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Prediction Process

How will I know if I was right or wrong?

Prompts​

For every prediction you make:

  1. "What's my conviction level (0-5)?" — Quantify confidence
  2. "What's the time horizon?" — When will this resolve?
  3. "How will I know I was right/wrong?" — Define success criteria
  4. "What would change my conviction?" — Identify update triggers
  5. "What's my position/allocation?" — Match stakes to conviction

The Prediction Record​

FieldQuestionExample
PredictionWhat exactly am I predicting?"AI coding assistants replace 50% of junior dev tasks"
Time FrameWhen will this resolve?"By end of 2026"
ConvictionHow confident am I (0-5)?4/5
PositioningWhat's my stance?Early adopter, investing in AI tools
AllocationWhat resources am I committing?20% of learning time, $500/year in tools

Context​

  • Source: Identify where the prediction originates (e.g., expert opinion, market research, historical analysis).
  • Domain: Categorize the prediction into macro-environmental dimensions using frameworks like STEEP (Social, Technological, Economic, Environmental, Political).
  • Scope: Assess whether the prediction impacts a niche area or has global, cross-industry implications.

Evaluate Key Drivers​

  • Trends: Analyze historical trends that support the prediction. Trends are relatively stable and often predictable over time.
  • Emerging Issues: Identify nascent signals or weak indicators that could evolve into major drivers (e.g., new technologies, policy shifts).
  • Discontinuities: Consider potential disruptions that could alter the trajectory of the prediction (e.g., economic crises, regulatory changes).

Assess Timeframes​

Use forecasting models to estimate when predictions might materialize:

  • Time Series Models: Analyze historical data to project future trends.
  • Scenario Planning: Develop multiple plausible scenarios with varying time horizons to account for uncertainties.
  • Expert Judgment (Delphi Method): Aggregate opinions from a panel of experts to refine timelines.

Quantify Confidence Levels​

Assign personal conviction scores (e.g., 0/5 to 5/5) based on:

  • Quality of evidence supporting the prediction.
  • Alignment with broader meta-trends.
  • Credibility of the source or expert making the prediction.

Explore Consequences and Symptoms​

Map out potential ripple effects of the prediction:

  • What industries or systems will be impacted?
  • What secondary trends might emerge as a result?

This step can be visualized as a mind map branching out from initial trends to consequences and opportunities.

Positioning and Strategic Intent​

Define your positioning in response to the prediction:

  • Are you an observer, early adopter, or market leader in this space?
  • What actions or investments are required to align with this future?

Track and Validate Predictions​

Continuously monitor real-world developments to validate or adjust predictions:

  • Use tools like Google Trends, social listening platforms, and sales data analysis to track signals in real-time.
  • Compare past forecasts with actual outcomes to refine your methodology.

For large-scale predictions like those from Framework Ventures (e.g., blockchain adoption, DeFi growth), apply additional filters:

  • Market Size Estimates: Validate assumptions about user base growth (e.g., "1-3 billion MAUs on blockchains by 2030").
  • Technological Feasibility: Assess whether enabling technologies (e.g., Layer 2 blockchains) can scale within the predicted timeframe.
  • Policy and Regulation: Factor in geopolitical and regulatory shifts that could accelerate or hinder progress (e.g., global crypto policy).

Context​

Resources​