Llm - TechnoScripts

llm

Articles about large language models: how they work and how to use them from Python.

RAG System Design: The LLM Interview Whiteboard Round

RAG system design, short for Retrieval-Augmented Generation, is the GenAI whiteboard round where an interviewer says “design ChatPDF for an enterprise” and then watches how you think for forty-five minutes, not what you can draw. This post walks that round end to end: an eight-layer framework, two fully worked designs, the follow-up gauntlet on ACLs, freshness, and scale, and a mock transcript with the rubric, every number computed with real code. “They grade the numbers you defend, not the boxes ... Read More

How to Add AI to an Existing App Without Breaking It

When you add AI to existing app code, the danger is almost never the model itself. It is everything the model touches on the way in and out: the endpoint you wired it into, the request that now hangs for ten seconds, the bill that arrives at the end of the month. “Add the new thing at the edge, where you can rip it out again, not through the middle where it fuses to everything.” Advice worth more than most ... Read More

AI Agent Project: From Raw Loop to LangGraph, With Evals

Agent frameworks rotate every few months; the design underneath them does not. This AI agent project is the capstone: one research-and-summarize assistant with four tools, built three ways. A raw loop written by hand, the same tools served from your own MCP server, and a LangGraph 1.x port with checkpoints and a human approval step. All three get graded on the same 20 tasks, with the results table in the README. “Make it work, make it right, make it fast. ... Read More