# chiphuyen/aie-book

[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)

Repository: https://github.com/chiphuyen/aie-book
Canonical: https://ross.abutalabs.com/products/aie-book
Language: Jupyter Notebook
License Family: other
Last push: 2026-07-03T07:04:59+00:00

## Health v2 (maintenance only)
Score: 62/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 90, release rhythm 35, longevity 45
- inputs: {"age_days": 638, "days_push": 61, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 17155, forks 2507 (observed 2026-08-28T04:11:17.732526+00:00)

## What it is
A companion repository for the book 'AI Engineering' by Chip Huyen, containing curated resources, chapter summaries, study notes, prompt examples, and case studies for building applications on foundation models. It is primarily educational material rather than software, with a few supporting Jupyter Notebook scripts.

## Use cases
- learn how to adapt foundation models to real-world applications
- find curated AI engineering resources and reading lists
- study chapter summaries and notes for the AI Engineering book
- browse prompt engineering examples and case studies
- understand evaluation and design decisions for LLM applications

## When to choose
- you are reading or considering the AI Engineering book and want supporting materials
- you want a curated, high-level resource list for building LLM applications
- you prefer conceptual frameworks over code-heavy tutorials

## When to avoid
- you need runnable production code or a software library
- you want a hands-on tutorial with extensive code snippets
- you need a maintained tool rather than reference material

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: artificial-intelligence, large-language-models, tutorials
- platform: python
- tags: ai-engineering, book, foundation-models, study-notes, prompt-examples, chip-huyen

## Member repositories
- chiphuyen/aie-book (main) score 62

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:17.732526+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:03:29.375205+00:00, confidence not recorded.
  - readme: https://github.com/chiphuyen/aie-book (fetched 2026-08-28T04:11:17.732526+00:00, sha 7903d4cebf42)
- Data as of 2026-08-30T08:39:29.467469+00:00.