Jobber Automated 80% of Mobile Smoke Tests Using Natural‑Language AI

Introduction

For Jobber, providing seamless, reliable mobile experiences for home service professionals is mission-critical. As the company scaled operations and release velocity, manual mobile testing became a bottleneck in both regression validation and performance monitoring.

In 2024, Jobber partnered with GPT Driver to explore AI-driven mobile automation for faster, more scalable testing.

The Challenge

Jobber’s mobile teams faced two major challenges:

• Manual testing bottlenecks: Smoke tests for iOS and Android were time-consuming and resource-heavy.

• SDK performance testing gaps: Reliable test automation was needed to feed performance metrics into dashboards, requiring precise control over flows on real devices.

The Solution: Implementing GPT Driver

GPT Driver’s AI automation platform enabled Jobber to:

• Create tests in natural language, reducing the burden on engineers and QA.

• Execute tests across cloud simulators and physical device farms.

• Broaden testing participation, opening collaboration between product and engineering teams.

• Integrate AI-driven automation into CI/CD pipelines.

Tailoring GPT Driver to Engineering Workflows

Working closely with GPT Driver, Jobber identified and resolved key hurdles:

• SDK stability: Initial coordinate tapping issues on iOS devices were traced to case sensitivity in configurations, a simple fix that improved reliability.

• Execution speed: Faster local execution became critical to improve iteration cycles during test development.

• SDK and web app synergy: Jobber surfaced the need for exporting tests from the natural language web interface into TypeScript SDK code, bridging workflows between product managers and engineers.

The Results

Since adopting GPT Driver, Jobber has achieved measurable improvements:

• Over 80% of mobile test cases automated, reducing manual testing overhead.

• Full activation of iOS smoke testing, helping the engineering team hit key quarterly goals.

• Faster feedback loops during test creation, boosting productivity.

• Reliable data pipelines for mobile performance dashboards, improving real-time visibility into app behavior.

Future Outlook

As GPT Driver evolves, Jobber sees opportunities for deeper integration between product and engineering workflows, including natural language-to-code export and additional SDK optimizations.

The partnership positions Jobber among the early adopters of AI-driven testing practices, creating benefits for both internal teams and customers.

Conclusion

GPT Driver has enabled Jobber to streamline and scale mobile testing efforts, from smoke tests to performance flows, with far less manual work.