AI – anoop.blog

September 3, 2026

Data-Driven Decisions: Explained Over a Drink

A few weeks back, over drinks with friends in Sydney, the topic turned to Beer vs Whiskey — which one is “stronger”?

Everyone agreed: “Beer is light, yaar. Whiskey, Brandy, Vodka — that’s the real stuff.” And on paper, they were not wrong — beer sits at 4-5% alcohol, while whiskey, vodka, and brandy sit much higher, around 35-42%. Case closed, right?

I said, “Wait a minute. Let’s not close the case yet.”

The Question Nobody Was Asking

Everyone was comparing the percentage. Nobody was comparing the quantity.

Think about it. When you drink whiskey, how much do you actually pour? A peg is usually 30ml, sometimes 60ml if you’re generous. But when you drink beer, you are not sipping 30ml from a shot glass. You are opening a full bottle — 330ml, 500ml, sometimes 650ml.

So the real question is not “which drink has more alcohol in it.” The real question is “which drink puts more alcohol in you.”

And that, my friends, is where the data tells a completely different story.

July 30, 2026July 30, 2026

How I Mercilessly Laid Off My Favorite Proofreader (Sorry, Honey!)

For years, I had a very specific, high-stakes ritual every time I finished writing a blog post about Azure. But I was bit lazy to do proof reading few times to correct it and make a good flow.

So, like any loving husband, I did what felt natural: I handed it over to my wife.

Now, you have to understand—my wife works in a completely different domain. Cloud architecture to her might as well have been ancient Greek. But bless her heart, she never hesitated. She’d sit there for hours, squinting at complex technical terms, patiently fixing my clunky sentences, and trying to make my Azure ramblings actually read like human English.

Did those technical blogs make any sense to her? Absolutely not. But she was a total team player.

The silver lining for her back then? I rarely wrote blogs. So her “unpaid proofreading side-hustle” didn’t completely ruin her work-life balance.

February 21, 2026February 23, 2026

From Rivers to Repositories: “Shifting Left” is Simplified

Once upon a time, a thriving town was built along the banks of a Great River. For generations, the town flourished, but as the population exploded, clean water became scarce. To keep the town running, the Mayor decided it was finally time to tap into the river’s massive current.

There was just one problem: The river water was thick with mud.

The Mayor summoned two experts, each proposing a radically different vision for the town’s future.

February 2, 2026February 2, 2026

The Pressure Cooker Whistle: Explaining My New Job

I am writing this from thousands of feet above, on my way to Seattle for Confluent’s Global Kick Off 2026.

It’s been three months since I joined. Looking back, leaving my previous role wasn’t easy. I was comfortable. I knew Azure like the back of my hand. Moving here meant leaving that safety net for a completely new technology stack. I have always loved technology, and I learned everything put in front of me. But the biggest change isn’t just the tech—it’s how I explain my job.

January 31, 2023January 31, 2023

Optimizing Design and Deployment Process with AI Guidance

We frequently ask questions to gather requirements and provide our designs and solutions. Many organizations standardize their questions for consistency among teams. Can chatbots handle these questions? Yes, AI services can be utilized to make decisions and trigger DevOps pipelines to deploy the desired design or service.

By using Infrastructure as Code (IAC), we can quickly deploy design templates using AI to assist in choosing the appropriate design. This allows customers to focus on workload migration instead of landing zone design. Although, not every customer is the same, for example, a secure Azure VNet hub and spoke design can be deployed initially and improved upon while testing non-critical workloads in the cloud. We can drive move from design workshop to design selection workshop where you are helping the customers to pick up one of best design available.

Another solution is deploying services on an existing subscription, where customers can quickly deploy VMs or PaaS services by answering a few questions posed by a chatbot, without waiting for a human response. This speeds up the deployment process and increases customer satisfaction.

In conclusion, by utilizing AI and chatbots, customers can avoid creating tickets and waiting for support, as they can immediately provision resources by answering questions and confirming with AI suggestions.

What do you think?