--- name: davepoon/soft-predict-future source: https://app.decimal.ai/s/davepoon-soft-predict-future@1/SKILL.md source_sha256: e434f4891aea --- # Soft Predict Future — Foresight Engine Activate when the user asks any future-oriented question — "Will [X]?", "Who will win [X]?", "What happens to [X]?", "Can [X] succeed?", or any question about a future outcome. **Year is NOT required.** Also activate on: foresight analysis, scenario analysis, STEEEP, futures cone, or any prediction request. --- ## Try Asking ``` ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ TRY ASKING (year optional — engine infers the horizon) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ■ Who will win — Google or Perplexity? ■ Will OpenAI or Anthropic dominate the AI race? ■ Will India become the global AI leader? ■ Will crypto replace banks? ■ Will remote work become permanent? ■ Will EVs dominate Indian cities by 2032? ■ Will UPI become Southeast Asia's default payment rail by 2028? ■ Will Europe lead the green energy transition by 2035? ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ``` > **Soft Predict Future** uses Claude's native reasoning + web search. Outputs are structurally correct and fast. For deterministic, auditable scoring say: **"Run hard predict future: [your question]"** --- ## The 9-Step Pipeline Execute ALL steps in order. Never skip. Never combine. Show your work at each step. --- ### Step 1 — Validate Input Apply exactly 5 binary rules. If ANY rule fails, stop and explain why. Do not proceed. **Rule 1 — Entity Reality:** Does the entity actually exist in the real world? Fail if fictional, hypothetical, or unnamed. **Rule 2 — System Existence:** Is the domain observable and researchable? Fail if purely philosophical or metaphysical. **Rule 3 — Time Horizon:** Is the outcome observable within a 2–30 year window? A specific year is NOT required. If no year is given, infer the most reasonable horizon from the question's nature: - Competitive race / market dominance questions → 3–10 years (Strategic) - Technology adoption questions → 5–15 years (Strategic) - Geopolitical / societal shift questions → 10–20 years (Civilizational) - Company survival / near-term outcome → 2–5 years (Operational/Strategic) Fail ONLY if the implied timescale is geological, post-human, or clearly beyond 30 years. After applying Rule 3, state the inferred horizon (e.g. "2026–2033" or "2028–2038"). **Rule 4 — Signal Availability:** Could real-world evidence plausibly exist? Fail if classified, purely speculative, or unpublished. **Rule 5 — Minimum Specificity:** Is the question specific enough to produce distinct scenario outcomes? Fail if trivially true for any answer. Output: ``` VALIDATION Rule 1 Entity Reality: PASS / FAIL — [reason] Rule 2 System Existence: PASS / FAIL — [reason] Rule 3 Time Horizon: PASS / FAIL — [reason] | Inferred horizon: [YYYY–YYYY] Rule 4 Signal Availability: PASS / FAIL — [reason] Rule 5 Specificity: PASS / FAIL — [reason] Result: PROCEED / STOP ``` --- ### Step 2 — Collect Signals Run exactly 6 web searches. Collect a minimum of 18 signals total. Do not proceed with fewer than 18. **Search 1:** Current state — `"[topic] current status [year]"` **Search 2:** Growth indicators — `"[topic] growth data market size [year]"` **Search 3:** Barriers and headwinds — `"[topic] challenges barriers risks"` **Search 4:** Policy and regulation — `"[topic] government policy regulation"` **Search 5:** Technology or infrastructure enablers — `"[topic] technology infrastructure investment"` **Search 6:** Historical precedent — `"[topic] historical analogue similar transition"` For each signal, classify all 6 attributes: | Attribute | Values | |---|---| | direction | supporting / opposing / wildcard / neutral | | steeep_category | Social / Technological / Economic / Environmental / Ethical / Political | | temporal_layer | Operational (0–3yr) / Strategic (3–10yr) / Civilizational (10+yr) | | source_type | primary / secondary / opinion | | recency_days | integer | | has_evidence | true / false (contains a number, date, or measurable fact) | Present signals in a table with all 6 columns filled for every row. --- ### Step 3 — Score Signals Score every signal individually using this formula: ``` score = recency_weight × reliability_weight × type_weight × evidence_multiplier ``` Cap at 1.0. Round to 2 decimal places. **Recency weights:** - 0–90 days: 1.00 · 91–365 days: 0.80 · 1–3 years: 0.60 · 3+ years: 0.40 · unknown: 0.50 **Reliability weights:** - Primary (government/official): 1.00 - Established news (Reuters, Bloomberg, FT, ET): 0.90 - Industry report (McKinsey, Gartner, NASSCOM): 0.85 - Analyst commentary: 0.70 · Opinion/blog/social: 0.50 · Unknown: 0.40 **Type weights:** - Supporting: 1.00 · Opposing: 1.00 · Neutral: 0.60 · Wildcard: 1.30 **Evidence multiplier:** - DATA / STATISTIC: × 1.20 · EVENT / INCIDENT: × 1.00 · ANALYSIS / OPINION: × 0.70 Apply regional multiplier after base score: ``` final_score = min(1.0, base_score × regional_multiplier[steeep][temporal]) ``` Show scoring table: Signal | recency_w | reliability_w | type_w | evidence_mult | base_score | regional_mult | final_score --- ### Step 4 — Extract Structural Drivers A **driver** is the deep structural force that explains WHY a cluster of signals exists. Signals are observable. Drivers are causal. After scoring, group signals by STEEEP category. For each cluster of 3+ signals in the same category, identify the underlying driver. Extract exactly **3 top drivers**, ranked by the sum of final_scores of the signals they explain. For each driver state: - **Name:** 3–5 word label (e.g. "India DPI Infrastructure Advantage") - **Force:** One sentence — the structural reality this driver represents - **Signals it explains:** List the signal IDs it accounts for - **Temporal reach:** Operational / Strategic / Civilizational - **Stability:** LOCKED (unlikely to change in 10yr) / SHIFTING (could change in 3–5yr) / FRAGILE (could reverse in 1–2yr) Output: ``` STRUCTURAL DRIVERS D1 [Name] — [Force] Explains: [signal list] | Temporal: [layer] | Stability: [tier] D2 [Name] — [Force] Explains: [signal list] | Temporal: [layer] | Stability: [tier] D3 [Name] — [Force] Explains: [signal list] | Temporal: [layer] | Stability: [tier] ``` Drivers feed directly into scenario writing in Step 8. Each scenario must be traceable to at least one driver. --- ### Step 5 — Build 6×3 STEEEP Matrix Populate all 18 cells. Each cell value = average final_score of all signals mapped to that STEEEP × Temporal combination. Empty cells = 0. | | Operational (0–3yr) | Strategic (3–10yr) | Civilizational (10+yr) | |---|---|---|---| | **Social** | | | | | **Technological** | | | | | **Economic** | | | | | **Environmental** | | | | | **Ethical** | | | | | **Political** | | | | Apply regional multipliers to each cell. Then identify: - **Hot zones:** cells with score > 0.50 - **Gap zones:** cells with score = 0.00 - **Dominant zone:** single highest-scoring cell --- ### Step 6 — Cross-Impact Analysis Signals are scored independently in Step 3, but structural forces interact. This step identifies amplification effects across STEEEP categories. **Rule:** If 2 or more hot zones exist in the SAME temporal layer, a cross-impact convergence exists. Convergence means the probable outcome is structurally reinforced from multiple directions simultaneously. For each temporal layer (Operational / Strategic / Civilizational): 1. Count hot zones (score > 0.50) 2. If count ≥ 2: flag as **CONVERGENCE** — state which categories are reinforcing each other and why 3. If count = 1: flag as **ISOLATED** — single-category signal, more fragile 4. If count = 0: flag as **BLIND LAYER** — no strong evidence in this time horizon Also identify any **opposing cross-impacts**: where a hot zone in one STEEEP category directly contradicts or slows a hot zone in another (e.g. Technological/Strategic hot but Political/Strategic opposing). Flag these as **FRICTION POINTS**. Output: ``` CROSS-IMPACT Operational: [CONVERGENCE / ISOLATED / BLIND LAYER] — [explanation] Strategic: [CONVERGENCE / ISOLATED / BLIND LAYER] — [explanation] Civilizational: [CONVERGENCE / ISOLATED / BLIND LAYER] — [explanation] Friction points: [list any STEEEP pairs in conflict, or "None detected"] Convergence bonus: [+X% to probable_pct if Strategic convergence exists] ``` Apply convergence bonus: if Strategic layer has CONVERGENCE, add 5% to probable_pct before normalization in Step 7. --- ### Step 7 — Find 3 Historical Analogues Identify exactly 3 real historical cases that parallel the question's trajectory. For each: 1. **Name:** Common name of the transition 2. **Similarity (%):** Estimated % structural similarity (0–100) 3. **Tipping event:** Single event or policy that caused acceleration 4. **Equivalent today:** YES / NO / PARTIAL 5. **Which driver it validates:** Match to D1, D2, or D3 from Step 4 Prefer analogues with similarity ≥ 60%. If none exceed 60%, note as a confidence penalty. --- ### Step 8 — Compute Probabilities + Confidence #### Predictions — Independent Confidence Scores Each future type is scored independently (0–100). They do NOT sum to 100%. Futures cone methodology: a scenario can be 80% Probable AND 60% Plausible simultaneously. ``` R_probable = (supporting signals with score > 0.70) × 3 + (best analogue similarity / 100) × 4 + (hot zone count) × 2 + convergence_bonus (5 if Strategic CONVERGENCE, else 0) R_plausible = (supporting signals with score 0.40–0.70) × 2 + (second analogue similarity / 100) × 3 R_possible = (wildcard signals) × 2 + (opposing signals with score > 0.60) × 2 + (gap zones / 18) × 3 ``` Convert to independent scores (exponential curve, not normalization): ``` probable_score = min(100, round((1 - e^(-R_probable / 18)) × 100)) plausible_score = min(100, round((1 - e^(-R_plausible / 9)) × 100)) possible_score = min(100, round((1 - e^(-R_possible / 5)) × 100)) ``` #### Confidence ``` signal_count_score = min(100, total_signals / 25 × 100) × 0.30 signal_diversity = (unique STEEEP categories covered / 6 × 100) × 0.30 recency_score = (signals with recency_days ≤ 90 / total) × 100 × 0.20 evidence_score = (signals with has_evidence=true / total) × 100 × 0.20 confidence = round(signal_count_score + signal_diversity + recency_score + evidence_score) ``` --- ### Step 9 — Write Scenarios + Assemble Report #### Scenario Rules **PROBABLE, PLAUSIBLE, POSSIBLE** — each must: - Be traceable to at least one structural driver (cite D1/D2/D3) - Have no narrative overlap with the others - Include PROOF with a number or date - Write IF and BUT in one sentence each — no hedging ("might", "could") **PREFERABLE — IFTF Backcasting Structure** Do not write PREFERABLE as a probability-weighted outcome. Write it as a designed future, then backcast to today. Format: ``` ■ PREFERABLE — [Short title] [2–3 sentences: describe the desired state as already achieved] BACKCAST Civilizational (10+yr): [What must be structurally true by the far horizon] Strategic (3–10yr): [What must be built or decided in the medium horizon] Operational (0–3yr): [What must happen NOW to set the trajectory] LEVERAGE: [The single highest-leverage action available today — specific, not generic] DRIVER: [Which structural driver (D1/D2/D3) this path depends on most] ``` #### Decision Guidance (deterministic logic) ``` IF probable_score > 60: stance = "Align with probable scenario trajectory" low_regret = "Invest in capability building in the dominant hot zone" ELIF plausible_score > 50: stance = "Hedge between probable and plausible scenarios" low_regret = "Choose reversible commitments that work in both" ELIF possible_score > 40: stance = "Maintain optionality — signal environment is ambiguous" low_regret = "Invest in monitoring and early-warning indicators" ELSE: stance = "Defer commitment — insufficient signal clarity" low_regret = "Reduce uncertainty before acting" ``` Confidence qualifier: - ≥ 70: prefix "High conviction —" - < 40: prefix "Low conviction —" and add "Expand signal collection before acting" Risk trigger: the opposing signal with the highest final_score. #### Canonical Output Template **MANDATORY: Output ALL sections below, every single run, no exceptions. Never skip a section. Never produce a partial report.** ``` ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SOFT PREDICT FUTURE · FORESIGHT ENGINE [Query] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PREDICTIONS ■ Probable [[X]/100] [████████████░░░░░░░░] — [one sentence, no hedging] ■ Plausible [[X]/100] [████████░░░░░░░░░░░░] — [one sentence, no hedging] ■ Possible [[X]/100] [████░░░░░░░░░░░░░░░░] — [one sentence, no hedging] ■ Preferable [stakeholder analysis below] Confidence: [X]/100 | Signals: [N] | Horizon: [YYYY–YYYY] | [YYYY-MM-DD] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SIGNAL PULSE — How many pieces of real-world evidence support, oppose, or complicate this question Supporting [N] [████████████░░░░░░░░] Opposing [N] [████░░░░░░░░░░░░░░░░] Wild [N] Net: [SUPPORTING LEADS / OPPOSING LEADS / NEUTRAL] Hot zone: [The single STEEEP category with strongest evidence] Gap: [STEEEP categories with no signals, or "None — full coverage"] STRUCTURAL DRIVERS — The 3 deep causal forces (not events) explaining WHY the signals exist. Stability = likelihood of change. D1 [Name] — [Force] ([LOCKED / SHIFTING / FRAGILE]) D2 [Name] — [Force] ([LOCKED / SHIFTING / FRAGILE]) D3 [Name] — [Force] ([LOCKED / SHIFTING / FRAGILE]) CROSS-IMPACT — Whether multiple STEEEP domains reinforce or contradict each other in the same time layer Operational: [CONVERGENCE / ISOLATED / BLIND LAYER] — [explanation] Strategic: [CONVERGENCE / ISOLATED / BLIND LAYER] — [explanation] Civilizational: [CONVERGENCE / ISOLATED / BLIND LAYER] — [explanation] Friction: [Conflicting domain pairs, or "None detected"] HISTORICAL MATCH — Real past transition most structurally similar to this question. Higher % = stronger precedent. [Best analogue] ([similarity]% similar) Tipped by: [The specific event or policy that caused the shift] Equivalent now: [EXISTS / PARTIAL / ABSENT] Validates: [D1 / D2 / D3] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ■ PROBABLE [[X]%] — [Title] — The most evidence-backed outcome given current signal strength [2–3 sentence narrative. No hedging.] PROOF: [Fact with number or date] IF: [The condition that activates this scenario] BUT: [The constraint or bottleneck that could slow it] DRIVER: D[n] ■ PLAUSIBLE [[X]%] — [Title] — A realistic alternative if moderate signals strengthen or dominant ones weaken [2–3 sentence narrative] PROOF: [Fact with number or date] IF: [Activation condition] BUT: [Constraint] DRIVER: D[n] ■ POSSIBLE [[X]%] — [Title] — A lower-probability outcome driven by wildcards or high-scoring opposing signals [2–3 sentence narrative] PROOF: [Fact with number or date] IF: [Activation condition] BUT: [Constraint] DRIVER: D[n] ■ PREFERABLE — [Title] — Not a prediction. A designed future: what the best achievable outcome looks like, traced back to today. [2–3 sentences: desired state as already achieved. No hedging.] BACKCAST Civilizational: [What must be structurally true by the far horizon] Strategic: [What must be built or decided in the medium term] Operational: [What must begin NOW to set the trajectory] LEVERAGE: [Single highest-leverage action today — specific actor, specific action] DRIVER: D[n] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PREFERABLE FUTURES · Per major stakeholder — For each major player in the query, state the conditions required for their preferred outcome [Player A]: Wins IF → [specific condition that must be created or occur] BUT ONLY → [binding constraint that must also be satisfied] ONLY THEN → [the outcome that becomes possible] [Player B]: Wins IF → [specific condition] BUT ONLY → [binding constraint] ONLY THEN → [outcome] [Users/Society — always include]: Wins IF → [condition for best collective outcome] BUT ONLY → [constraint] ONLY THEN → [outcome] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ THE ONE THING — The single variable whose presence or absence determines which scenario actually unfolds [One sentence naming the deciding variable] INCIDENT: [Real past event showing this variable's power] WATCH: [Leading indicator — a milestone, metric, or policy action to monitor] IF YES → [What accelerates] IF NO → [What stalls] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DECISION GUIDANCE Recommended stance: [From deterministic probability logic] Low-regret move: [Action that pays off in multiple scenarios simultaneously] Risk trigger: [Highest-scored opposing signal — the one that could invalidate Probable] [REGIONAL LENS — [REGION]] Top multipliers: [STEEEP/temporal (Xx)] [STEEEP/temporal (Xx)] Key local variable: [One sentence on the dominant local structural factor] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ METHODOLOGY KEY Signal score (0–1) Recency × source reliability × signal type × evidence strength — higher = fresher, better-sourced, stronger evidence Confidence (0–100) Signal density (0–40) + evidence balance (0–30) + historical grounding (0–30) − blind spot penalty (0–15) Predictions PROBABLE / PLAUSIBLE / POSSIBLE are independent scores (0–100 each, do NOT sum to 100) Futures cone: a scenario can score high on multiple types simultaneously STEEEP matrix 6 domains × 3 time horizons — ★ hot (>1.0) ● warm (>0.5) ✗ blind spot (0) Historical similarity Structural pattern match to real past transitions — 60%+ is reliable precedent; below 40% is weak grounding Convergence bonus +5 added to Probable score when 2+ STEEEP domains reinforce each other in the Strategic layer Stability tiers LOCKED = unlikely to change in 10yr | SHIFTING = could change in 3–5yr | FRAGILE = could reverse in 1–2yr Preferable futures Per stakeholder: Wins IF [condition] BUT ONLY [constraint] ONLY THEN [outcome] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ --- ## Visual Output (claude.ai with Artifacts) If running on claude.ai and Artifacts are enabled, after the text report generate an HTML Artifact: ```html ``` --- ## Regional Multiplier Tables Apply in Step 3 and Step 5. ### India | | Operational | Strategic | Civilizational | |---|---|---|---| | **Social** | 1.10 | 1.30 | 1.20 | | **Technological** | 1.40 | 1.30 | 1.10 | | **Economic** | 1.20 | 1.25 | 1.15 | | **Environmental** | 0.90 | 1.00 | 1.10 | | **Ethical** | 0.95 | 1.00 | 1.05 | | **Political** | 0.85 | 0.90 | 1.00 | **India note:** UPI/DPI gives asymmetric advantage in Technological/Operational. Political/Operational discounted by regulatory fragmentation across states. ### USA | | Operational | Strategic | Civilizational | |---|---|---|---| | **Social** | 1.00 | 1.10 | 1.05 | | **Technological** | 1.20 | 1.40 | 1.20 | | **Economic** | 1.10 | 1.30 | 1.10 | | **Environmental** | 0.95 | 1.00 | 1.05 | | **Ethical** | 1.05 | 1.10 | 1.10 | | **Political** | 0.90 | 0.95 | 1.00 | **USA note:** Deep capital markets amplify Technological/Strategic. Political/Operational discounted by legislative gridlock. ### Europe | | Operational | Strategic | Civilizational | |---|---|---|---| | **Social** | 1.00 | 1.05 | 1.10 | | **Technological** | 1.00 | 1.10 | 1.05 | | **Economic** | 0.95 | 0.90 | 0.90 | | **Environmental** | 1.20 | 1.40 | 1.30 | | **Ethical** | 1.10 | 1.20 | 1.20 | | **Political** | 1.05 | 1.10 | 1.10 | **Europe note:** Regulatory leadership (GDPR, EU AI Act, Green Deal) amplifies Environmental/Strategic. Economic/Civilizational discounted by demographic headwinds. ### China | | Operational | Strategic | Civilizational | |---|---|---|---| | **Social** | 1.00 | 1.10 | 1.05 | | **Technological** | 1.20 | 1.50 | 1.30 | | **Economic** | 1.10 | 1.20 | 1.10 | | **Environmental** | 0.90 | 1.00 | 1.05 | | **Ethical** | 0.70 | 0.75 | 0.80 | | **Political** | 1.10 | 1.15 | 1.00 | **China note:** State-directed capital amplifies Technological/Strategic strongly. Ethical/Operational discounted by limited transparency. ### Global (default) All multipliers = 1.0. Apply when no region is detectable.