diff --git a/integration_tests/dbt_project/dbt_project.yml b/integration_tests/dbt_project/dbt_project.yml
index 6a82f50c6..bb2663282 100644
--- a/integration_tests/dbt_project/dbt_project.yml
+++ b/integration_tests/dbt_project/dbt_project.yml
@@ -29,3 +29,6 @@ models:
     +schema: elementary
     +enabled: "{{ var('elementary_enabled', True) }}"
     +file_format: "{{ 'delta' if target.type in ['spark', 'fabricspark'] else none }}"
+
+flags:
+  require_batched_execution_for_custom_microbatch_strategy: True
\ No newline at end of file
diff --git a/integration_tests/tests/test_dbt_artifacts/test_microbatch_compiled_code.py b/integration_tests/tests/test_dbt_artifacts/test_microbatch_compiled_code.py
new file mode 100644
index 000000000..dea35420a
--- /dev/null
+++ b/integration_tests/tests/test_dbt_artifacts/test_microbatch_compiled_code.py
@@ -0,0 +1,143 @@
+from contextlib import contextmanager
+
+import pytest
+
+from dbt_project import DbtProject
+
+
+def _microbatch_source_model_sql() -> str:
+    return """
+{{ config(event_time='order_date') }}
+{% set event_time_data_type = 'datetime2' if target.type == 'sqlserver' else 'timestamp' %}
+
+select
+    1 as order_id,
+    1 as customer_id,
+    42 as amount,
+    cast('2024-01-01 00:00:00' as {{ event_time_data_type }}) as order_date
+union all
+select
+    2 as order_id,
+    2 as customer_id,
+    84 as amount,
+    cast('2025-01-01 00:00:00' as {{ event_time_data_type }}) as order_date
+"""
+
+
+def _microbatch_model_sql(source_model_name: str) -> str:
+    return """
+{% set model_config = {
+    "materialized": "incremental",
+    "incremental_strategy": "microbatch",
+    "event_time": "order_date",
+    "batch_size": "year",
+    "begin": "2024-01-01"
+} %}
+{% if target.type != "duckdb" %}
+    {% do model_config.update({"unique_key": "order_id"}) %}
+{% endif %}
+{{ config(**model_config) }}
+
+select
+    order_id,
+    customer_id,
+    amount,
+    order_date
+from {{ ref('__MICROBATCH_SOURCE_MODEL__') }}
+""".replace("__MICROBATCH_SOURCE_MODEL__", source_model_name)
+
+
+@contextmanager
+def _with_microbatch_test_models(dbt_project: DbtProject, model_suffix: str):
+    source_model_name = f"mb_src_{model_suffix}"
+    target_model_name = f"mb_tgt_{model_suffix}"
+    source_model_path = dbt_project.tmp_models_dir_path.joinpath(f"{source_model_name}.sql")
+    target_model_path = dbt_project.tmp_models_dir_path.joinpath(f"{target_model_name}.sql")
+
+    source_model_path.write_text(_microbatch_source_model_sql())
+    target_model_path.write_text(_microbatch_model_sql(source_model_name))
+    relative_source_model_path = source_model_path.relative_to(dbt_project.project_dir_path)
+    relative_target_model_path = target_model_path.relative_to(dbt_project.project_dir_path)
+    try:
+        yield relative_source_model_path, relative_target_model_path, target_model_name
+    finally:
+        if source_model_path.exists():
+            source_model_path.unlink()
+        if target_model_path.exists():
+            target_model_path.unlink()
+
+
+def _run_microbatch_model_and_get_latest_success_result(
+    dbt_project: DbtProject, model_suffix: str
+):
+    with _with_microbatch_test_models(dbt_project, model_suffix) as (
+        source_model_path,
+        model_path,
+        target_model_name,
+    ):
+        dbt_project.dbt_runner.run(
+            select=f"{source_model_path} {model_path}"
+        )
+
+    unique_id = f"model.elementary_tests.{target_model_name}"
+    run_results = dbt_project.read_table(
+        "dbt_run_results",
+        where=f"unique_id = '{unique_id}' and status = 'success'",
+        order_by="generated_at desc",
+        limit=1,
+    )
+    return run_results
+
+
+@contextmanager
+def _with_microbatch_macro_file(dbt_project: DbtProject, macro_name: str):
+    macro_path = (
+        dbt_project.project_dir_path / "macros" / "microbatch.sql"
+    )
+    macro_sql = """
+{% macro __MACRO_NAME__(arg_dict) %}
+  {{ return(elementary.get_incremental_microbatch_sql(arg_dict)) }}
+{% endmacro %}
+""".replace("__MACRO_NAME__", macro_name)
+    if macro_path.exists():
+        raise FileExistsError(f"Expected no macro file at {macro_path}")
+
+    macro_path.write_text(macro_sql)
+    try:
+        yield
+    finally:
+        if macro_path.exists():
+            macro_path.unlink()
+
+
+@pytest.mark.skip_targets(["spark", "vertica", "bigquery", "athena", "clickhouse", "dremio"])
+@pytest.mark.skip_for_dbt_fusion
+@pytest.mark.parametrize(
+    "macro_name,expected_compiled_code,model_suffix",
+    [
+        ("get_incremental_microbatch_sql", True, "with_override"),
+        ("get_incremental_microbatch_sql_not_used", False, "without_override"),
+    ],
+    ids=["with_override", "without_override"],
+)
+def test_microbatch_run_results_compiled_code_behavior(
+    dbt_project: DbtProject,
+    macro_name: str,
+    expected_compiled_code: bool,
+    model_suffix: str,
+):
+    dbt_project.dbt_runner.vars["disable_run_results"] = False
+
+    with _with_microbatch_macro_file(dbt_project, macro_name):
+        run_results = _run_microbatch_model_and_get_latest_success_result(
+            dbt_project, model_suffix
+        )
+    assert run_results, "Expected a successful run result row for microbatch model"
+    if expected_compiled_code:
+        assert run_results[0]["compiled_code"], (
+            "Expected compiled_code to be populated when override macro is present"
+        )
+    else:
+        assert not run_results[0]["compiled_code"], (
+            "Expected compiled_code to stay empty when override macro is absent"
+        )
diff --git a/macros/edr/dbt_artifacts/microbatch/capture_microbatch_compiled_code.sql b/macros/edr/dbt_artifacts/microbatch/capture_microbatch_compiled_code.sql
new file mode 100644
index 000000000..856dd91cf
--- /dev/null
+++ b/macros/edr/dbt_artifacts/microbatch/capture_microbatch_compiled_code.sql
@@ -0,0 +1,50 @@
+{#-
+    NOTE FOR PACKAGE CONSUMERS:
+    This package macro is not guaranteed to be picked up automatically by dbt's
+    incremental strategy resolution in all projects.
+    To apply this behavior, users should:
+      1) Override `get_incremental_microbatch_sql` in their own project and delegate to
+         `elementary.get_incremental_microbatch_sql(arg_dict)`.
+      2) Enable dbt behavior flag `require_batched_execution_for_custom_microbatch_strategy`.
+
+    This flow is currently not supported for adapters:
+      - spark
+      - bigquery
+      - athena
+      - clickhouse
+      - dremio
+      - vertica
+
+    This flow is currently not supported for dbt Fusion.
+-#}
+{% macro get_incremental_microbatch_sql(arg_dict) %}
+    {% if execute and model is defined %}
+        {% do elementary.capture_microbatch_compiled_code_for_model() %}
+    {% endif %}
+
+    {{ return(adapter.dispatch("get_incremental_microbatch_sql", "dbt")(arg_dict)) }}
+{% endmacro %}
+
+
+{% macro capture_microbatch_compiled_code_for_model() %}
+    {% set model_unique_id = (
+        model.get("unique_id") if model is mapping else model.unique_id
+    ) | default(none, true) %}
+    {% set model_compiled_code = (
+        model.get("compiled_code") if model is mapping else model.compiled_code
+    ) | default(none, true) %}
+    {% if model_unique_id is none %}
+        {{ return(none) }}
+    {% endif %}
+    {% if not model_compiled_code %}
+        {{ return(none) }}
+    {% endif %}
+
+    {% set compiled_code_by_unique_id = elementary.get_cache(
+        "microbatch_compiled_code_by_unique_id"
+    ) %}
+    {% if model_unique_id in compiled_code_by_unique_id %}
+        {{ return(none) }}
+    {% endif %}
+    {% do compiled_code_by_unique_id.update({model_unique_id: model_compiled_code}) %}
+{% endmacro %}
diff --git a/macros/edr/tests/on_run_start/init_elementary_graph.sql b/macros/edr/tests/on_run_start/init_elementary_graph.sql
index 576cf2d38..00fda83de 100644
--- a/macros/edr/tests/on_run_start/init_elementary_graph.sql
+++ b/macros/edr/tests/on_run_start/init_elementary_graph.sql
@@ -11,6 +11,7 @@
             },
             "temp_test_table_relations_map": {},
             "duration_context_stack": {},
+            "microbatch_compiled_code_by_unique_id": {},
         },
     ) %}
 {% endmacro %}
diff --git a/macros/utils/graph/get_compiled_code.sql b/macros/utils/graph/get_compiled_code.sql
index 69ddcfb94..6ce92316e 100644
--- a/macros/utils/graph/get_compiled_code.sql
+++ b/macros/utils/graph/get_compiled_code.sql
@@ -1,5 +1,11 @@
 {% macro get_compiled_code(node, as_column_value=false) %}
-    {% set compiled_code = adapter.dispatch("get_compiled_code", "elementary")(node) %}
+    {% set compiled_code = node.get("compiled_code") or node.get("compiled_sql") %}
+    {% if not compiled_code and node and node.get("unique_id") %}
+        {% set compiled_code = elementary.get_cache(
+            "microbatch_compiled_code_by_unique_id", {}
+        ).get(node.get("unique_id")) %}
+    {% endif %}
+    {% set compiled_code = adapter.dispatch("format_compiled_code", "elementary")(compiled_code) %}
 
     {% set max_column_size = elementary.get_column_size() %}
     {% if as_column_value and max_column_size and compiled_code and compiled_code | length > max_column_size %}
@@ -9,12 +15,11 @@
     {% do return(compiled_code) %}
 {% endmacro %}
 
-{% macro default__get_compiled_code(node) %}
-    {% do return(node.get("compiled_code") or node.get("compiled_sql")) %}
+{% macro default__format_compiled_code(compiled_code) %}
+    {% do return(compiled_code) %}
 {% endmacro %}
 
-{% macro redshift__get_compiled_code(node) %}
-    {% set compiled_code = node.get("compiled_code") or node.get("compiled_sql") %}
+{% macro redshift__format_compiled_code(compiled_code) %}
     {% if not compiled_code %} {% do return(none) %}
     {% else %} {% do return(compiled_code.replace("%", "%%")) %}
     {% endif %}