Over 40% of all AI-generated code contains a security vulnerability. While teams use these tools to ship software fast, this speed comes at a high price. Most of this code is deployed without essential guardrails, such as code reviews or automated security testing, creating a massive shadow attack
Your business dashboard displays a 90% success rate for a key automated process. It looks like a win. But behind that comforting metric, your development team is grappling with the fallout from the other 10%. This is the “unhappy path,” and it’s where your operational efficiency goes to die. This
For decades, business intelligence has operated on a simple premise: ask the right technical questions to get the right reports. But this model has a fundamental bottleneck. Formulating the "right questions" often requires deep data expertise, creating a costly and frustrating delay between inquiry
For decades, Java’s core promise has been “ write once, run anywhere .” That sentiment, however, has always come with an asterisk. It applied to servers, desktops, and Android devices, but it consistently broke against the hard wall of Apple’s iOS ecosystem. The technical and philosophical divide
Software systems are becoming increasingly complex. For example, modern cars have over 150 electronic control units , making it difficult to understand applications or infrastructure solely through source code or traditional monitoring. As digitalization advances, businesses require comprehensive
Unmanaged data quietly drains budgets and increases risk, with 69% of organizations experiencing cyberattacks from poor asset management. Yet, many businesses still view software asset management as a compliance task rather than a strategic tool. Modern asset management cuts costs, closes security
