diff --git a/ext/TensorKitEnzymeExt/TensorKitEnzymeExt.jl b/ext/TensorKitEnzymeExt/TensorKitEnzymeExt.jl
index 98bc70c40..cadae496a 100644
--- a/ext/TensorKitEnzymeExt/TensorKitEnzymeExt.jl
+++ b/ext/TensorKitEnzymeExt/TensorKitEnzymeExt.jl
@@ -11,21 +11,6 @@ using MatrixAlgebraKit
 using TupleTools
 using Random: AbstractRNG
 
-"""
-    is_inactive(config, x::Annotation) -> Bool
-
-Check whether the annotated argument `x` should be treated as inactive, i.e. whether no tangent should be read from or accumulated into `x.dval`.
-Under runtime activity, Enzyme may pass an argument that is inactive at run time as a `Duplicated` whose shadow aliases the primal (`x.dval === x.val`);
-writing into that shadow would then corrupt the primal.
-See https://enzymead.github.io/Enzyme.jl/dev/faq/#faq-runtime-activity.
-
-!!! note
-    This is a stopgap until an equivalent helper is available in `EnzymeRules`
-    (see https://github.com/EnzymeAD/Enzyme.jl/pull/3597#discussion_r4014313289).
-"""
-@inline is_inactive(config, ::Const) = true
-@inline is_inactive(config, x::Annotation) = EnzymeRules.runtime_activity(config) && x.dval === x.val
-
 include("utility.jl")
 include("linalg.jl")
 include("indexmanipulations.jl")
diff --git a/ext/TensorKitEnzymeExt/tensoroperations.jl b/ext/TensorKitEnzymeExt/tensoroperations.jl
index 6b80fd26e..8d6652ba7 100644
--- a/ext/TensorKitEnzymeExt/tensoroperations.jl
+++ b/ext/TensorKitEnzymeExt/tensoroperations.jl
@@ -22,10 +22,10 @@ function EnzymeRules.augmented_primal(
         backend::Const,
         allocator::Const
     ) where {RT}
-    Ccache = isa(β, Const) || is_inactive(config, C) ? nothing : copy(C.val)
-    A_needs_cache = EnzymeRules.overwritten(config)[3] && !(typeof(B) <: Const) && !(typeof(C) <: Const) && !is_inactive(config, A)
+    Ccache = isa(β, Const) ? nothing : copy(C.val)
+    A_needs_cache = EnzymeRules.overwritten(config)[3] && !(typeof(B) <: Const) && !(typeof(C) <: Const)
     Acache = A_needs_cache ? copy(A.val) : nothing
-    B_needs_cache = EnzymeRules.overwritten(config)[5] && !(typeof(A) <: Const) && !(typeof(C) <: Const) && !is_inactive(config, B)
+    B_needs_cache = EnzymeRules.overwritten(config)[5] && !(typeof(A) <: Const) && !(typeof(C) <: Const)
     Bcache = B_needs_cache ? copy(B.val) : nothing
     AB = if !isa(α, Const)
         AB = TO.tensorcontract(A.val, pA.val, false, B.val, pB.val, false, pAB.val, One(), backend.val, allocator.val)
@@ -65,17 +65,17 @@ function EnzymeRules.reverse(
     Δα = pullback_dα(α, C, AB)
     Δβ = pullback_dβ(β, C, Cval)
 
-    if !is_inactive(A) && !is_inactive(C)
+    if !isa(A, Const)
         TensorKit.blas_contract_pullback_ΔA!(
             A.dval, C.dval, Aval, pA.val, Bval, pB.val, pAB.val, α.val, backend.val, allocator.val
         ) # this typically returns nothing
     end
-    if !is_inactive(B) && !is_inactive(C)
+    if !isa(B, Const)
         TensorKit.blas_contract_pullback_ΔB!(
             B.dval, C.dval, Aval, pA.val, Bval, pB.val, pAB.val, α.val, backend.val, allocator.val
         ) # this typically returns nothing
     end
-    !is_inactive(C) && pullback_dC!(C.dval, β.val) # this typically returns nothing
+    !isa(C, Const) && pullback_dC!(C.dval, β.val) # this typically returns nothing
     return nothing, nothing, nothing, nothing, nothing, nothing, Δα, Δβ, nothing, nothing
 end