Q13 of 21 · AI for testing
What is the plan-act-verify loop in agentic testing and when would you adopt it?
Short answer
Short answer: Plan-act-verify is the core cycle of AI testing agents: the agent plans the next action based on current state, executes it, then observes the outcome to plan the next step. Adopt it for exploratory regression of complex, frequently-changing UIs — not for high-stakes deterministic validation.
Detail
In a plan-act-verify loop: Plan: the agent receives the current page state (screenshot or accessibility tree) and a goal, and decides what action to take next. Act: it executes that action — click, fill, navigate. Verify: it evaluates whether the outcome matches the expectation and whether the goal is achieved or another plan step is needed.
This cycle repeats until the goal is met or the agent reports failure.
When to adopt: flows that change too frequently for scripted tests to stay current, exploratory testing of new features where the exact sequence is unknown, or broad coverage sweeps where scripted maintenance cost is too high.
When not to adopt: payment processing, authentication, compliance flows, or anything where non-determinism is unacceptable — and any check that must complete in under 30 seconds in a PR pipeline. See Agentic testing landscape and Agent cost and latency.