diff --git a/docs/src/man/automatic_differentiation.md b/docs/src/man/automatic_differentiation.md
index a09c91b6..df43a993 100644
--- a/docs/src/man/automatic_differentiation.md
+++ b/docs/src/man/automatic_differentiation.md
@@ -93,6 +93,31 @@ julia> norm(majorsymmetric(E) - E_sym)
 0.0
 ```
 
+## Differentiating mutating functions
+Some applications require the derivative of the output of a function `f(x,s)`, 
+wrt. `x`, where `f` also mutates `s`. 
+In these cases, we don't want the derivative of `s` wrt. `x`, and 
+the value to be set in `s` should only be the value and not be the dual part.
+For scalars, `ForwardDiff.jl` provides `ForwardDiff.value`,
+and for tensors, `Tensors.jl` provides `Tensors.extract_value`. 
+
+```@docs
+Tensors.extract_value
+```
+
+A simple example of the use-case is 
+```@example
+function mutating_fun(x::Vec, state::Vector)
+    state[1] = Tensors.extract_value(x)
+    return x
+end
+
+x = rand(Vec{2}); state = zeros(Vec{2}, 1)
+gradient(a -> mutating_fun(a, state, true), x)
+# Check that it got correctly modified by the extracted value
+state[1] == x 
+```
+
 ## Inserting a known derivative
 When conditionals are used in a function evaluation, automatic differentiation 
 may yield the wrong result. Consider, the simplified example of the function 
diff --git a/src/automatic_differentiation.jl b/src/automatic_differentiation.jl
index d0aaa877..a2eda3a9 100644
--- a/src/automatic_differentiation.jl
+++ b/src/automatic_differentiation.jl
@@ -19,6 +19,16 @@ end
 # Value extraction #
 ####################
 
+"""
+    extract_value(v::AbstractTensor)
+
+If `v` is used in a differentiation, such that 
+`eltype(v)::ForwardDiff.Dual`, extract the value-part of the derivative.
+Otherwise, just return `v`.
+"""
+extract_value(v::AbstractTensor{<:Any,<:Any,<:Dual}) = _extract_value(v)
+extract_value(v::AbstractTensor) = v
+
 # Scalar output -> Scalar value
 """
     function _extract_value(v::ForwardDiff.Dual)
diff --git a/test/test_ad.jl b/test/test_ad.jl
index bb696b4c..d6ad37b8 100644
--- a/test/test_ad.jl
+++ b/test/test_ad.jl
@@ -337,5 +337,26 @@ S(C) = S(C, μ, Kb)
         end
     
     end
+    
+    @testset "value_extraction" begin
+        function mutating_fun(x::Vec, state::Vector; use_extract::Bool, contract::Bool)
+            v = contract ? x⋅x : x
+            state[1] = use_extract ? Tensors.extract_value(v) : v
+            return x
+        end
+        TT = Vec{2,Float64}
+        x = rand(TT); state = zeros(TT, 1)
+        gradient(a -> mutating_fun(a, state; use_extract=true, contract=false), x)
+        # Check that it got correctly modified by the extracted value
+        @test state[1] == x 
+        # Check that test works: Should fail if no extract_value is not used
+        @test_throws MethodError gradient(a -> mutating_fun(a, state; use_extract=false, contract=false), x)
+        # Do not allow extract_value on a <:Real
+        @test_throws MethodError gradient(a -> mutating_fun(a, state; use_extract=false, contract=true), x)
+        # Check that it get correctly modified when not differentiating 
+        x = rand(TT);
+        mutating_fun(x, state; use_extract=true, contract=false)
+        @test state[1] == x
+    end
 
 end # testsection