Google Cloud Agent Builder
Overview
| Year | 2025 |
|---|---|
| Team | Google Cloud Data and Analytics AI |
| Product | Google Cloud BigQuery |
| Role | Lead Product Designer |
A user-friendly data analytics agent builder for better accuracy and easy sharing.
Summary
The Cloud Data Agent Builder gives data analysts a user-friendly tool to add advanced context engineering to a custom-built agent. The goal was to meet data experts where they were and give them the tools to build high-accuracy data agents that could be shared with their colleagues.
Currently in private preview, initial evaluations showed a promising +10-20% increase in agent accuracy when using the structured context of the builder.
2-column Layout
A familiar two-column agent-building design was used to align with other products in the Google ecosystem.
Metadata
Users can drill into an agent’s data sources to add rich metadata that boosts agent understanding of the data. AI-assisted context generation is provided to speed up the process.
SQL as Context
Users provide “golden” SQL queries to guide agents as they write SQL queries.
Suggested Queries
The system generates SQL queries based on the selected data sources. Users can verify and add the suggestions to their agent’s context.
Glossary Terms
Users can add terms specific to their business to increase agent understanding of internal vocabulary.
Testing
Once context is added, users can test their agent and iterate on their settings.
Agent Hub
Once saved or published, the agent appears in the agent hub, where users can start conversations or share their agent across platforms.
Data Studio
The agent can be shared onto less technical surfaces, like Google Data Studio, where their colleagues work.
Outcome
Currently in private preview, initial evaluations showed a promising +10-20% increase in agent accuracy when using the structured context of the builder.