Over the past year, Prompt Engineering has been the darling of the GenAI world. Tweak your prompt, get a better answer. Add more detail, get more context. Sounds great, right? If you’ve ever tried building AI agents that go beyond answering one-off questions — like automating test scenarios, helping with workflows, or making decisions across tools — you’ve probably hit a wall. And that’s where Context Engineering comes in. It’s not just the next trend — it's the foundation of truly intelligent AI agents . Prompt Engineering: Great for Questions, Not for Thinking Let’s start with what prompt engineering is good at. You give an LLM a prompt like: “Generate test cases for the login functionality with username, password, and forgot password link.” And it delivers. Job done — right? But what happens when your application has: Dynamic changes in functionality Reuse of components across modules Test dependencies that evolve over sprints Or user preferences like tes...
A blog about my testing stories where I pen down my thoughts about test automation covering primarily Selenium, Playwright, Java, JS/TS, Rest Assured, Karate, Maven, TestNG, Postman, newman, Jenkins, Git, Azure DevOps, etc.