Agency levels: What’s the Difference? Let’s keep it simple: It’s not just reacting. It’s planning. And doing. That’s a big shift. Main Parts of Agentic AI Here are the four key areas: 1. Understanding the Goal Agentic AI tries to figure out what you want. It doesn’t just look at words. Hard to do? Yeah. […]

There’s a big gap. A divide, really. Two clear paths, this diagram shows. Two Roads, Very Different Outcomes AI adoption splits in two ways: 1. Top 1% : Strategy Comes First These folks? Planned, they are. Measured, too. 2. The 99% (Most Users): Try-and-hope Method Guess what happens next? Big Difference in Results Elite Users

Let’s get real – AI isn’t magic. You can’t just plug it in and expect miracles. Aspect Top 1% (Do’s) 99% (Don’ts) Strategy AI, they tie to real goals. Clear roles. Toss random tools around. Projects live in silos. Data Time they spend on clean, secure, trusted data. Data prep? Nah. Dirty data, all day.

Discover how elite AI workflows are empowering top professionals to rapidly transform ideas into tangible results, significantly boosting productivity, efficiency, and creativity across development, testing, project management and more

Like a phone You have one daily battery of energy. Recharged it is, with sleep, food, some exercise. Like a phone, your energy runs low fast if you use it wrong. Spend it you must, but wisely. Is it worth it? Most people, real help they do not offer. Advice comes from many, but know

It feels like we’re on the verge of another major transformation. Vertical AI agents are stepping in. Not just to save time but to fundamentally redefine business operations. By automating actual business workflows and slashing costs, these AI tools promise to enable faster, smarter, and more accurate results. But how do they stack up against

Microservices Architecture Microservices break big systems into bite-sized, independent chunks. Each chunk, or service, has a single job and often runs on its own machine. These services “talk” to each other through APIs or by sending messages. But why do this, you ask? No more “giant deployment day” stress—ah, the sleepless nights it saves! Plus,

Semantic Kernel – intro What exactly is this thing called Semantic Kernel that I’m talking about? How does it fit into the world of AI development? And most importantly, how can you start using it? Let’s take a closer look. Imagine a powerful tool that acts as the foundation and orchestrator of AI systems, helping

The rise of artificial intelligence has caused a lot of talk about its impact on many fields, including software architecture. In my view, AI doesn’t need to approach to software architecture that much. Architecture is about capabilities which are defined by business functions. This principle stays the same, no matter how technology changes. Understanding Autonomous

Exploring the Impact of AI on Global Workforce Understanding the Change with AI Agents Have you ever thought about how AI is changing the way we work across the industries? AI agents are smart systems that are meant to imitate human thinking processes, like learning, problem-solving, and decision-making. They are changing industries by making processes