22.7What This Means for Your Career

Skills to Develop

1. AI agent architectures — ReAct patterns, multi-agent systems, tool use
2. Testing AI systems themselves — LLM evals (Ragas, TruLens, OpenAI Evals), RAG metrics, MCP/A2A flow testing; this is now explicit in QA job postings
3. Prompt/plan engineering for testing — writing effective specs and skill files
4. WebDriver BiDi protocol — the technical standard underneath
5. Token economics — understanding and optimizing AI costs as a first-class quality metric
6. CI/CD for AI workflows — running agent-driven tests in pipelines, reviewing healer patches

Skills That Are Declining

1. Manual selector management — refs, intents, and AI locators replaced it
2. Explicit wait strategies — actionability checks handle this
3. Page Object boilerplate — plans + seed tests replace class hierarchies
4. Browser-specific workarounds — BiDi standardization eliminates these

The QA Engineer of 2028

Instead of writing and maintaining test scripts, you'll:

• Define testing intent in natural language
• Curate AI-generated test suites and review healer patches
• Design evals for the AI features your product ships
• Manage AI test infrastructure costs
• Design test strategies that agents can execute
• Interpret AI-generated failure analysis

The job title might change from "QA Automation Engineer" to "AI Test Architect" or "Test Intelligence Engineer."