AI Engineering
by chip-huyen
A practitioner's guide to building applications on foundation models, covering prompt engineering, RAG, finetuning, agents, and evaluation.
prompt-engineering
(7)Why Prompting Breaks Down and BMAD Doesn't
by cian-clarke
BMAD's spec-driven methodology beats pure prompting for production-ready AI development because it forces clarity before code and catches requirements gaps before they become technical debt.
AI Agents 4 - Prompt Chaining, Routing and Reflection
by mohammad-ghassemi
Michigan State University lecture covering three agentic design patterns—prompt chaining, routing, and reflection—with practical LangChain and LangGraph implementations.
How I Use LLMs
by andrej-karpathy
Andrej Karpathy's practical guide to using LLMs effectively: understanding them as lossy internet zip files, managing token windows, selecting models across providers, and leveraging thinking models for complex problems.
Stop Chatting with AI. Start Loops (Ralph Driven Development)
by luke-parker
Replace interactive AI chat with structured execution loops—invest heavily in planning, dump full context each iteration, and let verification backpressure catch errors before they compound.
What is Prompt Chaining in AI Agents? - Theory and Code
by yacine-mahdid
Prompt chaining breaks complex LLM tasks into sequential steps, each with a specific job and structured input/output, trading latency for reliability.
Beast Mode 3.1: AI-Powered VS Code Chat Agent
by burke-holland
A custom VS Code chat mode that fixes GPT-4.1's tendency toward speed over thoroughness using todo lists, sequential thinking prompts, and forced web research.