We do not regenerate an application from scratch every time a user visits it. We write code once, store it, and serve many requests from that stable implementation. End-to-end tests should follow the same pattern. Here’s how a healthy AI-assisted test workflow looks like:
☑️ Use AI during creation, not execution: use AI to explore features and draft initial tests, but keep it out of your actual test execution loop.
☑️Store behavior as code, not prompts: encode understood workflows into deterministic Playwright code to create durable artifacts that execute identically every time.
☑️ Treat tests as executable memory: build tests to act as institutional memory that preserves critical product decisions and survives team turnover or architectural refactors.
Treat your tests like production code. It really is as simple as that.