A recent conversation with a professional (IT) friend, a Technical Project Manager brought this question back in our focus: When AI gets it wrong, who takes the blame? That exchange, combined with my own experience working with Dev Managers during a project, pushed me to explore this further. What follows is a concise synthesis of
When AI Gets It Wrong: Who Takes the Blame Read More »
Computing is no longer confined to centralized data centers. From smart home devices and industrial sensors to autonomous systems and edge gateways, billions of connected devices now operate closer to where data is generated, and often outside traditional information security (InfoSec) boundaries. This shift toward edge computing creates a basic cybersecurity challenge i.e. cyberattack attack
Cybersecurity at the ‘Edge’: Securing “IoT” and “Edge” Devices Read More »
I find it strange that today, if I am an IT executive, Technical Program Manager, PM, or Dev Manager, I am increasingly likely to face a familiar scenario; projects that once took months are now expected to be completed in weeks, “just deploy AI and results will follow”, even under aggressive deadlines. This expectation creates
Illusion of Efficiency: Why Faster Isn’t Always Smarter in Tech Read More »
No matter how much we try to sidestep this topic, question of “AI taking over human jobs” keeps surfacing in social and professional conversations. In many organizations, senior IT executives keep hearing from their finance teams that they could ‘cut costs’ by reducing headcount and using AI to perform those tasks. However, in my experience,
AI Will Not Replace Humans – However These 5 Behaviors Will Read More »
Recently, while researching on another AI topic, I noticed something interesting. Nearly every discussion is centered on AI models, GPUs, data, or prompting techniques, yet very few acknowledged technologies quietly connecting all of these pieces together. It became increasingly clear that every impressive AI capability, from drafting an email to generating an image or retrieving
APIs: A Quiet Glue Behind Every AI Feature We Use Daily Read More »
Listening to conversations about Artificial Intelligence (AI) across different forum, professional and personal, I sometimes find myself concerned about direction of discussion. My concern is not with technology itself. AI represents one of the most significant advancements of our generation and has tremendous potential to improve how we work, create, learn, and solve complex problems.
Using AI as Your Thought Partner, not a Thought Replacement Read More »
You may be thinking, why write about ITIL and Microsoft’s Operations Framework in 2026? I wrote this article because our technology industry finds itself at another inflection point. IT organizations are aggressively pursuing cloud modernization, automation, and artificial intelligence (AI) initiatives while facing economic pressures, evolving workforce models, and heightened expectations from customers, boards, and
I am pleased to announce the upcoming release of my fourth book in the CTRL-ALT series, CTRL-ALT-QA Testing, scheduled to launch on Amazon on July 17, 2026. This book represents our next logical step in a software delivery lifecycle. While software development often receives much of the attention, quality assurance (QA) testing are equally essential
Announcing My New Book: CTRL-ALT-QA Testing Read More »
During a recent conversation with a few seasoned technology professionals, including a Development Manager and a Technical Program Manager, the subject of backlog management surfaced alongside several other operational discussions. As we exchanged field experiences, it became clear that organizations often view backlogs through very different lenses, and those perceptions can lead to unintended consequences.
How to Effectively Manage Backlogs: Turning a Wish List into a Delivery Engine Read More »
Human Mistakes and Automation Bias Smart systems do not eliminate human error, they reshape it. Automation bias describes tendency to over-trust system outputs while ignoring conflicting signals. As system confidence increases, human skepticism often decreases. This creates new categories of failure: Moral Crumple Zones Human operators absorb blame when systems fail, even when their control
Smart Systems, Human Mistakes: Where Automation Meets Accountability Read More »
