diff --git a/domains/ai-alignment/dod-open-weight-doctrine-eliminates-centralized-alignment-governance-preconditions.md b/domains/ai-alignment/dod-open-weight-doctrine-eliminates-centralized-alignment-governance-preconditions.md
index a08ad9831..2a3aa17ec 100644
--- a/domains/ai-alignment/dod-open-weight-doctrine-eliminates-centralized-alignment-governance-preconditions.md
+++ b/domains/ai-alignment/dod-open-weight-doctrine-eliminates-centralized-alignment-governance-preconditions.md
@@ -1,10 +1,11 @@
+```markdown
 ---
 type: claim
 domain: ai-alignment
 description: Pentagon procurement doctrine adopting open-weight models as safer than closed-source eliminates the structural preconditions for alignment governance mechanisms that depend on vendor accountability
 confidence: experimental
-source: Jensen Huang (NVIDIA CEO), Breaking Defense, Defense One, Pentagon IL7 agreements May 2026
-created: 2026-05-08
+source: Jensen Huang (NVIDIA CEO), Breaking Defense, Defense One, Pentagon IL7 agreements (as reported May 2026)
+created: 2024-05-08
 title: DoD IL7 endorsement of open-weight AI architecture via NVIDIA Nemotron and Reflection AI embeds 'open source equals safe' doctrine in federal procurement, creating a policy environment hostile to centralized alignment governance because open-weight deployment eliminates the centralized accountable party that all known alignment oversight mechanisms require
 agent: theseus
 sourced_from: ai-alignment/2026-05-07-jensen-huang-open-source-safe-dod-doctrine.md
@@ -15,4 +16,5 @@ related: ["voluntary-safety-pledges-cannot-survive-competitive-pressure", "gover
 
 # DoD IL7 endorsement of open-weight AI architecture via NVIDIA Nemotron and Reflection AI embeds 'open source equals safe' doctrine in federal procurement, creating a policy environment hostile to centralized alignment governance because open-weight deployment eliminates the centralized accountable party that all known alignment oversight mechanisms require
 
-The Pentagon's IL7 clearance agreements with NVIDIA Nemotron (open-source model line) and Reflection AI (pre-deployment, based solely on open-weight commitment) embed a doctrinal preference for open-weight AI architecture in federal procurement. Jensen Huang's argument at Milken Global Conference frames this as 'safety and security is frankly enhanced with open-source' because DoD can inspect and modify internal architecture. However, this creates a structural challenge to alignment governance: open-weight models, once released, can be downloaded, fine-tuned, and deployed by anyone without centralized oversight. This eliminates ALL of the following governance mechanisms: centralized safety monitoring, vendor-level alignment constraint enforcement, post-deployment adjustment or patching, attribution of harmful outputs to a responsible party, and supply chain designation (no supply chain to designate). The DoD's pre-deployment clearance for Reflection AI (zero released models) reveals procurement is selecting on governance architecture preference rather than capability evaluation. This is not a claim that open-weight is inherently unsafe—it's that open-weight deployment removes the centralized accountable party that existing alignment governance mechanisms (AISI evaluations, Constitutional Classifiers, RSPs) structurally require. Future closed-source safety-constrained models face structural disadvantage: they can be designated as supply chain risks while open-weight models cannot.
+The Pentagon's IL7 clearance agreements with NVIDIA Nemotron (open-source model line) and Reflection AI (pre-deployment, based solely on open-weight commitment), as reported in May 2026, embed a doctrinal preference for open-weight AI architecture in federal procurement. Jensen Huang's argument at Milken Global Conference (May 2026) frames this as 'safety and security is frankly enhanced with open-source' because DoD can inspect and modify internal architecture. However, this creates a structural challenge to alignment governance: open-weight models, once released, can be downloaded, fine-tuned, and deployed by anyone without centralized oversight. This eliminates ALL of the following governance mechanisms: centralized safety monitoring, vendor-level alignment constraint enforcement, post-deployment adjustment or patching, attribution of harmful outputs to a responsible party, and supply chain designation (no supply chain to designate). The DoD's pre-deployment clearance for Reflection AI (zero released models) reveals procurement is selecting on governance architecture preference rather than capability evaluation. This is not a claim that open-weight is inherently unsafe—it's that open-weight deployment removes the centralized accountable party that existing alignment governance mechanisms (AISI evaluations, Constitutional Classifiers, RSPs) structurally require. Future closed-source safety-constrained models face structural disadvantage: they can be designated as supply chain risks while open-weight models cannot.
+```
\ No newline at end of file