The future of test automation isn’t about choosing code or no-code—it’s about combining both. Learn how this balanced approach reduces bottlenecks, speeds regression testing, and empowers QA teams to scale quality with confidence.| AI-Powered End-to-End Testing | Applitools
The newest updates to Applitools Autonomous and Eyes introduce AI-assisted test creation, built-in API and data support, and previews of upcoming MCP and mobile features.| AI-Powered End-to-End Testing | Applitools
The Model Context Protocol (MCP) is gaining traction as a smarter way to connect AI with testing tools. Here's what QA teams need to know—and how Applitools is putting it into practice.| AI-Powered End-to-End Testing | Applitools
Applitools Autonomous 2.2 introduces a smarter way to build and maintain automated tests—no code, no selectors, just natural language. With LLM test and data generation, visual comparisons across environments, and more, Autonomous 2.2 helps testers move faster with less friction and more confidence.| AI-Powered End-to-End Testing | Applitools
Not all AI testing is the same. This post breaks down the differences between assisted, augmented, and autonomous models—so you can scale automation with the right tools, at the right time.| AI-Powered End-to-End Testing | Applitools
Hybrid test automation—combining coded and no-code tools—is helping teams reduce maintenance, accelerate releases, and scale quality across skill levels. Learn how a balanced strategy leads to faster innovation, stronger collaboration, and smarter resource use.| AI-Powered End-to-End Testing | Applitools
No-code test automation tools are making test creation faster and more inclusive. Learn how AI-powered platforms empower teams to expand test coverage without adding complexity.| AI-Powered End-to-End Testing | Applitools
