Ai for Business

Image by Rajashree Rajadhyax It was the end of a long day, and I'd been focused on a challenge common to my work: getting an AI to align with a client's specific vision. This constant push and pull is the story of my life with AI—it's an incredible tool that amazes me one moment and drives me crazy the next. When I'm working with AI for my clients and also for my own projects, I can't help but wonder: are creativity and unpredictability two sides of the same coin? On one hand, I think AI is incredibly creative. It helps me generate all kinds of cool stuff—images, music, videos, whatever I need. It helps me find things, write a quick poem for a special event, or summarize long articles I don't have time to read. When I give it free rein, it really shines. I love how creative it is and I'm totally happy with the results. But then, there's the other side of the coin. The very same AI can be a source of significant challenge when I'm working on a client ...

  AI Agents Explained. Image by Rajashree Rajadhyax Everyone’s using chat companions like Chat GPT, Perplexity, Claude and the like. You’ll agree that we all find them useful in many ways. Just as we were getting a grip on generative AI, the term AI agents started gaining popularity.  Everybody’s talking  about "AI agents" now, but most of the time, it's either overhyped, vague, or poorly defined. Every week, there’s a post claiming, “We built an AI agent that will change your life.” But peel back the marketing gloss, and you’ll find a wide range of systems,  from simple scripts that run a series of prompts, to complex multi-step, self-directed workflows, all being labelled “agents.”  The truth is: AI agents aren’t a single thing with a rigid definition. They can have different levels of independence, and once you see that range, all the buzz feels clearer. The Core Idea of an AI Agent At its heart, a software can be called an ‘AI agent’ if it can: 1. Perceive ...

  Child playing with simple toys Just yesterday, I read in the news that OpenAI—the company behind ChatGPT—is now joining hands with toy-maker Mattel. Yes, the same Mattel that gave us Barbie and Hot Wheels. As I read it, I smiled, thinking of my own childhood. I used to love playing with Barbie, and those tiny Hot Wheels cars were so much fun. Now, it seems those very toys will come with AI inside them. I still remember how my sister and I would spend hours making up stories around our dolls. Our imagination would run wild. The toys themselves were simple, but the worlds we created were magical. Children love toys, no doubt. But they don’t really need fancy, high-tech ones. They can play with almost anything—a spoon, a piece of cloth, a cardboard box—and turn it into something special. For them, everything is a toy if it helps them imagine. Toys may look like small things, but they play a big role. They help shape who a child becomes. Think about your own childhood. Was it a soft ...

Components of a good prompt. Image by Rajashree Rajadhyax This is the second article in the three-part series on prompt engineering. In the first part, we explored various prompting techniques—different ways you can instruct AI to generate responses. The article introduced some theoretical approaches to interacting with AI, highlighting how different techniques influence the kind of output you receive. You can read the first part [here]. In this part, we’ll shift our focus to the building blocks of a prompt—the essential elements that make up a clear, effective instruction. Let’s revisit what a prompt is At a basic level, a prompt is simply the way you tell AI what you expect from it. It’s your way of saying, “Hey, here’s what I need—please respond accordingly.” But while it may seem as simple as typing a question, what you say and how you say it can drastically influence the output you get. This is because AI models, like LLMs (Large Language Models), understand prompts by recognizing...