“Instead of treating each prompt as a one-off request, the new agent remembers what was asked earlier, including datasets, filters, time ranges, and assumptions, and uses that context when answering follow-up questions. This lets users refine an analysis progressively rather than starting from scratch each time,” Satapathy added.
Satapathy pointed out that this eases the pressure on developers to prebuild dashboards or predefined business logic for every possible question that a data analyst or business user could ask.
“Rather than encoding every scenario upfront, teams can let the agent interpret user intent dynamically, while still enforcing access controls, metric definitions, and governance rules already defined in BigQuery,” he said.
