Ransomware crews now pivot across cloud accounts in minutes, phishing emails read like a colleague wrote them, and deepfake voices authorize wire transfers with eerie confidence, forcing security teams to choose between slow caution and fast mistakes. Against that backdrop, AI-enabled cybersecurity
Introduction to AI-Driven Testing in Fintech Payment rails rarely pause, risk models never sleep, and yet software changes ship constantly, so quality now depends on systems that learn where money, policy, and code will collide before customers ever feel the jolt. The shift under review is not
Context and Stakes Credentials multiplied faster than services could be secured, and pipelines turned into high-speed conduits for risk unless secrets were handled with rigor from commit to production. That pressure reshaped how teams think about identity, trust, and automation. In cloud-native
Metrics that promise safety by counting lines executed crumble when a missed permission check drains funds or delays medication, and that gap between comforting numbers and consequential reality sets the stage for a reset in how quality is planned, measured, and delivered in banking and healthcare.
Boardrooms are betting that an AI engineer can ship production code reliably, safely, and at scale, and that wager now underpins Cognition AI’s bid to raise a round that could value the company near $25 billion. The catalyst is Devin, an autonomous software developer that doesn’t just autocomplete
A New Pace of Software Risk An obscure configuration bug that once languished in a backlog for months can now be chained with a permissive log parser and an overlooked API edge case to yield a working exploit in a single afternoon. That is the promise—and the problem—unlocked when frontier AI is
