AI Development Lifecycle

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AI Code Generation Inside ADLC: How It Cuts Dev Time Without Cutting Quality

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Introduction Development timelines are shrinking, but expectations are rising. US engineering teams are expected to ship faster, iterate more often, and still maintain production-grade quality. According to GitHub’s 2025 developer report, over 70% of teams now use some form of AI-assisted coding, yet many still struggle to translate that into real delivery speed. Here’s the […]

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How AI Customer Support Apps Save 50% of Dev Time — and Keep Users Happy Longer

ADLC, ai, AI (Artificial Intelligence), AI & Technology, AI apps, AI chatbot, AI customer support, AI Development Lifecycle, AI in SaaS, AI Tools, Artificial Intelligence, Automation & Innovation, Chatbot automation, Customer Experience, Customer support automation, Product Engineering, SaaS Development, SaaS growth, Spritle Blog, SpritleSoftware, Support optimization, User retention

Introduction Customer support is no longer just a post-product function it’s becoming a core part of product experience. Traditionally, building support systems meant: Creating ticketing systems Writing FAQs Managing chat infrastructure Scaling support teams All of this takes months of engineering effort. But with AI customer support apps, teams are now cutting development time by

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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.

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ADLC vs Traditional SDLC: How AI Changes Requirement Gathering From Day One

ADLC, Agile vs ADLC, ai, AI (Artificial Intelligence), ai development, AI Development Lifecycle, AI in Software Development, AI Tools, Artificial Intelligence, digital transformation, product development, Product Engineering, Requirement Gathering, SDLC, software development, Software engineering, Spritle Blog, SpritleSoftware, Technology Trends

Introduction Most software failures don’t happen during deployment—they begin with poor requirements. Recent industry insights show that only around 30–40% of software projects fully succeed, while the majority face delays, cost overruns, or scope issues. Unclear, incomplete, or constantly evolving requirements remain one of the leading causes behind these failures. If you’re a CTO or

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