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Stack Overflow Blog

The AI magic words From better privacy to our new ChatGPT plugin, here's what's new on Stack Overflow for Agents AI, JD, and other letters of the law AI cybersecurity is a cat and mouse game (Re)introducing Developer Story Java’s age is its AI superpower Scaling your money safely with AI How to build a secure-by-default AI coding agent Elevating security, control, and accessibility: Stack Internal 2026.6 The economics of agent scale: tokens, ROI, and building platforms for AI-first teams (Part 2) The good ol’ days of building Java When you keep AI Lean, you keep AI correct Inside LinkedIn's cognitive memory agent for agentic personalization Responsible AI adoption needs developer workflow design Dispatches from O'Reilly: The right amount of spec for agentic development Get rid of your CAPTCHA, the future of the web is bots AI Won't Replace Project Managers, But It is Reshaping How Work Gets Done Quantum-Augmented Applications: Integrating Quantum Subroutines into Classical Software Stacks From PHP to team lead of agents: rethinking judgment, review, and data with Google's Andi Gutmans (Part 1) What does an agentic SDLC actually look like? No Dumb Questions: What is AI context architecture? Why not just build your own? Solving integration woes with a hackathon Your tokenmaxxing is not valuemaxxing How to be fearlessly AI native Explorers, exploiters, and the myth of the 100x engineer Your MVP doesn’t need a Kubernetes cluster Dispatches from O'Reilly: The best risk mitigation strategy in data? A single source of truth What happens to the internet when robots act like humans? Your trusted knowledge layer: Introducing Stack Internal's new platform experience Developers are attached to tools because tools encode trust
Building an agentic SDLC with a QA engineering mindset
Phoebe Sajor · 2026-08-18 · via Stack Overflow Blog

Ryan welcomes Suneet Malhotra, Senior Manager of Test Engineering at Motorola Solutions, to chat about building end-to-end agentic SDLC pipelines using MCPs, using Cohen’s kappa to evaluate multiple LLMs-as-judges, and how you can improve requirements by shifting QA left through a specification enrichment stage immediately after the design phase.

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