A few weeks ago, I shared Grocery Data Intelligence, a Data + AI app I built on Databricks Free Edition that helps grocery stores reduce stockouts, cut waste, and turn inventory data into daily actions, on r/databricks.
The goal was simple: help grocery stores reduce stockouts, reduce food waste, and make better daily inventory decisions.
The app uses a Bronze to Silver to Gold lakehouse pipeline, with an AI reasoning layer that suggests actions like reorder, discount, promote, or donate.
When I shared it, I was mainly hoping to get some honest feedback from the community.
That feedback helped me improve the app in a very practical way.
Denny Lee was one of the first people to respond. He appreciated the idea of connecting data and AI to build something actionable. He also gave useful feedback on the action flow and suggested that I document the architecture more clearly so others could understand and review it.
I made those changes the same day.
Then Youssef Mrini shared his thoughts. He appreciated how the app used Databricks Free Edition and Genie Code, and suggested exploring Lakebase for faster dashboard rendering and the Semantic Layer for a better natural language query experience.
That helped me rethink the read path and the Ask Data experience.
Sunmin Lee also reviewed the app and gave very helpful product feedback. She suggested simplifying the experience around fewer, stronger user journeys and creating a separate architecture page.
That feedback helped me restructure the app around three main flows:
Dashboard for visibility
Ask Data + AI for insights
Action Center for decisions
Another community member, datainthesun, also suggested using UC Metric Views to centralize business logic, which I added to the design.
Each round of feedback made the app a little clearer and more Databricks-native.
The post reached more people than I expected, including readers from the United States, India, the United Kingdom, and other countries. But the most valuable part was not the views. It was the quality of the feedback and the willingness of people to help.
Then came Data + AI Summit 2026 in San Francisco.
I had the chance to meet some of the same people who had helped me online.
"I met Denny Lee right after a DevConnect session at Summit. We talked about the app, context-aware AI, and what builders in the community are creating.
I also met Youssef Mrini on the Dev Connect conference floor and we connected in person after the Reddit discussion.
I also had the opportunity to meet Jonathan Frankle, Chief AI Scientist at Databricks, known for his groundbreaking Hypothesis research at MIT. Connecting with someone leading AI research at Databricks was a meaningful moment for me as someone building in the Data + AI space.
This experience reminded me why community matters.
A community is not only a place to ask questions. It is also a place to share what you are building, receive honest feedback, improve your work, and learn from people with real experience.
For me, this started as a small Reddit post. It became a better architecture, a better app, and a few meaningful conversations at Summit.
Thank you Denny, Youssef, Sunmin, Jonathan, datainthesun, and everyone who shared feedback and encouragement.
Grocery Data Intelligence is live here: https://grocerydataintelligence.com
Grateful for the learning, the feedback, and the community.
