The incorporation of AI into engineering work — through code completion, test generation, refactoring assistance and documentation support — continues to drive rapid gains in team productivity. As organizations expand their use of AI, they expect the velocity of deliverables to accelerate as well. However, those early gains are offset by increased security reviews, unresolved compliance questions and growing code-review workloads that many don’t account for. That slowdown points to how AI is being integrated into existing engineering processes, rather than limitations in the tools themselves. Engineers use agentic AI tools to ship faster, but many organizations lack the governance and oversight necessary to effectively manage how those AI tools are being used. Prompts sent through ungoverned agentic AI services lack consistent tracking, auditability and enforcement. This creates uncertainty and risk, leading leadership to worr...
People are used to digital services operating immediately, across various places, devices and systems. Should something break down, it is usually obvious to those operating the system. The crucial element is how fast companies can recover, and the key metric for digital stability is called mean time to recovery (MTTR). See how companies can reduce it to protect revenue, maintain trust and ensure consistent business activity. Outages are now Customer-Visible Events Customer interfaces often signal problems before companies know what is wrong. When an e-commerce transaction stops or a video stream pauses, users notice these issues immediately. Looking at companies such as Netflix or Amazon, where service dependability is the key requirement, makes people assess problems in a certain way. Online feedback, reviews and direct messages make these issues easier to spot. An issue, once narrowed to internal dealings...