# DataExpert-io/ai-engineer-handbook

All the links, books, and creators you need to follow to stay up to date with AI!

Repository: https://github.com/DataExpert-io/ai-engineer-handbook
Canonical: https://ross.abutalabs.com/products/ai-engineer-handbook
License Family: other
Last push: 2026-03-23T20:02:46+00:00

## Health v2 (maintenance only)
Score: 48/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 73, release rhythm 35, longevity 14
- inputs: {"age_days": 198, "days_push": 163, "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 1193, forks 197 (observed 2026-08-28T04:03:56.457555+00:00)

## What it is
A curated handbook of links, books, communities, newsletters, and creators for becoming and staying an AI engineer. It is a resource collection rather than software, covering LLM providers, frameworks, vector databases, and training tools.

## Use cases
- learn how to become an ai engineer
- find the best books on ai engineering and llms
- discover ai engineering communities and newsletters
- prepare for ai engineering interviews
- stay up to date with ai tools and companies
- find hands-on ai engineering project examples

## When to choose
- you want a curated starting point for learning AI engineering
- you need recommendations for books, communities, and creators to follow
- you are preparing for AI engineering job interviews

## When to avoid
- you need runnable code or a software library
- you want a structured course with lessons rather than a link collection
- you need deep technical documentation on a specific tool

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools
- domain: artificial-intelligence, large-language-models, machine-learning, tutorials, awesome-lists
- platform: cross-platform
- tags: ai-engineering, handbook, curated-resources, llm, career, interview-prep

## Member repositories
- DataExpert-io/ai-engineer-handbook (main) score 48

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:56.457555+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 2026-08-30T06:22:11.902920+00:00, confidence not recorded.
  - readme: https://github.com/DataExpert-io/ai-engineer-handbook (fetched 2026-08-28T04:03:56.457555+00:00, sha 60e4a0531ddf)
- Data as of 2026-08-30T08:39:29.467469+00:00.