The stress associated with cybersecurity is everywhere: alerts from the security operations center, patching updates, the latest ransomware attack, zero-day exploits, the growing demands of governance and regulatory oversights from government agencies. The pressure on CISOs and their security teams can be intense, given how they are held responsible following a data breach or a successful ransomware attack that can trigger a law enforcement investigation. In some extreme cases, security leaders have been held criminally liable. The burnout associated with cybersecurity and stress on tech pros costs U.S. businesses about $626 million in lost productivity annually, according to a survey published by Hack the Box, a performance center platform provider. The results are based on two sets of interviews each involving more than 1,000 security leaders and practitioners in the U.S. and U.K. Beyond illustrating the stress CISOs and their teams are under, the results underscore why recruiting an

If you’ve spent any time in software development, you understand the importance of documentation. But for many tech professionals, writing and editing documentation is a time-consuming pain—and a task they could accelerate through judicious use of AI. But how can you most effectively use AI to complete documentation? Before we plunge into that, it’s important to differentiate some broad types of documentation, including: Process documentation (breaking down how you did something) Product documentation (here’s how it works; breaks down into system and user documentation, targeted at different audiences) Requirements documentation (where’s what we need!) Planning documentation (here’s how we’ll build it!) There are further breakdowns, of course, including: Technical specifications Product roadmaps Troubleshooting/QA guides Tutorials Standards documentation Metrics documentation System/sysdmin documentation It’s a lot, in other words, especially when you consider how each of these documen

Companies everywhere need tech professionals for all sorts of reasons, from thwarting cyberattacks to building the next generation of “smart” apps. But where are managers experiencing the biggest difficulties in hiring tech talent? The latest edition of Skillsoft’s C-Suite Perspective Report offers some key insights into that question, based on responses from 219 C-level executives who completed Skillsoft’s 2024 IT Skills and Salary Survey. As you can see from the following chart pulled from the report, cybersecurity topped the list of hard-to-hire tech specializations, followed (perhaps predictably) by artificial intelligence (AI) and machine learning, analytics, and cloud computing: For context, it’s important to remember that the overall tech unemployment rate dipped to 2.5 percent last month, according to the latest CompTIA analysis of U.S. Bureau of Labor Statistics (BLS) data; that’s notably below the general unemployment rate of 4 percent. Tech professions that enjoyed double-di