diff --git a/.github/workflows/linux_aarch64.yml b/.github/workflows/linux_aarch64.yml
new file mode 100644
index 00000000..a505d1e4
--- /dev/null
+++ b/.github/workflows/linux_aarch64.yml
@@ -0,0 +1,37 @@
+name: Crystal CI
+
+on:
+  push:
+    branches: [ master ]
+  # pull_request:
+  #   branches: [ master ]
+
+jobs:
+  build:
+
+    runs-on: [linux, ARM64]
+
+    container:
+      image: crystallang/crystal:nightly-alpine
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Show Crystal version
+      run: crystal -v
+
+    - name: Install dependencies
+      # run: shards install && shards update
+      run: shards install --ignore-crystal-version && shards update --ignore-crystal-version
+
+    - name: Show repo version
+      run: scripts/version_info
+
+    - name: Run static code analysis
+      run: bin/ameba --no-color
+    - name: Run tests
+      run: scripts/test_always
+
+      # run: crystal spec
+    - name: Run tests (w/ junit format)
+      run: scripts/test_always_junit_format
diff --git a/.github/workflows/crystal.yml b/.github/workflows/linux_amd64.yml
similarity index 94%
rename from .github/workflows/crystal.yml
rename to .github/workflows/linux_amd64.yml
index 2615a289..ddc95472 100644
--- a/.github/workflows/crystal.yml
+++ b/.github/workflows/linux_amd64.yml
@@ -3,8 +3,8 @@ name: Crystal CI
 on:
   push:
     branches: [ master ]
-  pull_request:
-    branches: [ master ]
+  # pull_request:
+  #   branches: [ master ]
 
 jobs:
   build:
diff --git a/spec/ai4cr/breed/manager_spec.cr b/spec/ai4cr/breed/manager_spec.cr
index ea882386..da31cbc4 100644
--- a/spec/ai4cr/breed/manager_spec.cr
+++ b/spec/ai4cr/breed/manager_spec.cr
@@ -1,4 +1,3 @@
-require "./../../spec_helper"
 require "./../../spectator_helper"
 
 class MyBreed
diff --git a/spec/ai4cr/error_stats_spec.cr b/spec/ai4cr/error_stats_spec.cr
index d0fdbdc6..bcdbdc5c 100644
--- a/spec/ai4cr/error_stats_spec.cr
+++ b/spec/ai4cr/error_stats_spec.cr
@@ -1,4 +1,3 @@
-require "./../spec_helper"
 require "./../spectator_helper"
 
 Spectator.describe Ai4cr::ErrorStats do
diff --git a/spec/ai4cr/neural_network/cmn/mini_net_manager_spec.cr b/spec/ai4cr/neural_network/cmn/mini_net_manager_spec.cr
index 42dbe009..629a7ab8 100644
--- a/spec/ai4cr/neural_network/cmn/mini_net_manager_spec.cr
+++ b/spec/ai4cr/neural_network/cmn/mini_net_manager_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../spec_helper"
 require "./../../../spectator_helper"
 
 Spectator.describe Ai4cr::NeuralNetwork::Cmn::MiniNetManager do
diff --git a/spec/ai4cr/neural_network/from_json/learning_styles_spec.cr b/spec/ai4cr/neural_network/from_json/learning_styles_spec.cr
index aa66d431..a6dc1347 100644
--- a/spec/ai4cr/neural_network/from_json/learning_styles_spec.cr
+++ b/spec/ai4cr/neural_network/from_json/learning_styles_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../spec_helper"
 require "./../../../spectator_helper"
 
 Spectator.describe "from_json" do
diff --git a/spec/ai4cr/neural_network/from_json/mini_net_manager_spec.cr b/spec/ai4cr/neural_network/from_json/mini_net_manager_spec.cr
index c715263b..794f825e 100644
--- a/spec/ai4cr/neural_network/from_json/mini_net_manager_spec.cr
+++ b/spec/ai4cr/neural_network/from_json/mini_net_manager_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../spec_helper"
 require "./../../../spectator_helper"
 
 Spectator.describe Ai4cr::NeuralNetwork::Cmn::MiniNetManager do
diff --git a/spec/ai4cr/neural_network/from_json/mini_net_spec.cr b/spec/ai4cr/neural_network/from_json/mini_net_spec.cr
index cbcfc1a5..d66edca5 100644
--- a/spec/ai4cr/neural_network/from_json/mini_net_spec.cr
+++ b/spec/ai4cr/neural_network/from_json/mini_net_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../spec_helper"
 require "./../../../spectator_helper"
 
 Spectator.describe "from_json" do
diff --git a/spec/ai4cr/neural_network/from_json/rnn_simple_manager_spec.cr b/spec/ai4cr/neural_network/from_json/rnn_simple_manager_spec.cr
index 237716c1..112586c6 100644
--- a/spec/ai4cr/neural_network/from_json/rnn_simple_manager_spec.cr
+++ b/spec/ai4cr/neural_network/from_json/rnn_simple_manager_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../spec_helper"
 require "./../../../spectator_helper"
 
 Spectator.describe Ai4cr::NeuralNetwork::Rnn::RnnSimpleManager do
diff --git a/spec/ai4cr/neural_network/from_json/rnn_simple_spec.cr b/spec/ai4cr/neural_network/from_json/rnn_simple_spec.cr
index bfa42b37..51df1047 100644
--- a/spec/ai4cr/neural_network/from_json/rnn_simple_spec.cr
+++ b/spec/ai4cr/neural_network/from_json/rnn_simple_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../spec_helper"
 require "./../../../spectator_helper"
 
 Spectator.describe Ai4cr::NeuralNetwork::Cmn::RnnSimpleConcerns::TrainAndAdjust do
diff --git a/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/calc_guess_spec.cr b/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/calc_guess_spec.cr
index 335c2e19..93255595 100644
--- a/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/calc_guess_spec.cr
+++ b/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/calc_guess_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../../spec_helper"
 require "./../../../../spectator_helper"
 
 Spectator.describe Ai4cr::NeuralNetwork::Rnn::RnnSimpleConcerns::CalcGuess do
diff --git a/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/data_utils_spec.cr b/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/data_utils_spec.cr
index 2fa509c3..89434c1b 100644
--- a/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/data_utils_spec.cr
+++ b/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/data_utils_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../../spec_helper"
 require "./../../../../spectator_helper"
 
 Spectator.describe Ai4cr::NeuralNetwork::Rnn::RnnSimpleConcerns::DataUtils do
diff --git a/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/props_and_inits_spec.cr b/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/props_and_inits_spec.cr
index 3153850e..9a0c1809 100644
--- a/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/props_and_inits_spec.cr
+++ b/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/props_and_inits_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../../spec_helper"
 require "./../../../../spectator_helper"
 
 Spectator.describe Ai4cr::NeuralNetwork::Rnn::RnnSimpleConcerns::PropsAndInits do
diff --git a/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/train_and_adjust_spec.cr b/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/train_and_adjust_spec.cr
index ff5d5906..6cb62649 100644
--- a/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/train_and_adjust_spec.cr
+++ b/spec/ai4cr/neural_network/rnn/rnn_simple_concerns/train_and_adjust_spec.cr
@@ -1,4 +1,3 @@
-require "./../../../../spec_helper"
 require "./../../../../spectator_helper"
 
 Spectator.describe Ai4cr::NeuralNetwork::Rnn::RnnSimpleConcerns::TrainAndAdjust do
diff --git a/spec/ai4cr/neural_network/rnn/rnn_simple_manager_spec.cr b/spec/ai4cr/neural_network/rnn/rnn_simple_manager_spec.cr
index 6ddf9a28..040f6745 100644
--- a/spec/ai4cr/neural_network/rnn/rnn_simple_manager_spec.cr
+++ b/spec/ai4cr/neural_network/rnn/rnn_simple_manager_spec.cr
@@ -1,17 +1,17 @@
-require "./../../../spec_helper"
 require "./../../../spectator_helper"
 
 Spectator.describe Ai4cr::NeuralNetwork::Rnn::RnnSimpleManager do
   let(my_breed_manager) { Ai4cr::NeuralNetwork::Rnn::RnnSimpleManager.new }
   let(delta_child_1) { Ai4cr::Data::Utils.rand_neg_half_to_pos_one_and_half_no_zero_no_one }
-  let(delta_child_2) { Ai4cr::Data::Utils.rand_neg_half_to_pos_one_and_half_no_zero_no_one }
 
   let(ancestor_adam_value) { 0.1 }
   let(ancestor_eve_value) { 0.9 }
   let(expected_child_1_value) { ancestor_adam_value + delta_child_1 * (ancestor_eve_value - ancestor_adam_value) }
 
+  let(params) { my_breed_manager.gen_params }
   let(config_default_randomized) {
-    Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
+    # Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
+    params
   }
 
   let(config_adam) {
@@ -192,13 +192,6 @@ Spectator.describe Ai4cr::NeuralNetwork::Rnn::RnnSimpleManager do
       end
 
       context "children have expected values for" do
-        # let(child_1) {
-        #   # cain
-        #   child = my_breed_manager.breed(ancestor_adam, ancestor_eve, delta: delta_child_1)
-        #   child.name = "Cain, child of #{ancestor_adam.name} and #{ancestor_eve.name}"
-        #   child
-        # }
-
         let(ancestor_adam_json) { JSON.parse(ancestor_adam.to_json) }
         let(ancestor_eve_json) { JSON.parse(ancestor_eve.to_json) }
         let(child_1_json) { JSON.parse(child_1.to_json) }
@@ -334,92 +327,131 @@ Spectator.describe Ai4cr::NeuralNetwork::Rnn::RnnSimpleManager do
     end
   end
 
-  describe "#build_team" do
-    context "when using all defaults" do
-      it "creates specified quantity of members" do
-        qty_new_members = 4
-        params = Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
-        next_gen_members = my_breed_manager.build_team(qty_new_members, **params)
-        expect(next_gen_members.size).to eq(qty_new_members)
-      end
+  describe "#gen_params" do
+    let(param_keys) { params.keys.to_a }
+    let(expected_keys) {
+      [
+        :name, :history_size, :io_offset, :time_col_qty,
+        :input_size, :output_size, :hidden_layer_qty, :hidden_size_given,
+        :learning_style, :bias_disabled, :bias_default, :learning_rate,
+        :momentum, :deriv_scale,
+      ]
+    }
+    it "which include expected keys" do
+      expect(param_keys).to eq(expected_keys)
     end
   end
 
-  describe "#train_team" do
-    pending "successive generations score better (i.e.: lower errors)" do
-      # TODO: (a) move to 'spec_bench' and (b) replace here with more 'always' tests
-      max_members = 10
-      qty_new_members = max_members
+  describe "#build_team" do
+    context "with defaults" do
+      let(team_members) { my_breed_manager.build_team }
 
-      params = Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
+      it "builds a team of expected size" do
+        expect(team_members.size).to eq(10)
+      end
 
-      first_gen_members = my_breed_manager.build_team(qty_new_members, **params)
-      second_gen_members = my_breed_manager.train_team(inputs, outputs, first_gen_members, max_members)
-      third_gen_members = my_breed_manager.train_team(inputs, outputs, second_gen_members, max_members)
+      it "builds a team of expected class" do
+        expect(team_members.class).to eq(Array(Ai4cr::NeuralNetwork::Rnn::RnnSimple))
+      end
 
-      first_gen_members_scored = first_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
-      first_gen_members_stats = first_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
+      context "creates members with expected values for" do
+        it ":name" do
+          key = :name
+          key_string = key.to_s
+          team_members.each do |member|
+            member_json = JSON.parse(member.to_json)
+            expect(member_json[key_string]).to eq(params[key_string])
+          end
+          # member = team_members.first
+          # member_json = JSON.parse(member.to_json)
+          # expect(member_json[key_string]).to eq(params[key_string])
+        end
+      end
 
-      second_gen_members_scored = second_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
-      second_gen_members_stats = second_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
+      # context "creates members of specified params for key" do
+      #   let(next_gen_members) { my_breed_manager.build_team }
+      #   it "creates members of specified params" do
+      #     qty_new_members = 4
+      #     params = Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
+      #     next_gen_members = my_breed_manager.build_team(qty_new_members, **params)
+
+      #     puts
+      #     puts "params.class: #{params.class}"
+      #     puts
+      #     puts "params.keys: #{params.keys}"
+      #     puts
+      #     puts "JSON.parse(next_gen_members.first.to_json)[:name.to_s]: #{JSON.parse(next_gen_members.first.to_json)[:name.to_s]}"
+      #     puts
+
+      #     next_gen_members.each do |member|
+      #       member_json = JSON.parse(next_gen_members.first.to_json)
+      #       (params.keys.to_a - [:history_size, :learning_style]).each do |key|
+      #         key_string = key.to_s
+      #         params_value = params[key]
+
+      #         # expect([key_string, member_json[key_string]]).to eq([key_string, params_value])
+      #         # assert_approximate_equality_of_nested_list([key_string, member_json[key_string]], [key_string, params_value])
+      #       end
+      #     end
+
+      #   end
+      # end
+    end
 
-      third_gen_members_scored = third_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
-      third_gen_members_stats = third_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
+    context "when given qty_new_members' and using defaults params" do
+      it "creates specified quantity of members" do
+        qty_new_members = 4
+        next_gen_members = my_breed_manager.build_team(qty_new_members)
+        expect(next_gen_members.size).to eq(qty_new_members)
+      end
 
-      puts
-      puts "#train_team:"
-      puts
-      puts "first_gen_members_scored: #{first_gen_members_scored}"
-      first_gen_members_stats.each { |m| puts m }
+      it "creates members of specified class" do
+        qty_new_members = 4
+        next_gen_members = my_breed_manager.build_team(qty_new_members)
+        member_classes = next_gen_members.map { |member| member.class.name }.sort.uniq
+        expect(member_classes.size).to eq(1)
+        expect(member_classes.first).to eq(Ai4cr::NeuralNetwork::Rnn::RnnSimple.name)
+      end
+    end
 
-      puts
-      puts "second_gen_members_scored: #{second_gen_members_scored}"
-      second_gen_members_stats.each { |m| puts m }
-      expect(second_gen_members_scored).to be < first_gen_members_scored
+    context "when given qty_new_members' and params" do
+      it "creates specified quantity of members" do
+        qty_new_members = 4
+        params = Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
+        next_gen_members = my_breed_manager.build_team(qty_new_members, **params)
+        expect(next_gen_members.size).to eq(qty_new_members)
+      end
 
-      puts
-      puts "third_gen_members_scored: #{third_gen_members_scored}"
-      third_gen_members_stats.each { |m| puts m }
-      expect(third_gen_members_scored).to be < second_gen_members_scored
+      it "creates members of specified class" do
+        qty_new_members = 4
+        params = Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
+        next_gen_members = my_breed_manager.build_team(qty_new_members, **params)
+        member_classes = next_gen_members.map { |member| member.class.name }.sort.uniq
+        expect(member_classes.size).to eq(1)
+        expect(member_classes.first).to eq(Ai4cr::NeuralNetwork::Rnn::RnnSimple.name)
+      end
     end
   end
 
-  describe "#train_team_using_sequence" do
-    pending "successive generations score better (i.e.: lower errors)" do
-      # TODO: (a) move to 'spec_bench' and (b) replace here with more 'always' tests
-      max_members = 10
-      qty_new_members = max_members
-
-      params = Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
-
-      first_gen_members = my_breed_manager.build_team(qty_new_members, **params)
-      second_gen_members = my_breed_manager.train_team_using_sequence(inputs_sequence, outputs_sequence, first_gen_members, max_members)
-      third_gen_members = my_breed_manager.train_team_using_sequence(inputs_sequence, outputs_sequence, second_gen_members, max_members)
-
-      first_gen_members_scored = first_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
-      first_gen_members_stats = first_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
-
-      second_gen_members_scored = second_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
-      second_gen_members_stats = second_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
-
-      third_gen_members_scored = third_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
-      third_gen_members_stats = third_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
-
-      puts
-      puts "#train_team_using_sequence:"
-      puts
-      puts "first_gen_members_scored: #{first_gen_members_scored}"
-      first_gen_members_stats.each { |m| puts m }
+  describe "#train_team" do
+    context "with defaults" do
+      # let(qty_new_members) { 3 }
+      let(team_members) { my_breed_manager.build_team } # (qty_new_members) }
+
+      # let(inputs) { 3 }
+      # let(outputs) { 3 }
+      # let(max_members) { 3 }
+
+      # it "" do
+      #   expect(team_members.size).
+      #   next_gen_members = my_breed_manager.train_team(inputs, outputs, team_members) #, max_members)
+      # end
+    end
+  end
 
-      puts
-      puts "second_gen_members_scored: #{second_gen_members_scored}"
-      second_gen_members_stats.each { |m| puts m }
-      expect(second_gen_members_scored).to be < first_gen_members_scored
+  describe "#train_team_using_sequence" do
+  end
 
-      puts
-      puts "third_gen_members_scored: #{third_gen_members_scored}"
-      third_gen_members_stats.each { |m| puts m }
-      expect(third_gen_members_scored).to be < second_gen_members_scored
-    end
+  describe "#cross_breed" do
   end
 end
diff --git a/spec/ai4cr/team_spec.cr b/spec/ai4cr/team_spec.cr
index d351badb..6f0340e3 100644
--- a/spec/ai4cr/team_spec.cr
+++ b/spec/ai4cr/team_spec.cr
@@ -1,4 +1,3 @@
-require "./../spec_helper"
 require "./../spectator_helper"
 
 Spectator.describe Ai4cr::Team do
diff --git a/spec_bench/ai4cr/neural_network/rnn/rnn_simple_manager_spec.cr b/spec_bench/ai4cr/neural_network/rnn/rnn_simple_manager_spec.cr
new file mode 100644
index 00000000..18d57556
--- /dev/null
+++ b/spec_bench/ai4cr/neural_network/rnn/rnn_simple_manager_spec.cr
@@ -0,0 +1,200 @@
+require "../../../../spec/spectator_helper"
+require "../../../spec_bench_helper"
+# require "../../../support/neural_network/data/*"
+
+Spectator.describe Ai4cr::NeuralNetwork::Rnn::RnnSimpleManager do
+  let(my_breed_manager) { Ai4cr::NeuralNetwork::Rnn::RnnSimpleManager.new }
+
+  let(ancestor_adam_value) { 0.1 }
+  let(ancestor_eve_value) { 0.9 }
+
+  let(config_default_randomized) {
+    Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
+  }
+
+  let(config_adam) {
+    config_default_randomized.merge(
+      name: "Adam",
+
+      bias_disabled: false,
+      bias_default: (ancestor_adam_value / 2.0).round(1),
+
+      learning_rate: ancestor_adam_value,
+      # momentum: (1.0 - ancestor_adam_value).round(1),
+      momentum: ancestor_adam_value,
+      deriv_scale: (ancestor_adam_value / 4.0).round(1),
+
+      history_size: 3
+    )
+  }
+
+  let(config_eve) {
+    config_default_randomized.merge(
+      name: "Eve",
+
+      bias_disabled: false,
+      bias_default: (ancestor_eve_value / 2.0).round(1),
+
+      learning_rate: ancestor_eve_value,
+      # momentum: (1.0 - ancestor_eve_value).round(1),
+      momentum: ancestor_eve_value,
+      deriv_scale: (ancestor_eve_value / 4.0).round(1),
+
+      history_size: 3
+    )
+  }
+  let(ancestor_adam) {
+    ancestor = my_breed_manager.create(**config_adam)
+    ancestor.mini_net_set.each do |mini_net_li|
+      mini_net_li.each do |mini_net_ti|
+        mini_net_ti.weights.map_with_index! do |row, i|
+          row.map_with_index! do |_col, j|
+            (i + j / 10.0).round(1)
+          end
+        end
+      end
+    end
+    ancestor.train(inputs, outputs)
+    # ancestor.train(inputs, outputs)
+    ancestor
+  }
+  let(ancestor_eve) {
+    ancestor = my_breed_manager.create(**config_eve)
+    ancestor.mini_net_set.each do |mini_net_li|
+      mini_net_li.each do |mini_net_ti|
+        mini_net_ti.weights.map_with_index! do |row, i|
+          row.map_with_index! do |_col, j|
+            -(i + j / 10.0).round(1)
+          end
+        end
+      end
+    end
+    ancestor.train(inputs, outputs)
+    # ancestor.train(inputs, outputs)
+    ancestor
+  }
+
+  let(inputs) {
+    [
+      [0.1, 0.2],
+      [0.3, 0.4],
+    ]
+  }
+  let(outputs) {
+    [
+      [0.1],
+      [0.9],
+    ]
+  }
+
+  let(inputs_sequence) {
+    [
+      [
+        [0.1, 0.2],
+        [0.3, 0.4],
+      ],
+      [
+        [0.3, 0.4],
+        [0.5, 0.6],
+      ],
+      [
+        [0.5, 0.6],
+        [0.7, 0.8],
+      ],
+    ]
+  }
+  let(outputs_sequence) {
+    [
+      [
+        [0.1],
+        [0.9],
+      ],
+      [
+        [0.9],
+        [0.5],
+      ],
+      [
+        [0.5],
+        [0.3],
+      ],
+    ]
+  }
+
+  describe "#train_team" do
+    it "successive generations score better (i.e.: lower errors)" do
+      # TODO: (a) move to 'spec_bench' and (b) replace here with more 'always' tests
+      max_members = 10
+      qty_new_members = max_members
+
+      params = Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
+
+      first_gen_members = my_breed_manager.build_team(qty_new_members, **params)
+      second_gen_members = my_breed_manager.train_team(inputs, outputs, first_gen_members, max_members)
+      third_gen_members = my_breed_manager.train_team(inputs, outputs, second_gen_members, max_members)
+
+      first_gen_members_scored = first_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
+      first_gen_members_stats = first_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
+
+      second_gen_members_scored = second_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
+      second_gen_members_stats = second_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
+
+      third_gen_members_scored = third_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
+      third_gen_members_stats = third_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
+
+      puts
+      puts "#train_team:"
+      puts
+      puts "first_gen_members_scored: #{first_gen_members_scored}"
+      first_gen_members_stats.each { |m| puts m }
+
+      puts
+      puts "second_gen_members_scored: #{second_gen_members_scored}"
+      second_gen_members_stats.each { |m| puts m }
+      expect(second_gen_members_scored).to be < first_gen_members_scored
+
+      puts
+      puts "third_gen_members_scored: #{third_gen_members_scored}"
+      third_gen_members_stats.each { |m| puts m }
+      expect(third_gen_members_scored).to be < second_gen_members_scored
+    end
+  end
+
+  describe "#train_team_using_sequence" do
+    it "successive generations score better (i.e.: lower errors)" do
+      # TODO: (a) move to 'spec_bench' and (b) replace here with more 'always' tests
+      max_members = 10
+      qty_new_members = max_members
+
+      params = Ai4cr::NeuralNetwork::Rnn::RnnSimple.new.config
+
+      first_gen_members = my_breed_manager.build_team(qty_new_members, **params)
+      second_gen_members = my_breed_manager.train_team_using_sequence(inputs_sequence, outputs_sequence, first_gen_members, max_members)
+      third_gen_members = my_breed_manager.train_team_using_sequence(inputs_sequence, outputs_sequence, second_gen_members, max_members)
+
+      first_gen_members_scored = first_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
+      first_gen_members_stats = first_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
+
+      second_gen_members_scored = second_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
+      second_gen_members_stats = second_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
+
+      third_gen_members_scored = third_gen_members.map { |member| member.error_stats.score }.sum / qty_new_members
+      third_gen_members_stats = third_gen_members.map { |member| "#{member.birth_id} => #{member.error_stats.plot_error_distance_history} @ #{member.error_stats.score}" }
+
+      puts
+      puts "#train_team_using_sequence:"
+      puts
+      puts "first_gen_members_scored: #{first_gen_members_scored}"
+      first_gen_members_stats.each { |m| puts m }
+
+      puts
+      puts "second_gen_members_scored: #{second_gen_members_scored}"
+      second_gen_members_stats.each { |m| puts m }
+      expect(second_gen_members_scored).to be < first_gen_members_scored
+
+      puts
+      puts "third_gen_members_scored: #{third_gen_members_scored}"
+      third_gen_members_stats.each { |m| puts m }
+      expect(third_gen_members_scored).to be < second_gen_members_scored
+    end
+  end
+end
diff --git a/src/ai4cr/breed/manager.cr b/src/ai4cr/breed/manager.cr
index 9226553e..58d77d9b 100644
--- a/src/ai4cr/breed/manager.cr
+++ b/src/ai4cr/breed/manager.cr
@@ -46,7 +46,8 @@ module Ai4cr
       # end
       # ```
 
-      MAX_MEMBERS_DEFAULT = 10
+      QTY_NEW_MEMBERS_DEFAULT = 10
+      MAX_MEMBERS_DEFAULT     = QTY_NEW_MEMBERS_DEFAULT
 
       ############################################################################
       # TODO: WHY is this required?
@@ -89,6 +90,10 @@ module Ai4cr
         @@counter.reset(T.name, value)
       end
 
+      def gen_params
+        T.new.config
+      end
+
       def create(**params)
         # i.e.: via NO parents
         channel = Channel(Int32).new
@@ -232,6 +237,21 @@ module Ai4cr
         qty_new_members.times.to_a.map { channel.receive }
       end
 
+      def build_team(qty_new_members : Int32 = QTY_NEW_MEMBERS_DEFAULT) : Array(T)
+        params = gen_params
+        build_team(qty_new_members, **params)
+      end
+
+      def train_team(inputs, outputs, team_members : Array(T), max_members = MAX_MEMBERS_DEFAULT, train_qty = 1)
+        team_members = train_team_in_parallel(inputs, outputs, team_members, train_qty)
+
+        team_members = cross_breed(team_members)
+
+        team_members = train_team_in_parallel(inputs, outputs, team_members, train_qty)
+
+        (team_members.sort_by { |contestant| contestant.error_stats.score })[0..max_members - 1]
+      end
+
       def train_team_using_sequence(inputs_sequence, outputs_sequence, team_members : Array(T), max_members = MAX_MEMBERS_DEFAULT, train_qty = 1)
         inputs_sequence.each_with_index do |inputs, i|
           outputs = outputs_sequence[i]
@@ -248,16 +268,6 @@ module Ai4cr
         (team_members.sort_by { |contestant| contestant.error_stats.score })[0..max_members - 1]
       end
 
-      def train_team(inputs, outputs, team_members : Array(T), max_members = MAX_MEMBERS_DEFAULT, train_qty = 1)
-        team_members = train_team_in_parallel(inputs, outputs, team_members, train_qty)
-
-        team_members = cross_breed(team_members)
-
-        team_members = train_team_in_parallel(inputs, outputs, team_members, train_qty)
-
-        (team_members.sort_by { |contestant| contestant.error_stats.score })[0..max_members - 1]
-      end
-
       def train_team_in_parallel(inputs, outputs, team_members, train_qty)
         channel = Channel(T).new
         qty = team_members.size