add asi-pathway: map arXiv:2606.12683 four AGI-to-ASI pathways to our architecture

src/examples/test-asi.ts

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+import { pathwayReportCard, assessASIPathways } from "../upgrades/asi-pathway.js";
+
+function log(msg: string): void { process.stdout.write(msg + "\n"); }
+
+function main(): void {
+  log("\n" + pathwayReportCard());
+  log("\n=== Gap Closure Needed ===");
+  const assessment = assessASIPathways();
+  for (const p of assessment.pathways) {
+    if (p.gaps.length > 0) {
+      log(`\n${p.name} gaps:`);
+      for (const g of p.gaps) log(`  ○ ${g}`);
+    }
+  }
+  log("\nPathway 4 (Multi-Agent Collectives) is our architecture.");
+  log("Paper: Genewein et al. 2026. From AGI to ASI. arXiv:2606.12683.\n");
+}
+
+main();

src/upgrades/asi-pathway.ts

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+/**
+ * ASI Pathway Mapper — maps arXiv:2606.12683's four ASI pathways to our system.
+ *
+ * Paper: "From AGI to ASI" — Genewein, Franklin, Lerchner, Orseau, Albanie,
+ *        Bales, Wyeth, Chan, Gabriel, Leibo, Dafoe, Hutter, Graepel, Legg
+ *        (Google DeepMind, June 2026)
+ *
+ * Four pathways from AGI → ASI:
+ *   1. Scaling AGI         — more compute, more data
+ *   2. AI Paradigm Shifts  — new architectures, new algorithms
+ *   3. Recursive Improvement — AI that improves AI
+ *   4. Multi-Agent Collectives — large-scale agent coordination (OUR ARCHITECTURE)
+ *
+ * This module maps each pathway to our existing modules and identifies gaps.
+ */
+
+export interface ASIPathway {
+  id: number;
+  name: string;
+  description: string;
+  ourCoverage: string[];
+  gaps: string[];
+  priority: "high" | "medium" | "low";
+}
+
+export interface ASIAssessment {
+  pathways: ASIPathway[];
+  totalCoverage: number;
+  strongestPathway: string;
+  weakestPathway: string;
+  recommendedFocus: string;
+}
+
+const PATHWAYS: ASIPathway[] = [
+  {
+    id: 1,
+    name: "Scaling AGI",
+    description: "More compute, more data, larger models. The current paradigm.",
+    ourCoverage: [
+      "SafetyBoundary — routes to best available model per task",
+      "CostTracker + CostCap — manages compute budget",
+      "BenchmarkRunner — measures if scaling improves compounding",
+    ],
+    gaps: [
+      "No auto-scaling compute backend (cloud provisioning)",
+      "No model comparison harness (A/B test models on same task)",
+    ],
+    priority: "low",
+  },
+  {
+    id: 2,
+    name: "AI Paradigm Shifts",
+    description: "New architectures, algorithms, or training methods.",
+    ourCoverage: [
+      "13 executors across 5+ model families — adapts to any paradigm",
+      "PhaseExecutor interface — model-agnostic by design",
+      "CompositeExecutor — routes different phases to different architectures",
+    ],
+    gaps: [
+      "No automated architecture discovery",
+      "No paradigm shift detection (when to switch model families)",
+    ],
+    priority: "low",
+  },
+  {
+    id: 3,
+    name: "Recursive Improvement",
+    description: "AI systems that improve AI systems. Self-modifying feedback loops.",
+    ourCoverage: [
+      "DreamingSystem — sleep → review → extract → codify → sharpen",
+      "RoutineEvolution — analyze execution history, auto-suggest improvements",
+      "SkillSharpener — meta-review, quality gate, auto-apply",
+      "FeedbackLoop — plan → execute → observe → reflect → refine",
+      "BenchmarkRunner — measures if improvements are compounding",
+      "HallucinationDetector — catches output degradation",
+    ],
+    gaps: [
+      "No automated weight/architecture modification (not publicly available)",
+      "No meta-learning across skill evolutions (each evolution is independent)",
+    ],
+    priority: "medium",
+  },
+  {
+    id: 4,
+    name: "Multi-Agent Collectives",
+    description: "Large-scale coordination of AI agents achieving collective superintelligence.",
+    ourCoverage: [
+      "MultiAgentOrchestrator — orchestrator → specialists → collect → verify",
+      "AgentTeams — 3-tier: orchestrator → leads → workers",
+      "AgentChains — sequential pipeline: scout → plan → build → review",
+      "KimiExecutor — up to 300 parallel sub-agents natively",
+      "SkillRegistry — shared knowledge across the collective",
+      "PersistentMemory — episodic/semantic/procedural across agents",
+      "SafetyBoundary — routes sub-agents to appropriate models",
+      "DecompositionGuard — detects coordinated multi-agent attacks",
+    ],
+    gaps: [
+      "No emergent behavior detection (when the collective acts unexpectedly)",
+      "No agent specialization optimization (auto-assign roles based on performance)",
+      "No inter-agent communication protocol (agents currently share state, not messages)",
+    ],
+    priority: "high",
+  },
+];
+
+/**
+ * Assess our system's ASI pathway readiness.
+ * Pathway 4 (Multi-Agent Collectives) is our strongest — it's what we architected for.
+ */
+export function assessASIPathways(): ASIAssessment {
+  const sorted = [...PATHWAYS].sort((a, b) => b.ourCoverage.length - a.ourCoverage.length);
+
+  return {
+    pathways: PATHWAYS,
+    totalCoverage: PATHWAYS.reduce((s, p) => s + p.ourCoverage.length, 0),
+    strongestPathway: sorted[0].name,
+    weakestPathway: sorted[sorted.length - 1].name,
+    recommendedFocus: sorted[0].name,
+  };
+}
+
+/** Generate a pathway report card */
+export function pathwayReportCard(): string {
+  const assessment = assessASIPathways();
+  const lines: string[] = [];
+
+  lines.push("╔══════════════════════════════════════════════╗");
+  lines.push("║     ASI Pathway Readiness (arxiv:2606.12683) ║");
+  lines.push("╚══════════════════════════════════════════════╝");
+  lines.push("");
+  lines.push(`Strongest:  ${assessment.strongestPathway}`);
+  lines.push(`Weakest:    ${assessment.weakestPathway}`);
+  lines.push(`Total modules: ${assessment.totalCoverage} across all pathways`);
+  lines.push(`Recommended focus: ${assessment.recommendedFocus}`);
+  lines.push("");
+
+  for (const p of assessment.pathways) {
+    const coverage = p.ourCoverage.length;
+    const gaps = p.gaps.length;
+    const bar = "▓".repeat(Math.min(coverage, 10)) + "░".repeat(Math.max(0, 10 - coverage));
+    lines.push(`[${bar}] Pathway ${p.id}: ${p.name}`);
+    lines.push(`    Coverage: ${coverage} modules, Gaps: ${gaps}`);
+    lines.push("");
+  }
+
+  lines.push("Citation: Genewein et al. (2026). From AGI to ASI. arXiv:2606.12683.");
+  lines.push("DeepMind's fourth pathway — Multi-Agent Collectives — is our architecture.");
+  lines.push("");
+
+  return lines.join("\n");
+}