Spot on. The biggest misconception I see with clients is treating AI testing tools as drop-in replacements for a testing strategy. The tool handles execution, but someone still needs to define what "correct" means for their specific domain. I've seen teams spend weeks configuring browser agents only to realize their flaky tests were a symptom of poor test architecture, not a tooling gap. The build-vs-buy framing here is really valuable — most teams would benefit more from investing in deterministic API-level tests first and layering AI agents on top for exploratory coverage.