AAanchalinaanchalfatwani.hashnode.dev·May 31 · 13 min readWorking Effectively with AI Coding Assistants: Principles, Patterns, and Best PracticesAI coding assistants have moved far beyond autocomplete. They now generate functions, refactor systems, write tests, debug complex issues, and assist with architectural decisions. But despite rapid pr00
AAanchalinaanchalfatwani.hashnode.dev·Apr 30 · 6 min readDesigning Multi-Agent Systems: Patterns and ArchitecturesAI systems are evolving fast. We started with: simple prompts then Retrieval-Augmented Generation (RAG) then agents that can use tools Now, we’re entering the next stage: Multi-Agent Systems (MA00
AAanchalinaanchalfatwani.hashnode.dev·Mar 31 · 8 min readGuardrails for AI: Building Safe and Reliable LLM ApplicationsIntroduction: Why Guardrails Matter? Large Language Models (LLMs) have made it incredibly easy to build intelligent applications—chatbots, copilots, document assistants, and even autonomous agents. Ho00
AAanchalinaanchalfatwani.hashnode.dev·Feb 28 · 8 min readLangChain Explained: Architecture, Components, and Use CasesLarge Language Models (LLMs) changed software development forever. But using a raw LLM API alone quickly exposes serious limitations: No memory No access to external data No structured workflows N00
AAanchalinaanchalfatwani.hashnode.dev·Jan 31 · 8 min readVector Databases: A Complete Guide (Concepts, Use Cases, Advantages, and Limitations)1. Introduction As AI systems evolved—especially with the rise of machine learning, deep learning, and LLMs (Large Language Models)—traditional databases started showing their limits. Searching exact matches in rows and columns is great, but modern a...00
