diff --git a/production-pipelines/index.rst b/production-pipelines/index.rst
index c3b3696..a712308 100644
--- a/production-pipelines/index.rst
+++ b/production-pipelines/index.rst
@@ -2,7 +2,13 @@ Production Pipelines
 ====================
 
 Production pipelines is a CPG specific module for improving the interactions
-between Hail Batch, and metamist for processing genomics data
+between Hail Batch, and metamist for processing genomics data....
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Guides
+
+   targets_stages.md
 
 .. automodule:: cpg_workflows.workflow
    :members:
diff --git a/production-pipelines/targets_stages.md b/production-pipelines/targets_stages.md
new file mode 100644
index 0000000..ad51a57
--- /dev/null
+++ b/production-pipelines/targets_stages.md
@@ -0,0 +1,101 @@
+# Targets and Stages
+
+In production pipelines, stages process different types of targets: SequencingGroup, Dataset, Cohort, or MultiCohort. Understanding the characteristics of each target and the corresponding stage type is essential for building workflows effectively.
+
+## Targets Overview
+
+### SequencingGroup
+
+A SequencingGroup represents the sequence data from a single sample. It is effectively the result of running sequencing.
+
+Example:
+
+```json
+{
+    "id": "CPGAAAA",
+    "type": "genome",
+    "technology": "short-read",
+    "platform": "illumina"
+}
+```
+
+### Dataset
+
+A Dataset is a collection of SequencingGroups belonging to the same project. The terms Dataset and Project are used interchangeably at CPG, and each dataset has a 1:1 relationship with a project.
+
+Example:
+
+```json
+{
+    "id": 14,
+    "name": "fewgenomes",
+    "dataset": "fewgenomes",
+    "sequencingGroups": [
+        {"id": "CPGAAA"},
+        {"id": "CPGBBB"},
+        {"id": "CPGCCC"}
+    ]
+}
+```
+
+### Cohort
+
+A Cohort is a curated group of SequencingGroups that share common characteristics or criteria.
+
+Example:
+
+```json
+{
+    "id": "COH501",
+    "name": "ExomeCohortABC",
+    "description": "All exomes in Dataset A, B, and C, as of Batch 15 processed on 24/08/24",
+    "template": "TMPL12"
+}
+```
+
+### MultiCohort
+
+A MultiCohort is a collection of Cohorts. Unlike other target types, a MultiCohort is not stored or represented in metamist.
+
+Example:
+
+```json
+[ "COH123", "COH456", "COH675" ]
+```
+
+## Stages Overview
+
+Each stage in a production pipeline acts on a specific type of target. There are four types of stages, each designed to accommodate different targets:
+
+* SequencingGroupStage
+* DatasetStage
+* CohortStage
+* MultiCohortStage
+
+### How to Determine the Appropriate Stage Type
+
+The choice of stage type depends on the nature of the output produced by the stage:
+
+#### SequencingGroupStage
+
+**Use this stage when:** There is one unique output per SequencingGroup.
+
+**Example:** When running alignment, you produce a .cram file for each SequencingGroup.
+
+#### DatasetStage
+
+**Use this stage when:** There is one unique output per Dataset.
+
+**Example:** When running AnnotateDataset, which splits the MT by dataset and annotates dataset-specific fields.
+
+#### CohortStage
+
+**Use this stage when:** There is one unique output per Cohort.
+
+**Example:** When analyzing a group of SequencingGroups that share common characteristics, producing a single output per Cohort.
+
+#### MultiCohortStage
+
+**Use this stage when:** There is one output for the entire workflow run, which may involve multiple Cohorts.
+
+**Example:** JointCalling, which produces a VCF for all the GVCFs from all SequencingGroups. Note that a MultiCohort stage can run on a single Cohort or multiple Cohorts.