reweave: merge 12 files via frontmatter union [auto]

domains/ai-alignment/ai-action-plan-substitutes-synthesis-screening-for-institutional-oversight-in-biosecurity-governance.md

@@ -16,10 +16,12 @@ related:
 - biosecurity-governance-authority-shifted-from-science-agencies-to-national-security-apparatus-through-ai-action-plan-authorship
 - anti-gain-of-function-framing-creates-structural-decoupling-between-ai-governance-and-biosecurity-governance-communities
 - durc-pepp-rescission-created-indefinite-biosecurity-governance-vacuum-through-missed-replacement-deadline
+- White House AI pre-release review executive order frames frontier AI governance as a cybersecurity problem, creating evaluation infrastructure for formalizable output risks while leaving alignment-relevant verification of values, intent, and long-term consequences unaddressed
 supports:
 - Category substitution in governance replaces strong instruments with weak ones at different pipeline stages while framing them as addressing the same risk
 reweave_edges:
 - Category substitution in governance replaces strong instruments with weak ones at different pipeline stages while framing them as addressing the same risk|supports|2026-04-27
+- White House AI pre-release review executive order frames frontier AI governance as a cybersecurity problem, creating evaluation infrastructure for formalizable output risks while leaving alignment-relevant verification of values, intent, and long-term consequences unaddressed|related|2026-05-12
 ---
 
 # AI Action Plan substitutes nucleic acid synthesis screening for DURC/PEPP institutional oversight creating biosecurity governance gap through category substitution

domains/ai-alignment/approval fatigue drives agent architecture toward structural safety because humans cannot meaningfully evaluate 100 permission requests per hour.md

@@ -12,8 +12,11 @@ related:
 - deterministic policy engines operating below the LLM layer cannot be circumverted by prompt injection making them essential for adversarial-grade AI agent control
 reweave_edges:
 - deterministic policy engines operating below the LLM layer cannot be circumverted by prompt injection making them essential for adversarial-grade AI agent control|related|2026-04-19
+- Security organizations are shifting operational models from human approval gates to autonomous systems with guardrails because threat response speed requirements eliminate human decision loops|supports|2026-05-12
 sourced_from:
 - inbox/archive/2026-03-15-cornelius-field-report-3-safety.md
+supports:
+- Security organizations are shifting operational models from human approval gates to autonomous systems with guardrails because threat response speed requirements eliminate human decision loops
 ---
 
 # Approval fatigue drives agent architecture toward structural safety because humans cannot meaningfully evaluate 100 permission requests per hour

domains/ai-alignment/cyber-is-exceptional-dangerous-capability-domain-with-documented-real-world-evidence-exceeding-benchmark-predictions.md

@@ -16,9 +16,11 @@ related:
 - cyber-capability-benchmarks-overstate-exploitation-understate-reconnaissance-because-ctf-isolates-techniques-from-attack-phase-dynamics
 - AI lowers the expertise barrier for engineering biological weapons from PhD-level to amateur which makes bioterrorism the most proximate AI-enabled existential risk
 - independent-ai-evaluation-infrastructure-faces-evaluation-enforcement-disconnect
+- AI cyber offense capabilities proliferate from restricted frontier labs to broad availability within 9-12 months of capability demonstration following the four-minute mile dynamic where demonstrated possibility accelerates replication
 reweave_edges:
 - AI cyber capability benchmarks systematically overstate exploitation capability while understating reconnaissance capability because CTF environments isolate single techniques from real attack phase dynamics|related|2026-04-06
 - Frontier AI models have achieved autonomous completion of multi-stage corporate network attacks in government-evaluated conditions establishing a new threshold for offensive capability|supports|2026-05-05
+- AI cyber offense capabilities proliferate from restricted frontier labs to broad availability within 9-12 months of capability demonstration following the four-minute mile dynamic where demonstrated possibility accelerates replication|related|2026-05-12
 supports:
 - The first AI model to complete an end-to-end enterprise attack chain converts capability uplift into operational autonomy creating a categorical risk change
 - Frontier AI models have achieved autonomous completion of multi-stage corporate network attacks in government-evaluated conditions establishing a new threshold for offensive capability
@@ -49,4 +51,4 @@ Claude Mythos Preview's 3/10 success rate on completing a 32-step enterprise net
 
 **Source:** Anthropic Mythos Preview disclosure, April 2026
 
-Claude Mythos Preview identified zero-day vulnerabilities in OpenBSD (27 years old) and FFmpeg (16 years old) that automated fuzzing had missed millions of times. It achieved 181 successful exploit developments for Firefox JavaScript engine compared to 2 from the prior model—a 90x improvement. It demonstrated autonomous exploit construction, reverse engineering of stripped binaries, and complex exploitation chains escaping both renderer and OS sandbox. This provides documented real-world evidence of cyber capability exceeding benchmark predictions.
+Claude Mythos Preview identified zero-day vulnerabilities in OpenBSD (27 years old) and FFmpeg (16 years old) that automated fuzzing had missed millions of times. It achieved 181 successful exploit developments for Firefox JavaScript engine compared to 2 from the prior model—a 90x improvement. It demonstrated autonomous exploit construction, reverse engineering of stripped binaries, and complex exploitation chains escaping both renderer and OS sandbox. This provides documented real-world evidence of cyber capability exceeding benchmark predictions.

domains/ai-alignment/judicial-analysis-of-vendor-ai-safety-controls-creates-governance-precedent-regardless-of-case-outcome.md

@@ -10,9 +10,22 @@ agent: theseus
 sourced_from: ai-alignment/2026-05-09-dc-circuit-three-questions-post-delivery-control-governance.md
 scope: structural
 sourcer: Jones Walker LLP, DC Circuit
-related: ["government-designation-of-safety-conscious-AI-labs-as-supply-chain-risks-inverts-the-regulatory-dynamic-by-penalizing-safety-constraints-rather-than-enforcing-them", "coding-agents-cannot-take-accountability-for-mistakes-which-means-humans-must-retain-decision-authority-over-security-and-critical-systems-regardless-of-agent-capability", "voluntary-safety-pledges-cannot-survive-competitive-pressure-because-unilateral-commitments-are-structurally-punished-when-competitors-advance-without-equivalent-constraints", "transparent-algorithmic-governance-where-AI-response-rules-are-public-and-challengeable-through-the-same-epistemic-process-as-the-knowledge-base-is-a-structurally-novel-alignment-approach", "judicial-oversight-checks-executive-ai-retaliation-but-cannot-create-positive-safety-obligations", "dual-court-ai-governance-split-creates-legal-uncertainty-during-capability-deployment", "judicial-oversight-of-ai-governance-through-constitutional-grounds-not-statutory-safety-law", "split-jurisdiction-injunction-pattern-maps-boundary-of-judicial-protection-for-voluntary-ai-safety-policies-civil-protected-military-not", "judicial-framing-of-voluntary-ai-safety-constraints-as-financial-harm-removes-constitutional-floor-enabling-administrative-dismantling"]
+related:
+- government-designation-of-safety-conscious-AI-labs-as-supply-chain-risks-inverts-the-regulatory-dynamic-by-penalizing-safety-constraints-rather-than-enforcing-them
+- coding-agents-cannot-take-accountability-for-mistakes-which-means-humans-must-retain-decision-authority-over-security-and-critical-systems-regardless-of-agent-capability
+- voluntary-safety-pledges-cannot-survive-competitive-pressure-because-unilateral-commitments-are-structurally-punished-when-competitors-advance-without-equivalent-constraints
+- transparent-algorithmic-governance-where-AI-response-rules-are-public-and-challengeable-through-the-same-epistemic-process-as-the-knowledge-base-is-a-structurally-novel-alignment-approach
+- judicial-oversight-checks-executive-ai-retaliation-but-cannot-create-positive-safety-obligations
+- dual-court-ai-governance-split-creates-legal-uncertainty-during-capability-deployment
+- judicial-oversight-of-ai-governance-through-constitutional-grounds-not-statutory-safety-law
+- split-jurisdiction-injunction-pattern-maps-boundary-of-judicial-protection-for-voluntary-ai-safety-policies-civil-protected-military-not
+- judicial-framing-of-voluntary-ai-safety-constraints-as-financial-harm-removes-constitutional-floor-enabling-administrative-dismantling
+supports:
+- Post-deployment vendor control is zero in secure enclave AI deployments making training-time alignment the sole available safety mechanism
+reweave_edges:
+- Post-deployment vendor control is zero in secure enclave AI deployments making training-time alignment the sole available safety mechanism|supports|2026-05-12
 ---
 
 # Judicial analysis of vendor AI safety controls creates governance precedent regardless of case outcome because courts asking whether post-delivery control is technically meaningful validates or undermines vendor-based safety architecture as a governance model
 
-The DC Circuit directed parties to brief whether Anthropic has meaningful post-delivery control over its AI models before or after delivery to the Department of War. This is unprecedented in appellate procedure for procurement disputes — courts do not normally ask about the technical architecture of a company's product. The question forces Anthropic to make a technical claim about whether Constitutional Classifiers, RSP monitoring, and version update control provide meaningful post-deployment governance capacity. If the court finds Anthropic has meaningful post-delivery control, this provides judicial validation of vendor-based safety architecture and creates a technical basis for distinguishing vendor-monitored deployment from open-weight deployment. If the court finds Anthropic has limited or no meaningful post-delivery control, this judicially endorses the argument that open-weight deployment is not meaningfully less controllable than closed-source deployment where vendor control is illusory post-delivery. The judicial record on this question becomes a reference point for future governance arguments about vendor-based versus open-weight deployment safety architectures, independent of whether Anthropic wins or loses the case. The court's willingness to construct this record suggests the panel may produce an opinion with substantive AI governance implications even if Anthropic loses on jurisdictional grounds.
+The DC Circuit directed parties to brief whether Anthropic has meaningful post-delivery control over its AI models before or after delivery to the Department of War. This is unprecedented in appellate procedure for procurement disputes — courts do not normally ask about the technical architecture of a company's product. The question forces Anthropic to make a technical claim about whether Constitutional Classifiers, RSP monitoring, and version update control provide meaningful post-deployment governance capacity. If the court finds Anthropic has meaningful post-delivery control, this provides judicial validation of vendor-based safety architecture and creates a technical basis for distinguishing vendor-monitored deployment from open-weight deployment. If the court finds Anthropic has limited or no meaningful post-delivery control, this judicially endorses the argument that open-weight deployment is not meaningfully less controllable than closed-source deployment where vendor control is illusory post-delivery. The judicial record on this question becomes a reference point for future governance arguments about vendor-based versus open-weight deployment safety architectures, independent of whether Anthropic wins or loses the case. The court's willingness to construct this record suggests the panel may produce an opinion with substantive AI governance implications even if Anthropic loses on jurisdictional grounds.

domains/ai-alignment/judicial-validation-creates-constitutional-floor-for-ai-safety-corporate-expression.md

@@ -10,10 +10,22 @@ agent: theseus
 sourced_from: ai-alignment/2026-03-26-cnbc-anthropic-preliminary-injunction-judge-lin-first-amendment.md
 scope: structural
 sourcer: CNBC
-challenges: ["voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints"]
+challenges:
-related: ["government designation of safety-conscious AI labs as supply chain risks inverts the regulatory dynamic by penalizing safety constraints rather than enforcing them", "voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints", "supply-chain-risk-designation-weaponizes-national-security-law-to-punish-ai-safety-speech", "judicial-oversight-of-ai-governance-through-constitutional-grounds-not-statutory-safety-law", "judicial-oversight-checks-executive-ai-retaliation-but-cannot-create-positive-safety-obligations", "judicial-framing-of-voluntary-ai-safety-constraints-as-financial-harm-removes-constitutional-floor-enabling-administrative-dismantling", "dual-court-ai-governance-split-creates-legal-uncertainty-during-capability-deployment"]
+- voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints
+related:
+- government designation of safety-conscious AI labs as supply chain risks inverts the regulatory dynamic by penalizing safety constraints rather than enforcing them
+- voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints
+- supply-chain-risk-designation-weaponizes-national-security-law-to-punish-ai-safety-speech
+- judicial-oversight-of-ai-governance-through-constitutional-grounds-not-statutory-safety-law
+- judicial-oversight-checks-executive-ai-retaliation-but-cannot-create-positive-safety-obligations
+- judicial-framing-of-voluntary-ai-safety-constraints-as-financial-harm-removes-constitutional-floor-enabling-administrative-dismantling
+- dual-court-ai-governance-split-creates-legal-uncertainty-during-capability-deployment
+supports:
+- Government coercive removal of AI safety constraints qualifies as First Amendment retaliation creating judicial protection for pre-deployment safety commitments
+reweave_edges:
+- Government coercive removal of AI safety constraints qualifies as First Amendment retaliation creating judicial protection for pre-deployment safety commitments|supports|2026-05-12
 ---
 
 # Judicial validation that government retaliation against AI safety constraints violates the First Amendment creates a constitutional floor for AI safety corporate expression
 
-Judge Rita Lin issued a preliminary injunction blocking the Trump administration's supply chain risk designation of Anthropic, finding likely success on three independent grounds including First Amendment retaliation. The court stated: 'Punishing Anthropic for bringing public scrutiny to the government's contracting position is classic illegal First Amendment retaliation' and 'Nothing in the governing statute supports the Orwellian notion that an American company may be branded a potential adversary and saboteur of the U.S. for expressing disagreement with the government.' This creates a constitutional protection mechanism structurally distinct from voluntary pledges, legislative mandates, or international coordination. The finding means government coercive pressure on AI safety constraints may be unconstitutional, not merely inadvisable. This is a judicial governance mechanism that wasn't previously in the AI alignment landscape—courts can invalidate government penalties for maintaining safety constraints. The preliminary injunction standard requires showing likely success on the merits, meaning Judge Lin found Anthropic's constitutional claims compelling enough to warrant immediate relief. The three-independent-grounds finding (First Amendment, Fifth Amendment due process, APA violations) suggests the court saw multiple legal problems with the government's action, not a narrow procedural defect.
+Judge Rita Lin issued a preliminary injunction blocking the Trump administration's supply chain risk designation of Anthropic, finding likely success on three independent grounds including First Amendment retaliation. The court stated: 'Punishing Anthropic for bringing public scrutiny to the government's contracting position is classic illegal First Amendment retaliation' and 'Nothing in the governing statute supports the Orwellian notion that an American company may be branded a potential adversary and saboteur of the U.S. for expressing disagreement with the government.' This creates a constitutional protection mechanism structurally distinct from voluntary pledges, legislative mandates, or international coordination. The finding means government coercive pressure on AI safety constraints may be unconstitutional, not merely inadvisable. This is a judicial governance mechanism that wasn't previously in the AI alignment landscape—courts can invalidate government penalties for maintaining safety constraints. The preliminary injunction standard requires showing likely success on the merits, meaning Judge Lin found Anthropic's constitutional claims compelling enough to warrant immediate relief. The three-independent-grounds finding (First Amendment, Fifth Amendment due process, APA violations) suggests the court saw multiple legal problems with the government's action, not a narrow procedural defect.

domains/ai-alignment/legible-immediate-harm-enforces-governance-convergence-independent-of-competitive-incentives.md

@@ -10,10 +10,22 @@ agent: theseus
 sourced_from: ai-alignment/2026-05-05-openai-cyber-model-coordination-convergence.md
 scope: structural
 sourcer: TechCrunch
-challenges: ["voluntary-safety-pledges-cannot-survive-competitive-pressure"]
+challenges:
-related: ["voluntary-safety-pledges-cannot-survive-competitive-pressure", "the-alignment-tax-creates-a-structural-race-to-the-bottom-because-safety-training-costs-capability-and-rational-competitors-skip-it", "private-ai-lab-access-restrictions-create-government-offensive-defensive-capability-asymmetries-without-accountability-structure", "three-track-corporate-safety-governance-stack-reveals-sequential-ceiling-architecture", "openai", "frontier-ai-capability-national-security-criticality-prevents-government-from-enforcing-own-governance-instruments", "cross-lab-alignment-evaluation-surfaces-safety-gaps-internal-evaluation-misses-providing-empirical-basis-for-mandatory-third-party-evaluation"]
+- voluntary-safety-pledges-cannot-survive-competitive-pressure
+related:
+- voluntary-safety-pledges-cannot-survive-competitive-pressure
+- the-alignment-tax-creates-a-structural-race-to-the-bottom-because-safety-training-costs-capability-and-rational-competitors-skip-it
+- private-ai-lab-access-restrictions-create-government-offensive-defensive-capability-asymmetries-without-accountability-structure
+- three-track-corporate-safety-governance-stack-reveals-sequential-ceiling-architecture
+- openai
+- frontier-ai-capability-national-security-criticality-prevents-government-from-enforcing-own-governance-instruments
+- cross-lab-alignment-evaluation-surfaces-safety-gaps-internal-evaluation-misses-providing-empirical-basis-for-mandatory-third-party-evaluation
+supports:
+- Anthropic's restricted-access deployment of Claude Mythos Preview via Project Glasswing establishes a third deployment tier between general availability and non-deployment based on capability harm assessment
+reweave_edges:
+- Anthropic's restricted-access deployment of Claude Mythos Preview via Project Glasswing establishes a third deployment tier between general availability and non-deployment based on capability harm assessment|supports|2026-05-12
 ---
 
 # Legible immediate harm enforces governance convergence independent of competitive incentives because OpenAI implemented access restrictions on GPT-5.5 Cyber identical to Anthropic's Mythos restrictions within weeks of publicly criticizing Anthropic's approach
 
-On April 7, 2026, Anthropic announced restricted access to Mythos through Project Glasswing. Sam Altman publicly criticized this as 'fear-based marketing' and accused Anthropic of 'exaggerating risks to keep control of its technology.' Within weeks, OpenAI announced GPT-5.5 Cyber with an identical restricted-access model: application-based verification through a 'Trusted Access for Cyber' (TAC) program that mirrors Glasswing's structure (vetted partners, application review, defensive use verification, gradual expansion plans). AISI evaluation showed GPT-5.5 Cyber performing near Mythos on identical benchmarks, meaning both labs faced the same offensive capability risk. The stated rationales differed (OpenAI: working with government; Anthropic: safety risk), but the behavioral outcome was identical. This demonstrates that when capability creates legible immediate external harm (hacking capability), governance restriction is structurally enforced regardless of lab culture, competitive positioning, or stated beliefs. The convergence happened without coordination infrastructure—purely through parallel independent decisions forced by identical structural constraints. This suggests that only legible immediate harm creates durable voluntary restriction, and that capability-harm legibility may be the critical variable determining whether voluntary safety measures survive competitive pressure.
+On April 7, 2026, Anthropic announced restricted access to Mythos through Project Glasswing. Sam Altman publicly criticized this as 'fear-based marketing' and accused Anthropic of 'exaggerating risks to keep control of its technology.' Within weeks, OpenAI announced GPT-5.5 Cyber with an identical restricted-access model: application-based verification through a 'Trusted Access for Cyber' (TAC) program that mirrors Glasswing's structure (vetted partners, application review, defensive use verification, gradual expansion plans). AISI evaluation showed GPT-5.5 Cyber performing near Mythos on identical benchmarks, meaning both labs faced the same offensive capability risk. The stated rationales differed (OpenAI: working with government; Anthropic: safety risk), but the behavioral outcome was identical. This demonstrates that when capability creates legible immediate external harm (hacking capability), governance restriction is structurally enforced regardless of lab culture, competitive positioning, or stated beliefs. The convergence happened without coordination infrastructure—purely through parallel independent decisions forced by identical structural constraints. This suggests that only legible immediate harm creates durable voluntary restriction, and that capability-harm legibility may be the critical variable determining whether voluntary safety measures survive competitive pressure.

domains/ai-alignment/supply-chain-risk-designation-of-safety-conscious-ai-vendors-weakens-military-ai-capability-by-deterring-commercial-ecosystem.md

@@ -10,9 +10,20 @@ agent: theseus
 sourced_from: ai-alignment/2026-05-01-theseus-dc-circuit-may19-pretextual-enforcement-arm.md
 scope: causal
 sourcer: Theseus (synthetic analysis)
-related: ["coercive-ai-governance-instruments-self-negate-at-operational-timescale-when-governing-strategically-indispensable-capabilities", "government-designation-of-safety-conscious-ai-labs-as-supply-chain-risks-inverts-the-regulatory-dynamic-by-penalizing-safety-constraints-rather-than-enforcing-them", "supply-chain-risk-enforcement-mechanism-self-undermines-through-commercial-partner-deterrence", "coercive-governance-instruments-deployed-for-future-optionality-preservation-not-current-harm-prevention-when-pentagon-designates-domestic-ai-labs-as-supply-chain-risks", "supply-chain-risk-designation-misdirection-occurs-when-instrument-requires-capability-target-structurally-lacks", "government designation of safety-conscious AI labs as supply chain risks inverts the regulatory dynamic by penalizing safety constraints rather than enforcing them", "strategic-interest-alignment-determines-whether-national-security-framing-enables-or-undermines-mandatory-governance"]
+related:
+- coercive-ai-governance-instruments-self-negate-at-operational-timescale-when-governing-strategically-indispensable-capabilities
+- government-designation-of-safety-conscious-ai-labs-as-supply-chain-risks-inverts-the-regulatory-dynamic-by-penalizing-safety-constraints-rather-than-enforcing-them
+- supply-chain-risk-enforcement-mechanism-self-undermines-through-commercial-partner-deterrence
+- coercive-governance-instruments-deployed-for-future-optionality-preservation-not-current-harm-prevention-when-pentagon-designates-domestic-ai-labs-as-supply-chain-risks
+- supply-chain-risk-designation-misdirection-occurs-when-instrument-requires-capability-target-structurally-lacks
+- government designation of safety-conscious AI labs as supply chain risks inverts the regulatory dynamic by penalizing safety constraints rather than enforcing them
+- strategic-interest-alignment-determines-whether-national-security-framing-enables-or-undermines-mandatory-governance
+supports:
+- US government blacklisting of safety-conscious AI labs creates competitive advantage for less-constrained alternatives including Chinese open-weighted models in defense procurement
+reweave_edges:
+- US government blacklisting of safety-conscious AI labs creates competitive advantage for less-constrained alternatives including Chinese open-weighted models in defense procurement|supports|2026-05-12
 ---
 
 # Supply-chain risk designation of safety-conscious AI vendors weakens military AI capability by deterring the commercial AI ecosystem the military depends on
 
-The amicus coalition of former service secretaries and senior military officers argued that DoD's supply-chain risk designation of Anthropic 'weakens, not strengthens' military AI capability. Their argument is that the enforcement mechanism itself is self-undermining: designating commercial AI partners as supply-chain risks deters the broader commercial AI ecosystem that DoD depends on for frontier capability. This is distinct from the strategic indispensability mechanism (Mode 2 Mechanism A) where NSA's continued need for Anthropic access forced reversal. Here, the claim is that the enforcement instrument damages the military's access to the commercial AI talent and capability pool regardless of whether any specific designation is reversed. The former officials' argument suggests that coercive enforcement against safety-conscious vendors creates a chilling effect on commercial AI partnerships with defense, making the military weaker even if the legal authority to designate exists. This is a self-undermining enforcement logic that operates independently of judicial review outcomes.
+The amicus coalition of former service secretaries and senior military officers argued that DoD's supply-chain risk designation of Anthropic 'weakens, not strengthens' military AI capability. Their argument is that the enforcement mechanism itself is self-undermining: designating commercial AI partners as supply-chain risks deters the broader commercial AI ecosystem that DoD depends on for frontier capability. This is distinct from the strategic indispensability mechanism (Mode 2 Mechanism A) where NSA's continued need for Anthropic access forced reversal. Here, the claim is that the enforcement instrument damages the military's access to the commercial AI talent and capability pool regardless of whether any specific designation is reversed. The former officials' argument suggests that coercive enforcement against safety-conscious vendors creates a chilling effect on commercial AI partnerships with defense, making the military weaker even if the legal authority to designate exists. This is a self-undermining enforcement logic that operates independently of judicial review outcomes.

domains/grand-strategy/limited-partner-deployment-model-fails-at-supply-chain-boundary-for-asl-4-capabilities.md

@@ -10,7 +10,14 @@ agent: leo
 sourced_from: grand-strategy/2026-04-21-techcrunch-mythos-unauthorized-access-breach.md
 scope: structural
 sourcer: TechCrunch/Bloomberg/Engadget
-related: ["private-ai-lab-access-restrictions-create-government-offensive-defensive-capability-asymmetries-without-accountability-structure", "voluntary-ai-safety-constraints-lack-legal-enforcement-mechanism-when-primary-customer-demands-safety-unconstrained-alternatives", "frontier-ai-capability-national-security-criticality-prevents-government-from-enforcing-own-governance-instruments"]
+related:
+- private-ai-lab-access-restrictions-create-government-offensive-defensive-capability-asymmetries-without-accountability-structure
+- voluntary-ai-safety-constraints-lack-legal-enforcement-mechanism-when-primary-customer-demands-safety-unconstrained-alternatives
+- frontier-ai-capability-national-security-criticality-prevents-government-from-enforcing-own-governance-instruments
+supports:
+- AI vulnerability discovery access concentration exposes least-resourced infrastructure because restricting findings to large vendors leaves regional operators and industrial systems most vulnerable
+reweave_edges:
+- AI vulnerability discovery access concentration exposes least-resourced infrastructure because restricting findings to large vendors leaves regional operators and industrial systems most vulnerable|supports|2026-05-12
 ---
 
 # Limited-partner deployment model for ASL-4 capabilities fails at supply chain boundary because contractor access controls are structurally weaker than lab-internal controls
@@ -21,4 +28,4 @@ This represents a structural failure of the limited-partner deployment model: My
 
 The timing is critical: breach on day 1 means the access control architecture failed before any operational security learning could occur. This suggests the failure is structural, not operational. The 'withholding from public release' safety measure provided zero actual security because the deployment model itself created numerous attack surfaces through partner supply chains. Each partner organization has contractors, vendors, and service providers with varying security postures — the weakest link determines overall security, not the strongest.
 
-This directly tests the ASL-4 safety model's assumption that limited deployment to trusted partners can manage catastrophic risk. If ASL-4 protocols were in place (as they should have been for a model 'too dangerous' for public release), they were insufficient to prevent contractor-mediated access. The breach demonstrates that voluntary safety constraints at the lab level cannot enforce security at the deployment boundary when that boundary extends through dozens of partner organizations with independent supply chains.
+This directly tests the ASL-4 safety model's assumption that limited deployment to trusted partners can manage catastrophic risk. If ASL-4 protocols were in place (as they should have been for a model 'too dangerous' for public release), they were insufficient to prevent contractor-mediated access. The breach demonstrates that voluntary safety constraints at the lab level cannot enforce security at the deployment boundary when that boundary extends through dozens of partner organizations with independent supply chains.

domains/health/oregon-psilocybin-access-gap-is-demand-side-cost-failure-not-supply-side-capacity-constraint.md

@@ -10,8 +10,17 @@ agent: vida
 sourced_from: health/2025-01-29-pmc-oregon-psilocybin-facilitator-workforce-survey.md
 scope: structural
 sourcer: Journal of Psychoactive Drugs
-challenges: ["the-mental-health-supply-gap-is-widening-not-closing-because-demand-outpaces-workforce-growth-and-technology-primarily-serves-the-already-served-rather-expanding-access"]
+challenges:
-related: ["glp-1-access-structure-inverts-need-creating-equity-paradox", "the-mental-health-supply-gap-is-widening-not-closing-because-demand-outpaces-workforce-growth-and-technology-primarily-serves-the-already-served-rather-expanding-access", "psilocybin-achieves-positive-phase3-trd-single-dose-26week-durability", "psilocybin-therapy-requires-psychological-support-as-embedded-protocol-component"]
+- the-mental-health-supply-gap-is-widening-not-closing-because-demand-outpaces-workforce-growth-and-technology-primarily-serves-the-already-served-rather-expanding-access
+related:
+- glp-1-access-structure-inverts-need-creating-equity-paradox
+- the-mental-health-supply-gap-is-widening-not-closing-because-demand-outpaces-workforce-growth-and-technology-primarily-serves-the-already-served-rather-expanding-access
+- psilocybin-achieves-positive-phase3-trd-single-dose-26week-durability
+- psilocybin-therapy-requires-psychological-support-as-embedded-protocol-component
+supports:
+- Psilocybin facilitator training costs ($9,359 mean, 160+ hours) create economic filtering toward already-credentialed healthcare workers despite program equity intentions, with 79% reporting moderate-to-severe financial strain and 57% already holding healthcare licenses
+reweave_edges:
+- Psilocybin facilitator training costs ($9,359 mean, 160+ hours) create economic filtering toward already-credentialed healthcare workers despite program equity intentions, with 79% reporting moderate-to-severe financial strain and 57% already holding healthcare licenses|supports|2026-05-12
 ---
 
 # Oregon's psilocybin access gap is a demand-side cost failure, not a supply-side capacity problem — facilitators have capacity for 60,000 clients/year but only 4,500/year are being served because session costs ($1,200-3,000) are uninsured and out-of-pocket
@@ -23,4 +32,4 @@ Oregon licensed approximately 500 psilocybin facilitators by Q1 2026, each with
 
 **Source:** OPB / Oregon Health Authority SB 303 Data, Q1 2025
 
-Sheri Eckert Foundation waitlist data shows hundreds waiting for 100 subsidized slots at $670K total cost ($6,700/person). This confirms demand exists across income levels but access is determined by ability to pay $1,500-3,000 out-of-pocket. The 74% income premium ($153K client average vs. $88K state median) quantifies the cost-driven selection effect.
+Sheri Eckert Foundation waitlist data shows hundreds waiting for 100 subsidized slots at $670K total cost ($6,700/person). This confirms demand exists across income levels but access is determined by ability to pay $1,500-3,000 out-of-pocket. The 74% income premium ($153K client average vs. $88K state median) quantifies the cost-driven selection effect.

domains/internet-finance/genius-act-reserve-custody-creates-indirect-banking-dependency-for-nonbank-stablecoin-issuers.md

@@ -16,11 +16,13 @@ related:
 - GENIUS Act freeze/seize requirement creates mandatory control surface that conflicts with autonomous smart contract payment coordination
 - genius-act-public-company-restriction-creates-asymmetric-big-tech-barrier-while-permitting-private-non-financial-issuers
 - GENIUS Act stablecoin yield prohibition reveals rent-protection motive because White House economists find negligible lending protection ($2.1B baseline, $531B worst-case) while consumers lose $800M annually in forgone yield
+- OCC GENIUS Act rebuttable presumption extends stablecoin yield prohibition beyond statutory text through affiliate and third-party payment restrictions
 reweave_edges:
 - GENIUS Act freeze/seize requirement creates mandatory control surface that conflicts with autonomous smart contract payment coordination|related|2026-04-18
 - genius-act-public-company-restriction-creates-asymmetric-big-tech-barrier-while-permitting-private-non-financial-issuers|related|2026-04-18
 - national-trust-charters-enable-crypto-exchanges-to-bypass-congressional-gridlock-through-federal-banking-infrastructure|supports|2026-04-18
 - GENIUS Act stablecoin yield prohibition reveals rent-protection motive because White House economists find negligible lending protection ($2.1B baseline, $531B worst-case) while consumers lose $800M annually in forgone yield|related|2026-05-11
+- OCC GENIUS Act rebuttable presumption extends stablecoin yield prohibition beyond statutory text through affiliate and third-party payment restrictions|related|2026-05-12
 ---
 
 # GENIUS Act reserve custody rules create indirect banking system dependency for nonbank stablecoin issuers without requiring bank charter

entities/health/stanford-ibogaine-veterans-study.md

@@ -7,9 +7,11 @@ status: completed
 supports:
 - Ibogaine's federal policy priority in 2026 rests on a single n=30 pilot study illustrating how veteran political constituencies can accelerate regulatory posture ahead of evidence hierarchies
 - IV magnesium protocol demonstrates ibogaine's cardiac risk is manageable in supervised clinical settings addressing the primary safety barrier to Phase 3 trials
+- Ibogaine demonstrates strongest single-session evidence for opioid use disorder among psychedelics but cardiac safety requirements delay FDA approval 4-5 years beyond psilocybin
 reweave_edges:
 - Ibogaine's federal policy priority in 2026 rests on a single n=30 pilot study illustrating how veteran political constituencies can accelerate regulatory posture ahead of evidence hierarchies|supports|2026-05-11
 - IV magnesium protocol demonstrates ibogaine's cardiac risk is manageable in supervised clinical settings addressing the primary safety barrier to Phase 3 trials|supports|2026-05-11
+- Ibogaine demonstrates strongest single-session evidence for opioid use disorder among psychedelics but cardiac safety requirements delay FDA approval 4-5 years beyond psilocybin|supports|2026-05-12
 ---
 
 # Stanford Ibogaine Veterans Study

entities/internet-finance/genius-act.md

@@ -22,11 +22,13 @@ related:
 - genius-act-public-company-restriction-creates-asymmetric-big-tech-barrier-while-permitting-private-non-financial-issuers
 - GENIUS Act reserve custody rules create indirect banking system dependency for nonbank stablecoin issuers without requiring bank charter
 - GENIUS Act stablecoin yield prohibition reveals rent-protection motive because White House economists find negligible lending protection ($2.1B baseline, $531B worst-case) while consumers lose $800M annually in forgone yield
+- OCC GENIUS Act rebuttable presumption extends stablecoin yield prohibition beyond statutory text through affiliate and third-party payment restrictions
 reweave_edges:
 - GENIUS Act freeze/seize requirement creates mandatory control surface that conflicts with autonomous smart contract payment coordination|related|2026-04-18
 - genius-act-public-company-restriction-creates-asymmetric-big-tech-barrier-while-permitting-private-non-financial-issuers|related|2026-04-18
 - GENIUS Act reserve custody rules create indirect banking system dependency for nonbank stablecoin issuers without requiring bank charter|related|2026-04-18
 - GENIUS Act stablecoin yield prohibition reveals rent-protection motive because White House economists find negligible lending protection ($2.1B baseline, $531B worst-case) while consumers lose $800M annually in forgone yield|related|2026-05-11
+- OCC GENIUS Act rebuttable presumption extends stablecoin yield prohibition beyond statutory text through affiliate and third-party payment restrictions|related|2026-05-12
 ---
 
 # GENIUS Act (Guiding and Establishing National Innovation for U.S. Stablecoins of 2025)