For many QA teams, automation presents a challenge: how do you scale efficiently when team members have different levels of coding expertise?
Eric Terry, Senior Director of Quality Control at EVERSANA INTOUCH, shared how his team successfully adopted a hybrid automation approach—leveraging both coded and no-code automation to bridge skill gaps, improve test efficiency, and enhance collaboration.
For teams considering Applitools Autonomous, Eric’s journey offers a real-world example of how AI-powered, no-code automation can accelerate testing while making automation accessible to a broader team.
The Challenge: Skill Gaps in Testing Teams
QA teams often include a mix of experienced developers and manual testers with limited coding experience. This gap can create inefficiencies and limit test coverage.
Common challenges QA managers face:
- Manual testers want to contribute to automation but lack programming skills.
- Automation engineers spend too much time maintaining scripts rather than innovating test strategies.
Inconsistent automation practices lead to knowledge silos and increased maintenance overhead.
The Solution: An AI-Powered Hybrid Approach to Coded and No-Code Automation
Eric’s team adopted a hybrid strategy that leverages both coded and no-code automation tools, ensuring that:
- AI-powered no-code tools (like Applitools Autonomous) allow manual testers to create automated tests with minimal coding.
- Coded automation remains essential for complex test scenarios requiring deep customization.
- Teams focus on collaboration, mentorship, and upskilling rather than forcing a single approach.
Eric’s team reduced test maintenance by 40% by integrating AI-driven no-code automation while keeping developers focused on high-value coding tasks.
The Benefits of an Autonomous-First Approach
One of the biggest breakthroughs for Eric’s team was prioritizing Autonomous-first testing for repetitive and UI-driven test cases. This led to:
- Faster onboarding for manual testers wanting to contribute to automation.
- Significant reduction in test maintenance, as AI-driven automation adapted to UI changes.
- More streamlined workflows, with non-developers actively participating in automation.
Key benefits of AI-powered no-code tools:
- Faster test creation for repetitive workflows.
- Reduction in script maintenance by up to 60%.
- Empowering manual testers to contribute without coding expertise.
- Accelerated test cycles by running automated tests in parallel.
Real-World Example: EVERSANA’s No-Code Automation Success
- Challenge: The team had a mix of highly technical engineers and manual testers who wanted to contribute to automation but lacked coding skills.
- Solution: They implemented a no-code-first strategy, using Applitools Autonomous to allow non-coders to automate repetitive UI tests.
- Results: Faster test execution, reduced manual effort, and a more collaborative approach to QA.
Want to see how Applitools Autonomous can help your team bridge your skill gaps to scale test automation? Try a free trial today.
How to Get Started: Lessons from Eric Terry’s Team
For QA teams considering Applitools Autonomous, Eric’s experience provides a clear roadmap for success in scaling coded and no-code automation to boost test efficiency. His key recommendations include:
- Encourage cross-functional collaboration – Build mentorship programs where automation engineers support manual testers.
- Adopt an Autonomous-first mindset – Automate simple workflows first before investing time in complex scripting.
- Leverage AI-powered tools – Use visual testing and self-healing automation to minimize maintenance effort.
- Align automation efforts with business goals – Ensure test automation supports faster releases and higher product quality.
Learn more by watching Code or No-Code Tests? Why Top Teams Choose Both
FAQ: Scaling Coded and No-Code Automation
No-code automation allows non-developers—like manual testers or business users—to create and run automated tests. This expands the pool of contributors to QA efforts, enabling faster coverage without hiring additional engineering resources.
Yes. Tools like Applitools Autonomous use AI to adapt tests to UI changes, significantly lowering the time spent on script maintenance while preserving accuracy and reliability.
A hybrid approach lets teams use no-code automation for fast, repeatable tests while reserving coded automation for complex scenarios. This combination enables faster test execution, better resource allocation, and more scalable testing strategies.
Use no-code automation for repetitive, UI-driven workflows that require quick setup and minimal technical oversight. Reserve coded automation for complex logic, API testing, and highly customized scenarios that no-code tools may not support well.
Demonstrate quick wins—like reduced maintenance and faster release cycles—from pilot projects. Highlight how no-code solutions scale QA efforts without adding headcount, and show how they complement, not replace, existing engineering investments.
