AI Observability

Auto Added by WPeMatico

From Exploration to Application: My Journey Building an AI-Assisted API Testing Tool

ADLC, ai, AI (Artificial Intelligence), AI Debugging, ai development, AI Development Lifecycle, AI in Software Development, AI Observability, Artificial Intelligence, CI/CD, DevOps & Automation, Intelligent Testing, Predictive Bug Detection, Software engineering, Software Quality Assurance, Spritle Blog, SpritleSoftware, Technology & Innovation, Technology Insights, Technology Trends

A few weeks ago, I started exploring how AI could support backend automation testing using Antigravity. My goal was simple—reduce the effort involved in writing, maintaining, and scaling API tests while improving overall efficiency. I began by experimenting with backend test execution using REST Assured, with Antigravity assisting me in generating and structuring test logic. […]

From Exploration to Application: My Journey Building an AI-Assisted API Testing Tool Read More »

AI Debugging in ADLC: Catching Production Bugs Before They Exist

ADLC, ai, AI (Artificial Intelligence), AI Debugging, ai development, AI Development Strategy, AI in Engineering, AI in Software Development, AI Observability, AI software development lifecycle, Artificial Intelligence, Bug Prevention, DevOps & Testing, DevOps AI, Intelligent Testing, Predictive Debugging, software development, Software Development Life Cycle, Software Quality, Spritle Blog, SpritleSoftware, Technology & Innovation

Introduction Production bugs are expensive—but the real cost isn’t just fixing them. It’s lost revenue, damaged trust, and engineering time spent firefighting instead of building. According to IBM’s Cost of a Data Breach Report (2023), issues caught in production can cost up to 15x more than those identified during development. The uncomfortable truth? Traditional debugging

AI Debugging in ADLC: Catching Production Bugs Before They Exist Read More »