Key outcomes
500 Cypress tests migrated to Playwright in 1 week
Tests automatically updated themselves after a full UI redesign – no manual work needed
Finished the UI redesign 30% faster and launched it ahead of schedule
About Engagement Agents
Engagement Agents is a SaaS platform that helps retailers unlock the marketing benefits already baked into their leases via their shopping center’ digital & physical retail media networks . By automating the submission, execution and tracking of marketing campaigns, the platform ensures retailers make full use of the marketing opportunitiesthey are already paying for.
Background
With a rapidly growing customer base, Engagement Agents depends on end‑to‑end test coverage to keep its mission‑critical workflow running smoothly. The team had accumulated hundreds of Cypress tests, but maintenance overhead and flakiness slowed every release. A major UI redesign was on the roadmap, and leadership wanted confidence that visual changes would not break core flows.
Problem
A brittle Cypress suite – more time was spent fixing selectors than building features.
Impending UI overhaul – the existing tests would fail en masse once the new design shipped.
Aggressive timeline – the redesign needed to go live without extending the release calendar.
Solution
Checksum generated a complete Playwright test suite using AI, replacing hundreds of flaky Cypress tests with faster, more reliable coverage in just one week. This let the Engagement Agents team spend less time fixing tests and more time building.
1. Lightning‑fast Cypress to Playwright migration
Checksum’s AI Playwright engine parsed the existing Cypress tests, generated functionally equivalent Playwright scripts, and plugged them into the existing CI pipeline. All 500 tests were ported in just 5 business days – with human review time measured in hours, not days.
2. Auto‑healing Playwright tests for the UI redesign
When the new UI hit staging, Checksum’s auto‑healing layer detected changed locators, text, and component structures. Tests self‑updated in real time, immediately validating every critical user journey. Developers received a green dashboard within minutes – no manual edits, no downtime.
3. Real-time feedback during the UI redesign
Checksum played a key role during the UI redesign by giving developers fast, reliable feedback on every pull request. Each code change automatically triggered the Playwright test suite, which was kept up-to-date by Checksum’s AI. This meant that as developers pushed UI updates, they immediately saw if something broke.
Bugs were caught early and often — sometimes within minutes of being introduced. This constant feedback loop helped the team fix issues before they snowballed and gave them confidence to keep pushing forward. Instead of slowing down to debug broken tests, developers stayed focused and shipped faster.
Results
Metric | Before Checksum | After Checksum |
Migration effort | N/A – stuck on Cypress | 500 tests migrated in 1 week |
UI redesign test fixes | Estimated 200+ hrs | Auto‑healed in real time |
Project timeline | Baseline | 30% faster |
Developer confidence | Low – flaky tests | High – reliable AI Playwright tests |
"Checksum turned what looked like a months-long test rewrite into a one-week migration. When our new UI landed, all the tests were already green — we launched 30% faster, with full confidence."
Sean Snyder, Founder and President, Engagement Agents
Why it worked
AI‑driven locator intelligence keeps Playwright tests resilient through DOM and style changes.
Automated Cypress to Playwright migration eliminates manual porting and speeds CI.
Continuous self‑healing means zero maintenance overhead and no flaky failures.
Next steps
Engagement Agents plans to scale coverage to edge cases and mobile flows using the same AI‑powered Playwright framework. If your team is facing a similar challenge, book a demo at checksum.ai and mention this case study.

Gal Vered is a Co-Founder at Checksum where they use AI to generate end-to-end Cypress and Playwright tests, so that dev teams know that their product is thoroughly tested and shipped bug free, without the need to manually write or maintain tests.
In his role, Gal helped many teams build their testing infrastructure, solve typical (and not so typical) testing challenges and deploy AI to move fast and ship high quality software.