Posts tagged rag
AI/LLM topics — agents, prompts
HTML, CSS, JS, HTTP, URL basics
TypeScript, Java, Python, Rust
Data structures, Big-O, patterns
React, Next.js, Tauri, Tailwind
Spring, FastAPI, SQL
Claude Code · MCP · Context7 · Figma — overview of AI coding tools
Deployment options and decision criteria
PostgreSQL · Kafka · data strategy notes
Docker, Compose, Caddy, SSH
Windows vs Mac and other dev-environment notes
Cross-platform options compared (Tauri · Flutter · RN)
pnpm, uv, Gradle, Git, regex
KISS · DRY · YAGNI · naming — development philosophy
OAuth · JWT · security fundamentals
Testcontainers, Vitest, pytest
Searching, reading docs, debugging
NotebookLM is Google's source-first AI notebook. It only answers from the PDFs, Google Docs, web pages, YouTube videos, and audio files you upload — so hallucinations are far rarer than a generic chatbot. Where 04-gemin…
The trend of combining large language model responses with external knowledge has settled under the name RAG (Retrieval-Augmented Generation). At its core sits vector similarity search, and PostgreSQL's pgvector extensi…
RAG (Retrieval-Augmented Generation) is an approach to supplement an LLM's limited training cutoff and memory limits with external knowledge. By separating retrieval and generation, you can handle new material without r…