A curated directory of links and descriptions covering AI engineering resources, including books, courses, papers, and tools. It is a reference list of static content rather than a runnable application.
Project overview
The project provides a focused list of actively maintained resources for building and shipping AI systems, addressing the difficulty of finding materials among an abundance of options.
Project type
Prompt Engineering
Deployment
Refer to project documentation
License
MIT
Best for
Developers, AI engineers, and educators seeking a categorized, static list of links and descriptions for AI engineering resources.
Key capabilities
A curated collection of must-use, actively maintained resources for building and shipping AI systems.
Lists books, courses, and landmark papers intended to provide deep, durable knowledge.
Categorizes tools, frameworks, IDEs, and models useful for building AI applications.
Limitations and risks
The project provides text and links rather than executable software.
Getting started
No setup instructions or first success path are documented.
Evidence and sources
README: A curated collection of **must-use, actively maintained resources** for building and shipping AI systems. Focus: **AI engineering** (RAG, agents, evals, guardrails, deploy) plus t…
README: _Deep, durable knowledge — still valuable five years from now._
README: _The toolchain for building with AI._ _Personal note: you don't need tons of frameworks — start with simple LLM calls and work up._
README: - [PocketFlow](https://the-pocket.github.io/PocketFlow/) — Extremely minimalist AI agent framework in just 100 lines of code. Fantastic way to learn.
README: - [Cursor](https://cursor.sh/) — LLM-powered IDE for multi-file edits and codebase-aware chat.