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Make accountable long-term predictions with skin in the game, forcing rigorous thinking about future outcomes through public commitments and charitable stakes

1 stars
1.2k downloads
Updated 3/20/2026

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SKILL.md

Long Bet Project

Overview

The Long Bet Project, created by the Long Now Foundation in 2002, is a public arena for accountable predictions about the future. It addresses a critical problem: pundits, CEOs, and thought leaders routinely make confident predictions with zero accountability. Media's short attention span lets them escape consequences when wrong.

Long Bets demands predictors put their name, a solid argument, and money down in support of their statement. Winnings go to charity. This mechanism transforms cheap talk into costly signals - if you're wrong, a cause you oppose might benefit. The minimum term is 2 years with no maximum, encouraging thinking across decades or centuries.

The framework operationalizes prediction accountability: your forecast becomes a matter of public record, your reasoning is documented, and resolution is guaranteed by institutional continuity. Warren Buffett's famous 10-year bet against hedge funds (won in 2017) demonstrated the model's power to settle debates definitively.

When to Use

  • Making long-term predictions you want held accountable
  • Settling debates that won't resolve for years or decades
  • Forcing rigorous thinking about future outcomes
  • Creating skin in the game for forecasts
  • Building institutional memory around predictions
  • Testing expertise claims publicly
  • Funding charities through competitive prediction
  • Challenging overconfident forecasters to back their words

The Process

Step 1: Formulate a Clear, Falsifiable Prediction

State exactly what will happen by when. Binary outcomes only - no hedging.

Poor prediction: "AI will change everything by 2030" Strong prediction: "By December 31, 2030, a commercially available AI system will have won a Grammy for Best New Artist"

Step 2: Build Your Argument

Document WHY you believe this outcome. Include:

  • Causal mechanism (what forces make this outcome likely)
  • Evidence supporting your position
  • Acknowledgment of key uncertainties
  • Why the timeline is appropriate

Example argument: "Foundation models demonstrate emergent musical composition. Grammy's 'Best New Artist' eligibility requires human performance, but AI-generated personas with human performers already chart. Commercial incentives push labels toward AI collaboration. Timeline based on 10-year cycles in music industry disruption."

Step 3: Set Meaningful Stakes

Minimum $200 per side, no maximum. Consider:

  • Amount large enough to create genuine accountability
  • Amount you can afford to lose entirely
  • Charity you'd want to fund if you win
  • Charity you'd prefer NOT fund (opponent's choice)

Stakes design: Higher stakes = stronger signal of conviction. Buffett bet $1M. Match stakes to confidence level.

Step 4: Publish and Invite Challenge

Make your prediction public. Either:

  • Post on longbets.org ($50 publication fee)
  • Announce publicly with clear terms and escrow mechanism

Critical: True names required. Anonymous predictions don't create accountability.

Step 5: Wait and Let the Future Adjudicate

Resist the urge to hedge or revise. The prediction stands as written.

Resolution: Mutual agreement between parties if both alive, otherwise Long Now Foundation adjudicates. Public announcement and charitable disbursement.

Step 6: Analyze the Outcome (Win or Lose)

Win: Document what you got right and why your reasoning held. Lose: Conduct honest post-mortem - where did your model break?

Key insight: The learning value exists regardless of outcome. The process of rigorous prediction improves forecasting ability over time.

Example Application

Situation: Tech industry debate about cryptocurrency future (2018).

Application:

  • Prediction: "By December 31, 2028, at least one sovereign nation will use Bitcoin as its primary legal tender for all domestic transactions"
  • Argument: El Salvador adoption trend, hyperinflation in emerging markets, Lightning Network scalability, generational shift in money perception
  • Stakes: $5,000 per side
  • Charities: Winner's choice - Electronic Frontier Foundation; Opponent's choice - Institute for Humane Studies
  • Publication: Posted on longbets.org with full reasoning

Outcome tracking: El Salvador adopted BTC as legal tender in 2021, but "primary" for "all domestic transactions" remains unmet. Prediction continues.

Scoring Rubric

  • Practitioner Weight: 8/10 - Real-money stakes from notable figures (Buffett, Bezos donors)
  • Clarity/Executability: 9/10 - Extremely clear process with institutional support
  • ROI: 7/10 - Indirect benefits through improved forecasting discipline
  • Novelty: 8/10 - Unique mechanism combining prediction markets with charity
  • Cross-domain: 8/10 - Applicable to any falsifiable future claim

Total: 40/50

Anti-Patterns

  • Making vague predictions that can't be definitively resolved
  • Setting stakes too low to create real accountability
  • Using pseudonyms or anonymous accounts (defeats accountability)
  • Refusing to publish reasoning (hides from scrutiny)
  • Revising predictions after initial publication
  • Betting on unfalsifiable outcomes ("AI will be important")
  • Ignoring the post-mortem learning opportunity
  • Only making predictions you're highly confident about (no learning)

Related

  • superforecasting (systematic prediction accuracy improvement)
  • tetlocks-10-commandments (forecasting best practices)
  • skin-in-the-game (accountability through personal risk)
  • cathedral-thinking (multi-generational timeframes)
  • thinking-in-bets (probabilistic decision-making)

Install

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AI Quality Score

78/100Analyzed 3/28/2026

Well-written conceptual framework skill about the Long Bet Project with clear process steps, good examples, anti-patterns, and related concepts. Scores high on clarity and safety. Somewhat limited actionability as it's advisory rather than technical. Tag mismatch (ci-cd) is confusing. General-purpose skill applicable across domains for accountability in long-term predictions.

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Metadata

Licenseunknown
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Updated3/20/2026
Publisherlev-os

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ci-cd