Atlas › 03 Agentic Testing Architectures › Mapping ReAct to CLI Browser Commands☰ Read as one page
Mapping ReAct to CLI Browser Commands
2.1Bridging Theory and PracticeThe ReAct pattern is abstract: Observe, Think, Act, Evaluate. To make it concrete, we need to map each phase to actual commands that an AI…2.2The Phase-to-Command MappingThe observation phase is about gathering state. The CLI's key design choice: state lands on disk, and the agent reads only what it needs:2.3A Complete ReAct Test Using the CLIHere is how an agent thinks through a login test using the ReAct loop:2.4Implementing the Agent in PythonNote what the disk-first design does to this loop: the full snapshot only enters the LLM prompt when observe() deliberately includes it. A…2.5Error Recovery PatternsOne of the most powerful aspects of mapping ReAct onto a CLI is the agent's ability to recover from errors:2.6Performance Considerations2.7The Same Mapping in Commercial SDKsThis phase-to-command mapping is not unique to the Playwright CLI — it is exactly what production agentic browser SDKs expose. Stagehand…2.8Key TakeawayThe Playwright CLI provides a natural mapping from the abstract ReAct pattern to concrete browser automation commands: observation via…