1"]
    ...

8.2 ASCII Wheel (6차 포함)

                         Sn1a1 ─ Qn1a1 ─ Q1a1
                                         /
                      T1a1 ─── S1a ─── P1 ─── (ring 1)
                     /                         \
[Center] ──────────                             S1b ─── T1b1 ─ Q1b1 ─ Qn1b1 ─ Sn1b1
                     \
                      T2a1 ─── S2a ─── P2 ─── S2b ─── T2b1 ...

8.3 차수별 표 (6차 전체, wheel_engine.py build_ring_table 생성)

echo '{"depth_target":6,"ring_1":[...],...}' | python3 wheel_engine.py build_ring_table

표 형식:

| 차수 | # | Impact | 시간 | 부모 oval | 부호 |
|-----|---|--------|------|-----------|------|
| Primary | P1 | {impact} | T+1~5y | Center | + |
| Primary | P2 | {impact} | T+1~5y | Center | - |
| Secondary | S1a | {impact} | T+5~10y | P1 | + |
| Secondary | S1b | {impact} | T+5~10y | P1 | - |
| Tertiary | T1a1 | {impact} | T+10~20y | S1a | + |
| Quaternary | Q1a1a | {impact} | T+15~25y | T1a1 | - |
| Quinary | Qn1a1a1 | {impact} | T+20~30y | Q1a1a | + |
| Senary | Sn1a1a1a | {impact} | T+25~50y | Qn1a1a1 | - |

8.4 PDF 원전 인용 fragment

> *Glenn (2009) V3.0 §III.A*: "{관련 인용문}"

9. 마스터 입력 인터페이스

sub_skill: vision-foresight-futures-wheel-basic-v1
inputs:
  center_issue:
    what: "{이슈 정의}"
    when: "{시점}"
    where: "{지리적 범위}"
    who: "{1차 주체}"
  depth_target: 6          # default 6 (박사님 강화), range [1,6]
  domains_frame: "{free-form or user-specified}"
  evaluation_mode: "fast"  # "fast" | "wagschal"
  primary_count_target: 7  # [5, 10]
  secondary_per_primary: 2  # [2, 3]
  tertiary_per_secondary: 1 # [1, 2]
  expert_pool_cast: []      # names from foresight-expert-pool
  web_research_results: {}
outputs:
  - mermaid_mindmap         # 6차까지 포함
  - ascii_wheel             # 6차까지 포함
  - tier_table              # wheel_engine.py build_ring_table 결과
  - pdf_citations
  - phase_log
  - srs_report              # wheel_engine.py compute_srs 결과
  - sign_reversal_reports   # wheel_engine.py check_sign_reversal × 3 (ring 4,5,6)
  - coer_validation         # wheel_engine.py check_coer 결과

10. Strengths (Glenn §IV)

Glenn (2009) §IV:

• Easy and enjoyable: no equipment necessary
• Quick group thinking activation
• Easy to transfer and adapt
• Diagnoses group's collective thinking about the future

본 sub-skill은 Glenn 원전 V1 본질 보존. Weaknesses(단순 collective judgment, correlation/causation 혼동, intellectual spaghetti)는 vision-foresight-futures-wheel-quality-control sub-skill에서 별도 점검.

11. 오류 및 예외 처리

12. 호출 후 마스터로 반환

sub_skill_output:
  status: completed
  ring_count:
    primary: N
    secondary: M
    tertiary: K
    quaternary: L
    quinary: J
    senary: I
  srs_report:             # wheel_engine.py compute_srs 결과
    avg_srs: float
    status: EXCELLENT | ACCEPTABLE | REVISIONS_REQUIRED
  sign_reversal_reports:  # rings 4,5,6 각각
    ring_4: {passed, fraction_pct}
    ring_5: {passed, fraction_pct}
    ring_6: {passed, fraction_pct}
  coer_validation:        # wheel_engine.py check_coer 결과
    valid: bool
    complete_entries: int
  contradictions_detected: [...]
  feedback_loops_suspected: [...]
  scenario_branches: [...]
  visualizations:
    mermaid: "..."
    ascii: "..."
    table: "..."          # wheel_engine.py build_ring_table 결과
  pdf_citations: [...]
  agent_log:
    leader: "..."
    panel: "..."
    synthesizer: "..."
    visualizer: "..."

13. references/

참고문헌

• Glenn J.C. (2009 [1971]). Futures Wheel. In J.C. Glenn & T.J. Gordon (Eds.), Futures Research Methodology V3.0, Chapter 06, §III.A, Figures 1·2·3.
• Wagschal P. (cited in Glenn 2009 §III.A): "the rule of unanimity" — 방식 B 평가에서 all-agree-before-entering.
• 박사님 2026-05-11 강화: 6차 default, SRS (Sewongjima Reversal Score), SIGN REVERSAL ≥50% 강제.