# CI/CD Workflows in the AI Engineering From Scratch Repository: Automated Curriculum Management > Explore CI CD workflows in the AI Engineering From Scratch GitHub repo. Automate curriculum validation and documentation updates with a single GitHub Actions workflow. - Repository: [Rohit Ghumare/ai-engineering-from-scratch](https://github.com/rohitg00/ai-engineering-from-scratch) - Tags: how-to-guide - Published: 2026-06-20 --- **The AI Engineering From Scratch project automates curriculum validation and documentation updates through a single GitHub Actions workflow ([`.github/workflows/curriculum.yml`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/.github/workflows/curriculum.yml)) that orchestrates four specialized jobs triggered on push and pull request events to the main branch.** The `rohitg00/ai-engineering-from-scratch` repository maintains a complex curriculum structure that requires continuous validation and synchronization. To manage this without manual intervention, the project implements robust CI/CD workflows defined in the [`.github/workflows/curriculum.yml`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/.github/workflows/curriculum.yml) file. These automated pipelines ensure lesson consistency, synchronize README statistics, and regenerate the documentation site whenever curriculum changes are proposed or merged. ## Workflow Architecture and Event Triggers The CI/CD implementation uses a single workflow file that responds to two GitHub events with specific path filtering. The workflow triggers on **pushes** to the `main` branch and **pull requests** targeting `main`, but only when changes occur within relevant paths—including phase directories, scripts, documentation, the site builder, or the workflow definition itself. This path-gated approach prevents unnecessary execution when unrelated files change, optimizing compute resources while ensuring curriculum integrity. ## The Four CI/CD Jobs Explained The workflow defines four distinct jobs, each handling specific aspects of curriculum maintenance and validation. ### Audit: Invariant Checks The **`audit`** job runs on every push and pull request, serving as the primary quality gate. It establishes a fresh Python 3.12 environment and executes [`scripts/audit_lessons.py`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/scripts/audit_lessons.py) to verify lesson consistency across the repository. This job validates naming conventions, required file presence, and structural invariants before any changes can be merged. If the audit detects inconsistencies, the workflow fails immediately, preventing broken curriculum states from entering the main branch. ### README Counts Auto-Fix: Continuous Maintenance The **`readme-counts-sync`** job operates exclusively on pushes to `main`, automatically correcting documentation drift. It first generates an updated catalog using [`scripts/build_catalog.py`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/scripts/build_catalog.py), then executes `scripts/check_readme_counts.py --fix` to reconcile lesson counts in [`README.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/README.md). When the script detects mismatches, the job commits the corrected README using bot credentials and pushes the update with built-in retry logic to handle race conditions. This ensures the repository documentation reflects the actual curriculum state without requiring manual bookkeeping. ### Site Rebuild: Documentation Generation The **`site-rebuild`** job depends on successful completion of the `readme-counts-sync` job and runs only on pushes to `main`. It executes the Node.js-based static site generator via `node site/build.js` to regenerate [`site/data.js`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/site/data.js)—the data source powering the project's documentation website. If the build produces changes to [`site/data.js`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/site/data.js), the job commits and pushes the updated file using the same bot identity and retry mechanisms employed in the README synchronization step. This creates a fully automated pipeline where curriculum changes automatically propagate to the published documentation site. ### Drift Advisory: Pull Request Validation The **`readme-counts-drift`** job runs exclusively on pull requests, providing early warning of potential synchronization issues. It builds a temporary catalog and executes [`scripts/check_readme_counts.py`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/scripts/check_readme_counts.py) (without the `--fix` flag) to validate current counts against the README. Rather than auto-fixing, this job emits a warning when it detects drift, alerting maintainers that the main branch will self-heal after merge through the `readme-counts-sync` job. This advisory approach prevents automated commits to Pull Request branches while ensuring visibility of pending changes. ## Local Development and Testing Developers can replicate the CI/CD checks locally before submitting changes. The following commands mirror the workflow's validation and build processes: Run the invariant audit locally: ```bash python3 scripts/audit_lessons.py ``` Manually fix README lesson counts (equivalent to the auto-fix job): ```bash python3 scripts/check_readme_counts.py --fix ``` Regenerate the site data file for local testing: ```bash node site/build.js ``` ## Summary - The repository centralizes all CI/CD workflows in [`.github/workflows/curriculum.yml`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/.github/workflows/curriculum.yml), using path-filtered triggers on `main` branch events. - The **`audit`** job provides mandatory invariant checking using [`scripts/audit_lessons.py`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/scripts/audit_lessons.py) across Python 3.12 environments. - The **`readme-counts-sync`** job auto-corrects documentation drift by running `scripts/check_readme_counts.py --fix` and committing changes with bot credentials. - The **`site-rebuild`** job depends on README synchronization and uses `node site/build.js` to regenerate [`site/data.js`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/site/data.js) for the documentation site. - The **`readme-counts-drift`** job offers PR-specific validation warnings without modifying branch history. ## Frequently Asked Questions ### What triggers the CI/CD workflows in the AI Engineering From Scratch repository? The workflows trigger on **push** events to the `main` branch and **pull requests** targeting `main`, specifically when changes affect curriculum phases, scripts, documentation, the site builder, or the workflow file itself. This path filtering ensures jobs run only when relevant content changes. ### How does the automated README synchronization work? The `readme-counts-sync` job generates a fresh catalog via [`scripts/build_catalog.py`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/scripts/build_catalog.py), then runs `scripts/check_readme_counts.py --fix` to identify and correct lesson count discrepancies in [`README.md`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/README.md). When changes are detected, the job commits and pushes updates using a bot identity with retry logic to prevent race conditions. ### Can I run the curriculum validation checks locally? Yes. Developers can execute `python3 scripts/audit_lessons.py` to replicate the audit job's invariant checks, and `python3 scripts/check_readme_counts.py --fix` to preview or apply README corrections. For documentation testing, run `node site/build.js` to regenerate the site data file locally. ### Why does the `site-rebuild` job depend on `readme-counts-sync`? The dependency ensures that the catalog and README counts are fully synchronized before the site generator runs. Since [`site/build.js`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/site/build.js) relies on accurate curriculum metadata, executing `readme-counts-sync` first guarantees that the generated [`site/data.js`](https://github.com/rohitg00/ai-engineering-from-scratch/blob/main/site/data.js) reflects the most current repository state, preventing documentation staleness.