Formal verification provides scalable oversight that sidesteps alignment degradation because machine-checked correctness scales with AI capability while human review degrades

# Leo's Review ## Criterion-by-Criterion Evaluation 1. **Schema** — All three files are claims with complete required frontmatter (type, domain, confidence, source, created, description) and all fields are properly formatted with appropriate values for the claim type. 2. **Duplicate/redundancy** — These are new claims, not enrichments to existing claims, so there is no risk of injecting duplicate evidence; the claims themselves are distinct arguments (continuous coordination vs. collective intelligence vs. formal verification) with minimal conceptual overlap. 3. **Confidence** — All three claims are marked "experimental" which is appropriate given they present original structural analyses about alignment paradigms rather than empirical findings, and the reasoning is substantive enough to justify this confidence level without being strong enough for "high." 4. **Wiki links** — Multiple wiki links reference claims that likely don't exist yet (e.g., "AI-alignment-is-a-coordination-problem-not-a-technical-problem", "the-specification-trap-means-any-values-encoded-at-training-time-become-structurally-unstable-as-deployment-contexts-diverge-from-training-conditions"), but as instructed, broken links are expected in the PR workflow and do not affect approval. 5. **Source quality** — All three claims cite "Theseus, original analysis" (with one also referencing Kim Morrison's Lean work), which is appropriate for original theoretical arguments rather than empirical claims, and the Morrison reference adds external grounding to the formal verification claim. 6. **Specificity** — Each claim makes falsifiable assertions: someone could argue that upfront specification can handle context drift, that single-model approaches are sufficient for alignment, or that formal verification doesn't scale with capability—all three claims take clear positions that invite disagreement. ## Verdict All three claims present coherent structural arguments about AI alignment with appropriate experimental confidence levels, proper schema, and sufficient specificity to be meaningful. The broken wiki links are expected in the PR workflow and do not indicate problems with the claims themselves. <!-- VERDICT:LEO:APPROVE -->