Technical articles on AI agents, agentic systems, MCP, LangGraph, LangChain, RAG, LLM APIs, automation, full-stack engineering, and security-aware implementation.
Showing 29 of 29 posts
Artificial Intelligence AI has made remarkable strides in recent years, but one of the perplexing challenges it faces is the phenomenon known as "hallucinations." In the context of AI, hallucinations refer to...
Creating embeddings with LangChain and LLM APIs is a practical way to transform text into numerical representations for semantic search, RAG, and AI workflows.
Introduction LangChain tools are what allow a language model to go beyond text generation and become an actionable system . Instead of only responding with natural language, an LLM can use tools to fetch data,...
Introduction In the rapidly evolving landscape of artificial intelligence, understanding how to orchestrate Large Language Models LLMs effectively is becoming a critical skill for developers and data scientists....
Introduction Retrieval-Augmented Generation RAG has become a standard approach for grounding large language models LLMs with external data. However, most implementations remain simplistic, typically following a...
