How Decisions Are Made
“The Multi-Intelligence Catalyst operates through an eight-stage decision cycle—from Intention through Reflection to renewed Intention—that mirrors how learning occurs in complex adaptive systems.” At the decision point sits the 80/100 Covenant.
The 80/100 Covenant
Decisions move forward when 80% agreement is reached, while 100% of Catalyst members commit to implementation. Dissenters serve as scouts, watching for signals and consequences the majority might miss.
A Holistic Pathway in Space, Key Stewardship/Governance Features
“The 20% don’t just acquiesce—they transform.” They become the “loyal opposition,” commit fully to making the decision work, hold space to notice if course correction is needed, and are “scouts, not saboteurs.” Their dissent is documented, honored, and actively consulted during implementation.
Initial decisions are time-bound, typically 3–6 months. Then the Catalyst reconvenes to examine what emerged, whether the 20% concerns were validated, and whether to continue, adjust, or reverse course.
Perfect consensus
Sounds ideal, but “often leads to lowest common denominator thinking, tyranny of the minority, exhaustion, and performative agreement.”
Simple majority
Efficient, but “creates winners and losers, doesn’t build genuine buy-in, and loses the wisdom in the dissenting 49%.”
The Covenant
“The threshold where substantial agreement exists, meaningful dissent remains, forward movement is possible, and commitment can be genuine.” The crucial innovation is the 100% commitment from the 20%.
Comparison from Appendix B, “On the 80/100 Covenant.”
The eight stages
“Think of it as a spiral or ferris wheel—we return, but transformed.”
1Intention
- What are we trying to serve? (Always in service to the Holistic Pathway in Space)
- Which intelligence(s) does this primarily concern?
- What’s the deeper purpose beyond the immediate task?
2Questions / Issues
- What don’t we know?
- What’s the actual problem or opportunity?
- Engage all four intelligences: What questions does each raise?
- Resist the rush to answers
3Options
- Generate possibilities (human creativity, AI modeling, natural patterns, cosmic timing)
- Hold multiple options longer than is comfortable
- Welcome the wild ideas alongside the practical ones
4Decisions / Choices
- Apply the 80/100 Covenant
- Use the Four-Fold Check
- Identify who has primacy for this decision
- Explicitly name the 20% dissent and its role going forward
5Actions
- Implement with full commitment (even those who were in the 20%)
- Document who’s doing what, when, how
- The 20% become scouts, watching for what the majority might miss
6Outcomes / Results
- What actually happened?
- Measure against intention, not just against plan
- Include unexpected results, especially those signaled by Natural/Cosmic intelligence
7Reflections
- What did we learn?
- Where were we wrong? (Incompetence Ledger entry)
- Which intelligence did we hear well? Which did we miss?
- What surprised us?
- What do we need to unlearn?
8Repeat → New Intention
- Spiral back with deeper understanding
- New questions emerge from old answers
- The cycle begins again, but we are changed
Biomimicking intelligence
Appendix B calls it “one of the most beautiful observations during the development of this framework”: the eight-stage cycle mirrors patterns across all four intelligences.
Natural and cosmic patterns
Seasons cycling … → spring again, transformed. Planetary orbits returning.
Mycelial networks: sense → respond → sense again.
Tidal rhythms: intention (the moon) → action (water rising) → outcome (shoreline transformed) → reflection (the ebb) → repeat.
Human patterns
Scientific method: hypothesis → experiment → results → analysis → new hypothesis.
Traditional wisdom cycles: dreaming → questioning → seeking → harvesting → reflecting → dreaming again.
Learning theory: intention → inquiry → exploration → decision → practice → assessment → integration → new intention.
AI patterns
Machine learning loops: objective function → data gathering → model generation → prediction → testing → evaluation → parameter adjustment → repeat.
Reinforcement learning: goal → explore → select action → receive feedback → update policy → repeat.
The cycle isn’t imposed on these intelligences—it emerges from how intelligence itself functions across domains. … When the Catalyst makes decisions using this cycle, we’re biomimicking intelligence itself.
A Holistic Pathway in Space, Appendix B: Why This Works
Questions still open
The paper names its own uncertainties about the framework: “Can this actually scale beyond a small group of committed pioneers? What happens when the four intelligences fundamentally disagree with no clear path to 80%?”