Writing about AI, low-code platforms, enterprise architecture and the engineering decisions worth arguing about — with the depth they deserve.
You type a question, hit Enter, and the answer streams in word by word. But what actually happens behind the scenes? I built an Enterprise AI Assistant from scratch — here is every single step, from keypress to rendered response.
Basic RAG breaks under complex, relational queries and returns dull Markdown walls. Here's how I rewired my AI app into a Supervisor–Worker multi-agent system, fused it with GraphRAG via Neo4j, and replaced static text with streaming Generative UI components.
I built a production-ready Enterprise AI Assistant using Retrieval-Augmented Generation (RAG) and Mistral LLM. Here’s the architecture, tech stack, and real-world use cases behind this scalable AI system.
This article explores the powerful intersection of Agentic AI and low-code platforms, with a spotlight on Appian’s latest 25.2 release.
Explore the game-changing features in Appian 25.2—from AI Agents and Process HQ to GridPlus and enhanced developer tools—designed to elevate enterprise automation and low-code development.
In a world flooded with technical jargon, my mission is simple: Decode technology. Empower minds. Build smarter.
By day, I'm an Appian developer architecting enterprise solutions. By night, I'm exploring GenAI, LLMs, and the frontiers of the modern web. Ai TechSavvy is where these worlds collide.
~1 post per week. No fluff. No roundups.