Introduction Large Language Model (LLM) applications are evolving beyond single prompt-and-response setups. While basic Retrieval-Augmented Generation (RAG) scripts work well for simple Q&A over documents, real-world enterprise environments demand a much broader set of capabilities.In production, enterprise data is inherently fragmented: HR policies reside in unstructured PDFs, workforce metrics live in relational databases (SQL), and […]
Our Quietest Team Member: How AI Changed the Way I Think About Testing It doesn’t attend stand-ups. It doesn’t ask questions during meetings. It doesn’t even have a Microsoft Teams status. Yet somehow, it has become one of the busiest members of our QA team. It Joined the Team Without Anyone Noticing A few months […]
Introduction Large Language Models (LLMs) are incredibly powerful, but they have a major limitation: they are cut off from the real world. Imagine building a customer support bot. A user asks, “Where is my order #12345?” On its own, an LLM cannot fetch live database records, call a shipping provider’s API, or check inventory levels […]
Introduction In Part 1 of this series, we looked at Adobe Skills. Skills teach AI coding assistants Adobe’s recommended way of doing things. Skills tell the assistant how to do something. But on their own, they do not know what is happening in your running AEM instance right now. They do not know which bundle […]
Hook: Experience vs Content Today, content is everywhere. Movies, shows, reels, podcasts, live streams—audiences are overwhelmed with choices across platforms. The problem is no longer content availability; it’s content discovery and OTT user experience. Modern media platforms are not competing on content libraries alone anymore—they are competing on OTT personalization and user experience. This is why […]
Introduction When we see any LLM model names like GPT-4o, Claude 3 Sonnet, or LLaMA-2-7B-chat we wonder why companies give such weird names to their models. But let me tell you, these names have lots of meanings inside it. They provide lots of information about that model. Common Patterns: Suffix […]
Let me be upfront with you: I was sceptical. When everyone started talking about how Gen-AI coding assistants would “10x” developer productivity, I rolled my eyes. I’ve been building React Native apps for years and I’ve seen plenty of silver bullets that turned out to be more trouble than they’re worth. But over the past […]
Generative AIProject Management
GenAI is everywhere today; in boardroom discussions, client pitches, internal roadmaps, and strategy decks. There is excitement, curiosity, and sometimes anxiety. As leaders, many of us are suddenly expected to “lead GenAI initiatives” even when we are not the most technical person in the room. I’ve been there. In several Gen AI discussions, I found […]
Introduction As AI developers, we’re constantly deciding which tools best serve our projects—whether we’re building chatbots, automated reports, or document analysis platforms. Two frameworks have emerged as frontrunners: LangChain and LangGraph. While they complement each other, they solve fundamentally different problems.This guide explores what makes each framework unique, their ideal use cases, and how teams […]
