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QMetry walkthrough: Test management, automation & AI-powered testing

Discover how QMetry streamlines test management with this comprehensive walkthrough covering requirements management, test design, test execution, automation, reporting, and AI-powered productivity features. Struggling with disconnected testing processes, manual test execution, and limited visibility into quality across your software development lifecycle? This complete QMetry tutorial shows testers, QA teams, and engineering organizations how to manage the entire testing workflow in a single platform, from requirements to release.

Your AI agent is fixing the wrong service

Everyone wants an AI agent factory in 2026. Autonomous agents fixing bugs and shipping features while you sleep. I’ve been building toward that myself. But the error rates don’t support the fantasy. The best AI coding agents in the world fix about 50% of real bugs on SWE-bench verified. Half the time they fail. And AI-generated code produces 1.7x more issues than human-written code.

API Gateway vs AI Gateway - What Actually Changed?

Kong's AI Gateway applies the same architectural pattern as the API Gateway — now governing LLM, MCP, and agent traffic at the infrastructure layer. Just as API gateways abstracted rate limiting, auth, and caching across microservices, AI gateways do the same for large language models and agents — with token budgets, semantic caching, and semantic routing replacing their REST equivalents. Kong breaks this into three layers: LLM Gateway, MCP Gateway for tool calls, and Agents Gateway for agent-to-agent traffic.#Shorts.

Stateful vs. Stateless Web App Design | DreamFactory

Last updated: May 2026 Stateful applications remember information about previous client interactions. Stateless applications treat every request as independent — no memory between calls. The choice between these two designs shapes how an application scales, how it handles failures, and increasingly how AI agents consume it.

SmartBear at Atlassian Team '26: A Recap of What's New with AI and Rovo

What did Atlassian Team ’26 reveal about the future of software quality and AI-powered delivery? In this recap from the event floor inside the Anaheim Convention Center, SmartBear shares key themes from the event, including Atlassian Rovo, the Teamwork Graph, AI-driven workflows, and how QA teams are adapting to faster, AI-assisted software delivery inside Jira. See quick highlights from the event floor, SmartBear’s latest Zephyr innovations, and how conversational AI and quality intelligence are becoming part of the modern software delivery workflow.

Tokens Per Watt Is the Real Limit on AI Revenue

Most AI revenue will flow through tokens — and the two bottlenecks are tokens per watt (energy cost) and tokens per second (throughput). Tokens per watt determines how much output you can generate from a fixed energy supply — already constrained and getting tighter. Tokens per second sets the ceiling on how fast that revenue can flow. Kong's AI Gateway optimizes both at the connectivity layer: semantic caching and semantic routing increase token output without adding watts or latency.#Shorts.