Modern software testing is built on a fragile assumption: correct behavior is repeatable. For deterministic code, that assumption mostly holds. But for autonomous agents like Github Copilot Coding Agent (aka Agent Mode), especially as we explore the frontiers of integrated “Computer Use,” that assumption breaks down almost immediately.  As agents move beyond simple code suggestions to interacting with real environments like UIs, browsers, and IDEs, correctness becomes multi-path. Loading screens can appear or disappear, timing shifts, and multiple valid action sequences can lead to the same result. Unless our GitHub Actions workflows are robust enough to account for this variability, it’s common for an agent to succeed at a task while the test still fails—a “false negative” that halts production.  This blog post explores how to move past brittle, step-by-step scripts and toward an independent “Trust Layer” for agentic validation.…