diff --git a/docetl/__init__.py b/docetl/__init__.py
index 8b996359..419d37d4 100644
--- a/docetl/__init__.py
+++ b/docetl/__init__.py
@@ -1,4 +1,4 @@
-__version__ = "0.1.5"
+__version__ = "0.1.6"
 
 from docetl.runner import DSLRunner
 from docetl.builder import Optimizer
diff --git a/docs/operators/split.md b/docs/operators/split.md
index 9f2cca33..2ae62d4d 100644
--- a/docs/operators/split.md
+++ b/docs/operators/split.md
@@ -11,7 +11,7 @@ Some common scenarios where the Split operation is valuable include:
 - Breaking down large legal documents to extract relevant clauses or sections
 - Preparing long-form content for summarization or topic extraction
 
-## 🚀 Example: Splitting Customer Support Transcripts
+## 🚀 Operation Example: Splitting Customer Support Transcripts
 
 Here's an example of using the Split operation to divide customer support transcripts into manageable chunks:
 
@@ -95,7 +95,7 @@ The Split operation generates multiple output items for each input item:
 3. **Topic Extraction from Research Papers**:
    Divide research papers into sections, use a map operation to extract key topics from each section, then apply a reduce operation to synthesize main themes across the entire paper.
 
-## Example: Analyzing Customer Frustration
+## 🚀 End-to-End Pipeline Example: Analyzing Customer Frustration
 
 Let's walk through a complete example of using Split, Map, and Reduce operations to analyze customer frustration in support transcripts.
 
diff --git a/pyproject.toml b/pyproject.toml
index d014aaf7..465736c1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "docetl"
-version = "0.1.5"
+version = "0.1.6"
 description = "ETL with LLM operations."
 authors = ["Shreya Shankar <shreyashankar@berkeley.edu>"]
 license = "MIT"