AHAshwin Hegdeinashwinhegde19.hashnode.dev·Mar 13 · 3 min readI won my first hackathon by building something I barely understoodA few weeks ago I was using OpenClaw to set reminders and run basic cron jobs. That's it. Nothing impressive. Then I walked into the HSRFC x OpenClaw Builders event in Bengaluru. 4 hours, real constra00
AHAshwin Hegdeinashwinhegde.hashnode.dev·Apr 22, 2025 · 7 min readMake Your AI Smarter with Step-Back, Chain of Thought, and HyDE PromptingOverview AI is becoming a powerful tool for solving complex problems, but what if it could think more like a human? Imagine AI breaking down a problem step by step, thinking about the broader context before diving into the details, or even imagining ...00
AHAshwin Hegdeinashwinhegde.hashnode.dev·Apr 21, 2025 · 5 min readEnhance Answer Quality with Smarter RAG Through Reciprocal Rank FusionOverview In this post, we’ll explore another smart way to boost the quality of search results when working with large text datasets, using a method called Reciprocal Rank Fusion (RRF). Just like Fan-Out Retrieval from our previous blog, we’ll use Lan...00
AHAshwin Hegdeinashwinhegde.hashnode.dev·Apr 20, 2025 · 4 min readMaster Advanced RAG Techniques with Parallel Query Retrieval Using LangChain, Gemini, and QdrantOverview IIn this post, we’ll explore a smart way to boost the quality of search results when working with large text datasets, using a method called Fan-Out Retrieval (also known as Parallel Query Expansion). We'll combine tools like LangChain, Goog...00
AHAshwin Hegdeinashwinhegde.hashnode.dev·Apr 18, 2025 · 4 min readUnderstanding the RAG Workflow: Step-by-Step Guide with Diagrams and CodeRetrieval-Augmented Generation (RAG) is a powerful AI framework that lets language models answer questions based on your own documents—like PDFs, manuals, or knowledge bases—by combining search and generation in one seamless pipeline. In this post, w...00
