theorem Ideal.IsHomogeneous.isPrime_of_homogeneous_mem_or_mem {I : Ideal A} (hI : I.IsHomogeneous 𝒜)
    (I_ne_top : I ≠ ⊤)
    (homogeneous_mem_or_mem :
      ∀ {x y : A}, Homogeneous 𝒜 x → Homogeneous 𝒜 y → x * y ∈ I → x ∈ I ∨ y ∈ I) :
    Ideal.IsPrime I :=
  ⟨I_ne_top, by
    intro x y hxy
    by_contra! rid
    obtain ⟨rid₁, rid₂⟩ := rid
    classical
      /-
        The idea of the proof is the following :
        since `x * y ∈ I` and `I` homogeneous, then `proj i (x * y) ∈ I` for any `i : ι`.
        Then consider two sets `{i ∈ x.support | xᵢ ∉ I}` and `{j ∈ y.support | yⱼ ∉ J}`;
        let `max₁, max₂` be the maximum of the two sets, then `proj (max₁ + max₂) (x * y) ∈ I`.
        Then, `proj max₁ x ∉ I` and `proj max₂ j ∉ I`
        but `proj i x ∈ I` for all `max₁ < i` and `proj j y ∈ I` for all `max₂ < j`.
        `  proj (max₁ + max₂) (x * y)`
        `= ∑ {(i, j) ∈ supports | i + j = max₁ + max₂}, xᵢ * yⱼ`
        `= proj max₁ x * proj max₂ y`
        `  + ∑ {(i, j) ∈ supports \ {(max₁, max₂)} | i + j = max₁ + max₂}, xᵢ * yⱼ`.
        This is a contradiction, because both `proj (max₁ + max₂) (x * y) ∈ I` and the sum on the
        right hand side is in `I` however `proj max₁ x * proj max₂ y` is not in `I`.
        -/
      set set₁ := (decompose 𝒜 x).support.filter (fun i => proj 𝒜 i x ∉ I) with set₁_eq
      set set₂ := (decompose 𝒜 y).support.filter (fun i => proj 𝒜 i y ∉ I) with set₂_eq
      have nonempty :
        ∀ x : A, x ∉ I → ((decompose 𝒜 x).support.filter (fun i => proj 𝒜 i x ∉ I)).Nonempty := by
        intro x hx
        rw [filter_nonempty_iff]
        contrapose! hx
        simp_rw [proj_apply] at hx
        rw [← sum_support_decompose 𝒜 x]
        exact Ideal.sum_mem _ hx
      set max₁ := set₁.max' (nonempty x rid₁)
      set max₂ := set₂.max' (nonempty y rid₂)
      have mem_max₁ : max₁ ∈ set₁ := max'_mem set₁ (nonempty x rid₁)
      have mem_max₂ : max₂ ∈ set₂ := max'_mem set₂ (nonempty y rid₂)
      replace hxy : proj 𝒜 (max₁ + max₂) (x * y) ∈ I := hI _ hxy
      have mem_I : proj 𝒜 max₁ x * proj 𝒜 max₂ y ∈ I := by
        set antidiag :=
          ((decompose 𝒜 x).support ×ˢ (decompose 𝒜 y).support).filter (fun z : ι × ι =>
            z.1 + z.2 = max₁ + max₂) with ha
        have mem_antidiag : (max₁, max₂) ∈ antidiag := by
          simp only [add_sum_erase, mem_filter, mem_product]
          exact ⟨⟨mem_of_mem_filter _ mem_max₁, mem_of_mem_filter _ mem_max₂⟩, trivial⟩
        

Proof state:
ι : Type u_1
σ : Type u_2
A : Type u_3
inst✝⁴ : CommRing A
inst✝³ : LinearOrderedCancelAddCommMonoid ι
inst✝² : SetLike σ A
inst✝¹ : AddSubmonoidClass σ A
𝒜 : ι → σ
inst✝ : GradedRing 𝒜
I : Ideal A
hI : IsHomogeneous 𝒜 I
I_ne_top : I ≠ ⊤
homogeneous_mem_or_mem : ∀ {x y : A}, Homogeneous 𝒜 x → Homogeneous 𝒜 y → x * y ∈ I → x ∈ I ∨ y ∈ I
x y : A
rid₁ : x ∉ I
rid₂ : y ∉ I
set₁ : Finset ι := filter (fun i => (proj 𝒜 i) x ∉ I) (DFinsupp.support ((decompose 𝒜) x))
set₁_eq : set₁ = filter (fun i => (proj 𝒜 i) x ∉ I) (DFinsupp.support ((decompose 𝒜) x))
set₂ : Finset ι := filter (fun i => (proj 𝒜 i) y ∉ I) (DFinsupp.support ((decompose 𝒜) y))
set₂_eq : set₂ = filter (fun i => (proj 𝒜 i) y ∉ I) (DFinsupp.support ((decompose 𝒜) y))
nonempty : ∀ x ∉ I, Finset.Nonempty (filter (fun i => (proj 𝒜 i) x ∉ I) (DFinsupp.support ((decompose 𝒜) x)))
max₁ : ι := max' set₁ (_ : Finset.Nonempty (filter (fun i => (proj 𝒜 i) x ∉ I) (DFinsupp.support ((decompose 𝒜) x))))
max₂ : ι := max' set₂ (_ : Finset.Nonempty (filter (fun i => (proj 𝒜 i) y ∉ I) (DFinsupp.support ((decompose 𝒜) y))))
mem_max₁ : max₁ ∈ set₁
mem_max₂ : max₂ ∈ set₂
hxy : (proj 𝒜 (max₁ + max₂)) (x * y) ∈ I
antidiag : Finset (ι × ι) :=
  filter (fun z => z.1 + z.2 = max₁ + max₂) (DFinsupp.support ((decompose 𝒜) x) ×ˢ DFinsupp.support ((decompose 𝒜) y))
ha :
  antidiag =
    filter (fun z => z.1 + z.2 = max₁ + max₂) (DFinsupp.support ((decompose 𝒜) x) ×ˢ DFinsupp.support ((decompose 𝒜) y))
mem_antidiag : (max₁, max₂) ∈ antidiag
⊢ (proj 𝒜 max₁) x * (proj 𝒜 max₂) y ∈ I

Next tactic:
have eq_add_sum :=
          calc
            proj 𝒜 (max₁ + max₂) (x * y) = ∑ ij in antidiag, proj 𝒜 ij.1 x * proj 𝒜 ij.2 y := by
              simp_rw [ha, proj_apply, DirectSum.decompose_mul, DirectSum.coe_mul_apply 𝒜]
            _ =
                proj 𝒜 max₁ x * proj 𝒜 max₂ y +
                  ∑ ij in antidiag.erase (max₁, max₂), proj 𝒜 ij.1 x * proj 𝒜 ij.2 y :=
              (add_sum_erase _ _ mem_antidiag).symm