# RAGyfied

> RAGyfied explains LLMs and AI like system design. In-depth blogs, curated learning paths, industry news, tutorials, and tools for AI engineers building with RAG, agents, and open-source models.

RAGyfied is a technical publication for engineers who think in systems. We cover Retrieval-Augmented Generation (RAG), large language models (LLMs), agentic AI, transformer architecture, and the open-source AI ecosystem. Content is written by engineers, for engineers.

## Core Sections

- [Home](https://ragyfied.com/): Featured articles, latest news, and curated learning content
- [Blogs](https://ragyfied.com/blogs): In-depth technical articles on RAG, LLMs, agents, and AI engineering
- [LLM 101](https://ragyfied.com/llm-101): Curated learning path from neural networks to production RAG systems
- [LLM Concepts](https://ragyfied.com/llm-101-concepts): Beginner-to-intermediate explanations of core LLM concepts
- [News](https://ragyfied.com/news): Latest AI and LLM industry news and analysis
- [AI Tools Directory](https://ragyfied.com/ai-tools-directory): Curated directory of AI tools for developers
- [AI Dev Tools Directory](https://ragyfied.com/ai-dev-tools-directory): Developer-focused AI tooling
- [Tutorials](https://ragyfied.com/articles/build-your-own-rag): Step-by-step AI engineering tutorials
- [About](https://ragyfied.com/about): About RAGyfied and the team
- [Contact](https://ragyfied.com/contact): Contact RAGyfied

## Key Articles — RAG & Retrieval

- [What is RAG?](https://ragyfied.com/articles/what-is-rag): Beginner-friendly introduction to Retrieval-Augmented Generation
- [How RAG Works](https://ragyfied.com/articles/how-retrieval-augmented-generation-works): Deep dive into RAG architecture and mechanics
- [Inside a RAG Pipeline: The 5 Building Blocks](https://ragyfied.com/articles/building-blocks-of-rag-pipelines): Embeddings, vector DBs, retrieval, LLMs, and generation
- [RAG vs Fine-Tuning](https://ragyfied.com/articles/rag-vs-fine-tuning): When to use each approach
- [GraphRAG Explained](https://ragyfied.com/articles/what-is-graphrag): Knowledge graph-enhanced retrieval
- [Beyond RAG: Gemini File Search Tool](https://ragyfied.com/articles/what-is-gemini-file-search-tool): Managed RAG as a service
- [Build Your Own RAG Pipeline](https://ragyfied.com/articles/build-your-own-rag): Complete beginner's tutorial

## Key Articles — Agentic AI

- [What is Agentic AI?](https://ragyfied.com/articles/agentic-ai-rag-agents): From Q&A to goal-directed systems
- [Agentic Design Patterns](https://ragyfied.com/articles/agentic-design-patterns): ReAct, planning, reflection, tool use, multi-agent architectures
- [MCP 2.0 Explained](https://ragyfied.com/articles/what-is-mcp-2): Model Context Protocol for AI agents
- [Prompt Injection Security](https://ragyfied.com/articles/what-is-prompt-injection): Critical security for RAG engineers
- [OpenClaw Security Case Study](https://ragyfied.com/articles/openclaw-moltbot-clawdbot-viral-ai-agent): Agentic AI security vulnerabilities

## Key Articles — LLM Concepts

- [Transformer Architecture Explained](https://ragyfied.com/articles/what-is-transformer-architecture): Where 7B parameters come from
- [How Attention Works](https://ragyfied.com/articles/attention-is-all-you-need-explained): Understanding LLMs and transformers
- [Why LLMs Hallucinate](https://ragyfied.com/articles/why-do-llms-hallucinate): Technical causes and defenses
- [How Reasoning Works in LLMs](https://ragyfied.com/articles/how-reasoning-works-in-llms): Chain-of-thought to reasoning agents
- [AI Embeddings Explained](https://ragyfied.com/articles/what-is-embedding-in-ai): From text to vectors
- [What is Tokenization?](https://ragyfied.com/articles/what-is-tokenization): How LLMs read text
- [LLM Temperature Explained](https://ragyfied.com/articles/what-is-llm-temperature): Creativity vs consistency
- [Context Windows in LLMs](https://ragyfied.com/articles/what-are-context-windows): Why context size matters
- [LLM Quantization Guide](https://ragyfied.com/articles/what-is-quantization): FP32 vs Int8 vs GGUF
- [BERT vs GPT](https://ragyfied.com/articles/bert-vs-gpt): Encoder vs decoder model architectures
- [Semantic Search Explained](https://ragyfied.com/articles/what-is-semantic-search): From keywords to meaning

## Key Articles — AI Industry & Strategy

- [AI Citations & AEO Strategy](https://ragyfied.com/articles/ai-citations-aeo-strategy): Getting cited by ChatGPT, Perplexity, and Gemini
- [The Future of Apps in the AI Era](https://ragyfied.com/articles/future-of-apps-ai-era): AI as the universal interface
- [What is AI-Native Software?](https://ragyfied.com/articles/what-is-ai-native-software): Intent-first, autonomous applications
- [Google Universal Commerce Protocol](https://ragyfied.com/articles/google-universal-commerce-protocol): Developer guide and integration
- [What is Gemma 4?](https://ragyfied.com/articles/what-is-gemma-4): Google's open-weight model explained

## Optional

- [Entity Map](https://ragyfied.com/entities.txt): Semantic knowledge graph of site entities and topic authority
- [Full Content](https://ragyfied.com/llms-full.txt): All site content in a single expanded document
- [Sitemap](https://ragyfied.com/sitemap.xml): Full XML sitemap of all pages