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UX snapshot: Improving SQL Query Editor Experience at VMware
AI + AUTOMATION • PRODUCT DESIGN + RESEARCH
As a product designer at VMware, I focused on improving the experience of running and interpreting complex SQL searches. I led design efforts to make powerful network management tools more intuitive and accessible—especially for users working with dense or abstract data. My work involved user research, prototyping, and designing clear, meaningful visualizations that helped turn raw query results into actionable insights.
Our SQL query editor allows users to run complex queries using pre-built templates. However, two core issues have emerged that significantly impact usability:
Misleading Feedback: When users run queries with unmodified sample values (placeholders), the editor often returns no results. The current success icon suggests the query was valid and meaningful, which creates a false sense of correctness.
Poor Placeholder Visibility: Users have difficulty identifying which parts of a query are placeholder values versus actual parameters. This confusion leads to time-consuming troubleshooting and failed attempts to get the right data.
Our objective is to reduce user friction and improve query success rates by helping users more easily identify and fix ineffective queries. Ultimately, by decreasing the mean time to resolution (MTTR), we improve overall efficiency, reduce engineering support overhead, and enhance user satisfaction—especially for power users and analysts.
We redesigned aspects of the SQL query editor to address these challenges directly:
Updated Visual Feedback: We replaced the misleading success icon with contextual status messaging that distinguishes between "query complete" vs "query incomplete"
Clear Placeholder Styling: Placeholder values in query templates are now visually distinct (e.g., different color and interaction cue), helping users immediately recognize what needs to be updated before execution.
These changes work together to guide users toward successful queries faster, turning the editor from a passive tool into a proactive assistant—reducing roadblocks and empowering more efficient data exploration.
In rethinking the SQL query editor experience, I drew inspiration from both consumer-facing and technical tools to find the right balance between clarity and control.
Text Editors as Inspiration
I took cues from familiar tools like Microsoft Word and Grammarly—products that are great at giving contextual feedback without getting in your way. The goal was to help users spot and fix issues fast, without breaking their flow.
Technical Tools and Code Editors
I also looked at developer-focused tools like Visual Studio Code. These inspired some of the more structured elements—like syntax highlighting and subtle cues that let technical users stay in control.
User Testing Insights
One interesting takeaway: even though our users are quite technical, more consumer-style patterns consistently performed better in testing. Clear labels, friendly prompts, and familiar interactions made the editor feel more approachable—without dumbing it down.
