Legacy test framework modernization with AI tooling

Challenge

A legacy test automation framework had grown hard to maintain: inconsistent style, uneven coverage from existing quality gates, and slow test development for new features.

Approach

The framework was refactored for structure and maintainability. The use and coverage of the existing linters and pre-commit hooks were expanded to make them more efficient and consistent. Reusable AI-agent skills and workflows were created together with other teams, supported by cross-team knowledge sharing. AI-assisted tools were built to accelerate test development, new-feature tests were added, and peers' merge requests were actively reviewed.

Outcome

A cleaner framework with consistently enforced checks, faster test development for new features, and shared AI practices adopted beyond a single team.

Article author: Andrei Olegovich