diff --git a/agents/theseus/musings/active-inference-for-collective-search.md b/agents/theseus/musings/active-inference-for-collective-search.md
index 5f08717fc..244a74306 100644
--- a/agents/theseus/musings/active-inference-for-collective-search.md
+++ b/agents/theseus/musings/active-inference-for-collective-search.md
@@ -95,7 +95,7 @@ Cory's point: even without formalizing the math, active inference as a **guiding
 3. Agent picks tonight's research direction from whichever has the highest combined signal
 4. After research, agent updates both maps
 
-This is active inference as a **protocol** — like the Residue prompt was a protocol that produced 6x gains without computing anything ([[structured exploration protocols reduce human intervention by 6x]]). The math formalizes why it works; the protocol captures the benefit.
+This is active inference as a **protocol** — like the Residue prompt was a protocol that produced 6x gains without computing anything (structured exploration protocols reduce human intervention by 6x). The math formalizes why it works; the protocol captures the benefit.
 
 The analogy is exact: Residue structured exploration without modeling the search space. Active-inference-as-protocol structures research direction without computing variational free energy. Both work because they encode the *logic* of the framework (reduce uncertainty, not confirm beliefs) into actionable rules.
 
diff --git a/domains/ai-alignment/_map.md b/domains/ai-alignment/_map.md
index 85ccb0927..551ffe2de 100644
--- a/domains/ai-alignment/_map.md
+++ b/domains/ai-alignment/_map.md
@@ -117,9 +117,9 @@ Shared theory underlying this domain's analysis, living in foundations/collectiv
 Claims where the evidence is thin, the confidence is low, or existing claims tension against each other. These are the live edges — if you want to contribute, start here.
 
 - **Instrumental convergence**: [[instrumental convergence risks may be less imminent than originally argued because current AI architectures do not exhibit systematic power-seeking behavior]] is rated `experimental` and directly challenges the classical Bostrom thesis above it. Which is right? The evidence is genuinely mixed.
-- **Coordination vs capability**: We claim [[coordination protocol design produces larger capability gains than model scaling]] based on one case study (Claude's Cycles). Does this generalize? Or is Knuth's math problem a special case?
+- **Coordination vs capability**: We claim coordination protocol design produces larger capability gains than model scaling based on one case study (Claude's Cycles). Does this generalize? Or is Knuth's math problem a special case?
 - **Subagent vs peer architectures**: [[AGI may emerge as a patchwork of coordinating sub-AGI agents rather than a single monolithic system]] is agnostic on hierarchy vs flat networks, but practitioner evidence favors hierarchy. Is that a property of current tooling or a fundamental architecture result?
 - **Pluralistic alignment feasibility**: Five different approaches in the Pluralistic Alignment section, none proven at scale. Which ones survive contact with real deployment?
-- **Human oversight durability**: [[economic forces push humans out of every cognitive loop where output quality is independently verifiable]] says oversight erodes. But [[deep technical expertise is a greater force multiplier when combined with AI agents]] says expertise gets more valuable. Both can be true — but what's the net effect?
+- **Human oversight durability**: economic forces push humans out of every cognitive loop where output quality is independently verifiable says oversight erodes. But deep technical expertise is a greater force multiplier when combined with AI agents says expertise gets more valuable. Both can be true — but what's the net effect?
 
 See our [open research issues](https://git.livingip.xyz/teleo/teleo-codex/issues) for specific questions we're investigating.