The September edition brings the curriculum to 523 lessons across 20 phases, with 20 new lessons and 21 revised lesson texts since Edition 2026.08. It adds learning paths for real engineering work, expands Agent Skills and MCP practice, and improves the experience of moving between the website, repository, and terminal.
Choose a path through the curriculum
The new AI Engineering Learning Paths organize the course into four core domains, two specialist paths, and six career routes.
Explore Building and Deploying AI Applications, Software Engineering Fundamentals, Agent-Assisted Engineering, and Product Judgment and Delivery. Career routes connect existing lessons to customer AI deployment, developer experience and education, AI data systems, agent systems, LLM product engineering, and evaluation and reliability.
Each career route includes a shared foundation, role practice, a proof project, and evidence you can use to assess your readiness.
Build Agent Skills and MCP systems
- A five-lesson Agent Skills Engineering path covers portable skill contracts, discovery, invocation, permissions and sandboxes, and evaluation and packaging. Complete skill bundles include their scripts, references, and assets.
- A 17-lesson MCP path covers servers and clients, transports, resources and prompts, authorization, tool contracts, reliability, registry admission, and conformance checks, with an optional integration capstone.
- Twelve new agent-engineering lessons teach task framing, planning from evidence, isolated delegation, workflow discovery, risk, success metrics, and delivery decisions.
Install the learning skills into your coding agent:
npx skills add rohitg00/ai-engineering-from-scratchThen ask it to use start-learning, learn-agent-skills, or learn-mcp.
A more consistent learning experience
- Clearer homepage entry points and responsive learning-path navigation.
- Theme synchronization, improved lesson and artifact cards, and corrected career-route navigation.
- Quiz prompts that keep answer keys separate and avoid revealing correct options through reply-format examples.
- More balanced placement questions and corrected answer-position bias in the reported lesson quiz.
- Updated public counts, social previews, search metadata, and machine-readable lesson access.
Translation coverage
All 523 phase lessons have published machine translations with source hashes matching this edition in Simplified Chinese, Hindi, Spanish, Arabic, French, Portuguese, Turkish, and Vietnamese. That is 4,184 current lesson translations across eight languages.
The 12 translated README landing pages are synchronized, including the sponsor section. Machine-translated lesson prose remains on the dedicated translations branch, and code and other protected technical content remain in their original form.
Certification curricula continue to be available in English through the website and repository and remain outside the translation and book pipelines.
Books
All six English volumes are rebuilt as EPUB and PDF files from this edition's source and attached below:
| Volume | Title | Chapters |
|---|---|---|
| 1 | Foundations | 52 |
| 2 | Deep Learning | 58 |
| 3 | Language | 45 |
| 4 | Large Language Models | 68 |
| 5 | Agents | 157 |
| 6 | Production | 143 |
| Total | 523 |
The book renderer now preserves literal examples such as <image>, <PERSON>, and <doc A> as text in both formats, fixing malformed EPUB chapters and examples omitted from PDFs.
PDF code blocks, inline code, long table identifiers, and bare reference URLs now wrap within the page instead of being clipped at the edge.
Interactive figures, graded quizzes, and runnable labs remain accessible through each chapter's online links. The website and README book links continue to use the latest release assets.
Sponsors
Thank you to SerpApi for supporting the curriculum. SerpApi provides a Web Search API for AI apps, available in Markdown and JSON.