diff --git a/examples/3_tricks.jl b/examples/3_tricks.jl
index 572b13b..8570898 100644
--- a/examples/3_tricks.jl
+++ b/examples/3_tricks.jl
@@ -5,6 +5,7 @@ We demonstrate several features that may come in handy for some users.
 =#
 
 using ComponentArrays
+using Enzyme  #src
 using ForwardDiff
 using ImplicitDifferentiation
 using Krylov
@@ -67,6 +68,8 @@ J = ForwardDiff.jacobian(forward_components, x)  #src
 Zygote.jacobian(implicit_components, x)[1]
 @test Zygote.jacobian(implicit_components, x)[1] ≈ J  #src
 
+@test Enzyme.jacobian(Enzyme.Forward, implicit_components, x) ≈ J  #src
+
 #- The full differentiable pipeline looks like this
 
 function full_pipeline(a, b, m)
diff --git a/ext/ImplicitDifferentiationEnzymeExt.jl b/ext/ImplicitDifferentiationEnzymeExt.jl
index 9d1d595..4f2f257 100644
--- a/ext/ImplicitDifferentiationEnzymeExt.jl
+++ b/ext/ImplicitDifferentiationEnzymeExt.jl
@@ -26,7 +26,7 @@ function EnzymeRules.forward(
     B = build_B(implicit, x, y_or_yz, args...; suggested_backend)
 
     dx_batch = reduce(hcat, dx)
-    dc_batch = mapreduce(hcat, eachcol(dx_batch)) do dₖx
+    dc_batch = mapreduce(hcat, dx_batch) do dₖx
         B * X(dₖx)
     end
     dy_batch = implicit.linear_solver(A, -dc_batch)
@@ -52,47 +52,4 @@ function EnzymeRules.forward(
     end
 end
 
-function EnzymeRules.forward(
-    func::Const{<:ImplicitFunction},
-    RT::Type{<:Union{Duplicated,DuplicatedNoNeed}},
-    func_x::Union{Duplicated{T},DuplicatedNoNeed{T}},
-    func_args::Vararg{Const,P},
-) where {T,P}
-    implicit = func.val
-    x = func_x.val
-    dx = func_x.dval
-    args = map(a -> a.val, func_args)
-
-    y_or_yz = implicit(x, args...)
-    y = output(y_or_yz)
-    Y = typeof(y)
-
-    suggested_backend = AutoEnzyme(Enzyme.Forward)
-    A = build_A(implicit, x, y_or_yz, args...; suggested_backend)
-    B = build_B(implicit, x, y_or_yz, args...; suggested_backend)
-
-    dc = B * dx
-
-    dy = convert(Y, implicit.linear_solver(A, -dc))
-    
-
-    if y_or_yz isa AbstractArray
-        if RT <: Duplicated
-            return Duplicated(y, dy)
-        elseif RT <: DuplicatedNoNeed
-            return dy
-        end
-    elseif y_or_yz isa Tuple
-        yz = y_or_yz
-        z = byproduct(yz)
-        Z = typeof(z)
-        dyz::NTuple{N,Tuple{Y,Z}} = ntuple(k -> (dy[k], make_zero(z)), Val(N))
-        if RT <: Duplicated
-            return Duplicated(yz, dyz)
-        elseif RT <: DuplicatedNoNeed
-            return dyz
-        end
-    end
-end
-
 end