A Simple Guide to AI Agents and RAG
ifioknkem · x · 2026-07-17
The Core of AI Agents: Taking Action
The author describes an AI Agent as a "brain with hands": it doesn't just answer questions, it uses tools and memory to complete tasks. The critical shift is that errors are no longer just "wrong answers," but potentially "wrong actions."
The Core of RAG: Read Before You Answer
RAG is a "brain with a book": it retrieves your documents or knowledge base before generating an answer. It improves the grounding of the response, not the model's inherent intelligence; the final answer still depends on what it can read.
More from coding & agent
- Codex helps build Valdiluce, an open-world game with climbing, gliding and gondolas — Dimillian · 2026-07-22
- HeyGen adds a media-sourcing skill for coding agents with 75k images and 10k tracks — HeyGen · 2026-07-22
- Agent search bottlenecks are now about variance, not raw latency — rohanpaul_ai · 2026-07-22
- LangSmith adds tracing for Pipecat, LiveKit, OpenAI Realtime, and Gemini Live — LangChain · 2026-07-22
- An MCP server signs every AI agent tool call into a verifiable Merkle chain — Funky_Chicken_22 · 2026-07-22
- Annotated transcript of a Claude Code team interview is now available — trq212 · 2026-07-22