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In part one, I looked at why organizations need a new approach to MDR. The expectations around Managed Detection and Response (MDR) have changed. MDR is no longer measured only by monitoring coverage or response speed, but by how well it helps organizations reduce risk, support decision-making, and connect security operations to business outcomes. That shift raises an important question: if MDR is becoming more strategic, what still prevents organizations from realizing its full value?

Organizations need a new approach to MDR. Managed Detection and Response (MDR) is no longer judged only by how many alerts it triages or how quickly it responds to incidents. The market has moved beyond that baseline. Today, organizations are asking a different question: how does MDR help reduce business risk in a way leadership can understand and defend?

The World Cup is on and during the weekend, as I was watching a couple of games (and yes, also enjoying some appetizers) , I was reminded that the teams lifting the trophy aren’t always the most talented. They’re the best prepared. Let’s think about it for a minute.

The first half of 2026 has been a blur for application security. Agentic AI has moved from experiment to expectation, reshaping how software is written, reviewed, attacked, and defended. Across security, engineering, and executive teams, many are still trying to grasp what this shift really means in practice. As we kick off the second half of the year, one thing is clear: the agentic AppSec evolution isn’t slowing down. However, the path forward is coming into focus.

For years, manufacturers viewed track and trace primarily as a compliance initiative. The goal was straightforward: meet regulatory requirements, maintain records, and support product recalls when necessary. Today, that mindset is changing. Manufacturers are facing a very different operating environment—one shaped by supply chain disruption, counterfeit products, evolving regulations, sustainability commitments, and rising customer expectations for transparency.

At the Higher Colleges of Technology (HCT), we have always been more than just an educational institution; we are a cornerstone of the UAE’s national vision. Established in 1988, HCT is now the nation’s largest applied higher education provider, serving approximately 30,000 students and staff across 16 campuses. Our mission is clear: to prepare Emirati students for the modern workforce through technology-driven, industry-aligned programs.

Most organizations are hemorrhaging money on cloud resources they don’t need. Corporations waste over $200 billion annually on unused or idle cloud resources. For 2025, enterprise cloud infrastructure waste alone is projected to reach $44.5 billion, driven by mismanaged, over-provisioned, or idle resources. And the problem isn’t getting better: 52% of engineering leaders say the disconnect between FinOps and engineering teams is actively contributing to wasted cloud spend.

Somewhere in your content archive, there’s a video that answers the question your team spent last week trying to resolve. It might be an inspection recording, a product demonstration, a training session, or decades of broadcast footage. The answer exists. The problem is that your search bar has no idea the video does.

Functional testing just crossed a meaningful threshold. For years, the path from manual to automated testing has demanded significant time, technical expertise, and ongoing maintenance. Automation has remained constrained to a subset of tests, while most of the coverage stays manual, slow, and increasingly unsustainable.

OpenText Core Software Delivery Platform Functional Testing is a cloud-based functional testing solution built within the OpenText Core Software Delivery Platform. It gives QA teams the tools to design, schedule, and execute functional tests through AI-powered codeless scripting, model-based testing, and a digital lab for testing across devices, browsers, and environments. Over time, most organizations build up a large library of manual tests.