Systems | Development | Analytics | API | Testing

AI now sits inside most software, whether teams planned for it or not. A recent report from Stanford HAI found that AI adoption jumped from 55 percent in 2023 to 78 percent in 2024.

Agentic AI is now moving into quality assurance (QA), and its impact is undeniable. What used to be a human-only responsibility is now becoming a shared system of humans and intelligent agents that observe, reason, and act across the stack.

Traditional crowdsourced testing has always promised scale, but it’s often come with headaches.

When product teams decide to launch globally, crowdsourced testing is one of the most talked-about approaches. But for many engineering leaders, QA managers, and product owners, the big question is where and how it fits.

Most product teams today are very good at one thing: testing what happens when a user types a prompt. Hemraj Bedassee , Delivery Excellence Practitioner,

Cyberweek 2025 demonstrated something unmistakable: the way customers shop, choose, and pay has changed permanently.

For a long time, we spoke about “AI agents” like they were a future concept, something that might eventually book flights, run workflows, or make payments on our behalf.

Accessibility and localization often seem like separate disciplines, each with its own set of guidelines and goals.

Over the past few years, model providers have invested heavily in “guardrails”: safety layers around large language models that detect risky content, block some harmful queries, and make systems harder to jailbreak.