Some of my favorite stories
Scroll down to see a few projects that give you an idea of how I approach my storytelling across mediums, from stage sessions to technical guides.
The common theme you’ll notice: taking what could have been a worn-out topic, and transforming it into a powerful, repeatable narrative that works well in multiple marketing channels.
PRODUCT LAUNCH
RAG Isn’t Enough
When Tecton, a feature platform focused on ML, expanded to generative AI offerings, I was responsible for the messaging that would establish Tecton’s POV on GenAI.
But everyone has commentary on GenAI. How do you make sure your company is the one to listen to? By staying focused on a strong opinion. Sounds like a no-brainer, but many brands lose the plot here.
My team focused on one story: RAG is an incomplete solution for personalized, up-to-date responses. We delivered this narrative through blogs, product landing pages, media outreach, and demos at developer events like MLOps Community.
STRATEGIC NARRATIVE
The drivable data stack
Alteryx was getting left out of the “modern data stack” and we needed to change that perception. As the technical PMM for data architecture, I led the charge to establish Alteryx’s place in the modern analytics workflow with a memorable POV.
Formula 1 drivers often complain that their car is “undriveable” when it’s not working right. I used this as my analogy for the modern data stack: it’s undriveable. It’s not working, because it’s not user-friendly for business users.
In an F1-themed session, I positioned Alteryx as the “steering wheel” — the easy-to-use interface for your “engine,” like the cloud data warehouse.
Everyone walked away remembering that Alteryx = the steering wheel.
PRODUCT DEMO
Predict ski ticket demand with Snowflake
As a technical PMM at Alteryx, I collaborated with ISV partners like Snowflake to tell end-to-end use case stories. But these can get lengthy and complex, which loses the audience.
To help tell the Alteryx + Snowflake story, I built a demo with a simple, relatable story: predicting ski lift ticket demand. How might a ski resort prepare data and use a model to see when to charge more for lift tickets during peak days? And why use Alteryx with Snowflake to do that?

Recently seen in:
- AWS Machine Learning Blog: Real value, real time: Production AI with Amazon SageMaker and Tecton
- Snowflake Blog: Machine Learning Made Easy: Q&A with Snowflake Head of Artificial Intelligence and Machine Learning Strategy Ahmad Khan
- Snowflake Developers YouTube: Prep A Ski Bookings Data Set Using The Snowflake Engine
- Databricks Data + AI Summit (stage session): Solve the Last-Mile Problem in Analytics with AI for Business Users
- Tecton Blog: GenAI Engineering Horror Stories (And How to Avoid Them)
- Tecton Blog: Why RAG Isn’t Enough Without the Full Data Context
- Tecton YouTube: Tecton 1.0 Launch
- Alteryx Blog: Solve the Last Mile of Analytics with Playbooks for Databricks
Media placements:
- TechCrunch: Per Diem raises $2.3M to help local businesses build subscription programs (client: Per Diem)
- CIO: Analytics in the cloud: Key challenges and how to overcome them (client: Qumulo)
- SiliconANGLE: A new path for unstructured data in a hybrid world (client: Qumulo)
- MIT Tech Review: Voice games are giving kids a break from screen time (client: Volley)
- TIME Magazine: COVID-19 Shutdowns Have Taken a Massive Toll On Elite Athletes’ Mental Health (client: Strava)
- Entrepreneur: IoT Can Give Your Retail Business a Competitive Edge. Here’s What You Need to Know. (client: Nutanix)
…and much more!




