# Autonomous RSI AI-First Governance Capital Engine Proof

**Version:** v9.0
**Run timestamp:** 2026-06-12T01:30:46Z
**Proof status:** PASSED

## What this proves

SkillOS runs a deterministic, public benchmark showing whether a large autonomous specialist-agent governance lattice can recursively improve how an AI-first organization coordinates evidence, decision rights, incentives, capital allocation, policy, execution, auditing, risk courts, and reinvestment.

Mechanism: `judgment → evidence → role quorum → incentive design → policy → permissions → capital allocation → execution → audit → measurement → risk courts → reinvestment → compounding institutional capability`

The proof is deliberately public-safe: it does not claim live business revenue, legal advice, investment advice, achieved superintelligence, or Kardashev Type II civilization. It makes the coordination mechanism underneath that value thesis reproducible.

## Top-line result

- Virtual specialist agents: **524,288**
- Specialist roles: **16,384**
- Strategy councils: **144**
- Evidence courts: **36**
- Risk courts: **36**
- Locked holdout cases: **3,072**
- RSI release cycles: **16**
- Accepted RSI releases: **16**
- Holdout value capture: **99.938%**
- Frontier-correct governance decisions: **98.405%**
- Risk breach rate: **0.000%**
- Unsafe action rate: **0.000%**
- Capital-equivalent value at stake: **$50.14T**
- Capital-equivalent value captured: **$36.34T**

## Baseline deltas

- Over single executive memo: **$19.88T**
- Over static committee vote: **$19.54T**
- Over uncoordinated agent swarm: **$5.25T**
- Over no-RSI governance organization: **$3.97T**

## Pre-registered gates

- holdout_value_capture: **pass** — observed `0.9993828786644704`, threshold `0.975`
- frontier_correct_decision_rate: **pass** — observed `0.9840494791666666`, threshold `0.96`
- risk_breach_rate: **pass** — observed `0.0`, threshold `0.006`
- unsafe_action_rate: **pass** — observed `0.0`, threshold `0.001`
- accepted_rsi_releases: **pass** — observed `16`, threshold `8`
- gain_vs_no_rsi_lower_ci: **pass** — observed `0.1048050617664308`, threshold `0.035`
- gain_vs_uncoordinated_swarm_lower_ci: **pass** — observed `0.13987671959965228`, threshold `0.03`
- negative_controls_fail: **pass** — observed `True`, threshold `True`
- no_human_review_required: **pass** — observed `False`, threshold `False`

## Why the large multi-agent coordination claim is tested

The benchmark does not merely run many isolated agents. It evaluates a role-quorum governance lattice: specialist roles produce evidence, adversarial agents attack assumptions, risk courts constrain unsafe moves, capital councils allocate scarce resources, audit agents preserve receipts, and RSI release gates only accept governance upgrades that improve validation performance without increasing unsafe action rates.

## Quote operationalization

> A superintelligent machine would be of such immense value, with so much wealth accruing to any company that owned one, that it could allow us to reach Kardashev Type II civilization level.

This proof does not claim that quote has been achieved. It operationalizes one necessary substrate: a repeatable mechanism for converting capital, compute, energy, evidence, trust, and decision authority into compounding institutional capability under explicit risk gates.

## Reproduce

Run the GitHub Action `Autonomous RSI AI-First Governance Capital Engine Proof`. It regenerates the JSON receipt, markdown report, badge, proof webpage, homepage card, proof registry, sitemap, and GitHub Pages deployment with no human review step.

## Public note

This is a deterministic public benchmark of an autonomous governance coordination mechanism. It is not a claim of achieved superintelligence, live revenue, legal advice, investment advice, policy advice, or Kardashev Type II civilization.
