Category: GPT-5

  • Agentic Systems vs MCP Systems

    ✍️ 𝐁𝐲 𝐀𝐛𝐡𝐢𝐬𝐡𝐞𝐤 𝐊𝐮𝐦𝐚𝐫 | #𝐅𝐢𝐫𝐬𝐭𝐂𝐫𝐚𝐳𝐲𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 Clear Differences, Use Cases, and When to Choose What 🧠 1. What is an Enterprise Agentic System? An Agentic System is an AI setup where the LLM behaves like an intelligent worker (an “agent”) that can: It focuses on autonomy and orchestration of tasks using LLM intelligence. Enterprise Agentic…

  • How Search Works in Vector Databases – From “Top Gun” to “Maverick”

    ✍️ 𝐁𝐲 𝐀𝐛𝐡𝐢𝐬𝐡𝐞𝐤 𝐊𝐮𝐦𝐚𝐫 | #𝐅𝐢𝐫𝐬𝐭𝐂𝐫𝐚𝐳𝐲𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 🧠 Why Do We Need Vector Databases? Traditional databases store structured data (rows & columns) and perform keyword or pattern matching.But AI systems don’t think in keywords — they think in meanings. For example: That’s why modern AI systems like ChatGPT, RAG pipelines, and semantic search engines rely on…

  • Building an End-to-End Vector Search Pipeline with Azure + LangChain

    ✍️ 𝐁𝐲 𝐀𝐛𝐡𝐢𝐬𝐡𝐞𝐤 𝐊𝐮𝐦𝐚𝐫 | #FirstCrazyDeveloper 💡 Why This Matters More Than Ever Traditional keyword search engines match exact text terms but often fail to capture semantic meaning. For example, searching for “legal agreement termination” should also surface results mentioning “contract cancellation”, even if the exact words differ. This is where Vector Search shines. By…

  • Event-Driven Agentic Architecture: From Events to Intelligence

    ✍️ By Abhishek Kumar | #FirstCrazyDeveloper In today’s world of intelligent automation and AI-driven operations, event-driven agentic systems are becoming the architectural backbone for enterprises integrating AI, microservices, and human workflows. These systems are not just reactive—they are autonomous, adaptive, and context-aware, capable of executing tasks intelligently across diverse environments. This blog explores the transformative…

  • Top AI Language Models in Action: Real-World Examples with Python & C#

    ✍️ By Abhishek Kumar | #FirstCrazyDeveloper Artificial Intelligence has rapidly evolved over the last decade, and Large Language Models (LLMs) have become the core drivers of this revolution. From OpenAI’s GPT family to Meta’s LLaMA, Anthropic’s Claude, Google’s Gemini, and more — each ecosystem brings unique capabilities tailored for developers, researchers, and enterprises. In this…

  • Supercharging Your Azure OpenAI MCP Agent with LangChain (Python & C#)

    ✍️ By Abhishek Kumar | #FirstCrazyDeveloper As Generative AI takes the spotlight across industries, the need for structured, multi-step reasoning and tool-enhanced agents is more critical than ever. In this blog, I’ll explain how you can integrate LangChain with your Azure OpenAI-powered MCP Agent—not just in Python, but with a C# equivalent, too. This blog…

  • AI Agents: Where GenAI Becomes Practical – A Developer’s Guide

    ✍️ by Abhishek Kumar | #FirstCrazyDeveloper “LLMs talk. RAGs talk smarter. AI Agents act. Agentic AI collaborates.” Generative AI is no longer just about writing poems or drafting emails. It’s evolving into intelligent systems that plan, reason, take actions, and even collaborate to solve real-world problems. This blog is your step-by-step guide to understanding the…

  • Building a Production-Ready AI Platform End-to-End on Azure

    By Abhishek Kumar — #FirstCrazyDeveloper Artificial Intelligence is moving fast. But building an AI prototype and building a production-grade AI platform are two very different challenges. In this blog, I’ll break down how developers can architect such a system using Azure with step-by-step real-world examples. 🔑 1. Cloud Infrastructure — The Foundation Every reliable AI…

  • Agentic AI Architecture Explained: 8 Powerful Building Blocks for Intelligent Agents

    by Abhishek Kumar | FirstCrazyDeveloper Artificial Intelligence is moving beyond static models. We are now in the Agentic AI era, where systems are not just predicting text or images but acting as autonomous problem solvers. These AI agents combine reasoning, planning, memory, and adaptability to tackle complex, real-world workflows. But what makes these agents truly agentic?The…

  • The AI Agent Playbook: Six Stages Every Developer Must Know

    by Abhishek Kumar | FirstCrazyDeveloper Building an AI Agent is not just about coding a model—it’s about creating an intelligent system that is purposeful, ethical, and continuously improving. To achieve this, the development process must follow a structured path that blends business strategy, technical design, testing rigor, and user-centered feedback loops. Let’s break down the six…