Writing about AI, low-code platforms, enterprise architecture and the engineering decisions worth arguing about — with the depth they deserve.
You're staring at five dashboards at 2 AM, trying to figure out why production is down. What if the first hour of investigation could happen automatically? I built an AI Incident Response Platform — here's why, and the architecture behind it.
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.
I build AI systems that ship. RAG pipelines. Multi-agent architectures. Production-grade backend design. That's what I do.
Nine years in enterprise software, hands-on with everything from Appian platform architecture to full-stack AI applications. Ai TechSavvy is where I write about what I've built and what I've learned.
~1 post per week. No fluff. No roundups.