What question did this study set out to answer?

The aim is to provide a structured roadmap for practical AI and LLM learning through five key layers.

July 14, 20260 citationsOpen Access

AI Learning Capability Roadmap: Prompting, RAG, Agents and Production

Key Points

The aim is to provide a structured roadmap for practical AI and LLM learning through five key layers.
Developed a bilingual capability roadmap in English and Simplified Chinese.
Organized learning into five layers: model behavior, prompt design, retrieval-augmented generation, safe agent orchestration, and production engineering.
Included practice focuses, artifact portfolios, failure tests, and concrete passing conditions for each layer.
Produced a PDF with searchable text and bookmarks for easy navigation.
Created companion resources, including a QR code and a Chinese reading map for additional guidance.
The educational content was enhanced through AI-assisted layout and human review.

Abstract

A seven-page bilingual English and Simplified Chinese capability roadmap for practical AI and LLM learning. It organizes learning into five durable layers: model behavior, prompt design, retrieval-augmented generation, safe Agent and MCP orchestration, and production engineering. Each layer includes a practice focus, a small portfolio artifact, a failure test, and a concrete passing condition. The PDF contains searchable text, bookmarks, a QR code, and links to the companion Chinese reading map. Companion reading map: AI Book reading guidance. Original educational deck by AI Book. AI-assisted layout; human-reviewed content. The CC BY 4.0 license applies to this uploaded deck only, not automatically to other AI Book pages.

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