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fix(no-slop): remove em-dashes from the wiki generator + README

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The wiki still showed em-dashes from generated chrome, not the lessons: the banner,
the UNITS unit titles (sidebar + Home TOC), the Home footer line, and the README
intro that feeds Home. Switched those to colons/semicolons and de-slopped README
(incl. a "How git works in this course" note + a Claude-Code-as-example bullet, and
a refreshed Status). Rendered wiki now has 0 em-dashes. Generator still compiles.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TfzV5QvtPDz8LJS3Pu5VLT
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Claude (agent)
2026-06-22 23:25:14 -04:00
parent c098933f25
commit ad3fa4b1ba
2 changed files with 45 additions and 31 deletions
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README.md
+34 -20
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@@ -2,33 +2,34 @@
### The Toolchain Around AI Coding
A living course for IT professionals who are comfortable in an AI chat window and starting to build
real software with it — but are still copy-pasting between the chat and their files. The goal is to
replace that loop with durable engineering workflows: version control, collaboration, CI/CD,
real software with it, but who are still copy-pasting between the chat and their files. The goal is
to replace that loop with durable engineering workflows: version control, collaboration, CI/CD,
runners, and the tools that extend AI into real systems.
> **Thesis:** the model is the cheap, swappable part. The workflow around it is the skill that
> lasts. This course is deliberately model- and vendor-agnostic — whichever LLM you use, the
> lasts. This course is deliberately model- and vendor-agnostic: whichever LLM you use, the
> scaffolding is the same.
This repo *is* the course, and it also dogfoods the course: it's version-controlled, it commits its
own AI instructions file ([`AGENTS.md`](AGENTS.md), the subject of Module 5), and each module is
built on a branch and merged through review — exactly the motion the modules teach.
built on a branch and merged through review, the same motion the modules teach.
---
## Read it as a book
The lessons are rendered into the **[Wiki](https://git.jpaul.io/justin/ai-workflow-course/wiki)** as a navigable textbook (unit-by-unit
sidebar, one page per module). The wiki is generated from `modules/` and kept in sync
automatically — it's build output, so read it there but **edit the lessons here in `modules/`**.
See [`tools/`](tools/) for the generator and the sync workflows.
The lessons render into the **[Wiki](https://git.jpaul.io/justin/ai-workflow-course/wiki)** as a
navigable textbook (unit-by-unit sidebar, one page per module, prev/next links). The wiki is
generated from `modules/` and kept in sync automatically; it's build output, so read it there but
**edit the lessons here in `modules/`**. See [`tools/`](tools/) for the generator and the sync
workflows.
---
## Who this is for
IT professionals who are fluent in an AI chat window and comfortable with ops concepts — **not
beginners.** If you already paste code between a chat tab and your editor and feel the friction, you
IT professionals who are fluent in an AI chat window and comfortable with ops concepts. Not
beginners. If you already paste code between a chat tab and your editor and feel the friction, you
are the audience. You will not be taught what a variable is; you will be taught the engineering
scaffolding that makes AI-assisted work safe, shareable, and repeatable.
@@ -42,11 +43,11 @@ units, plus a capstone finale.
| Unit | Modules | Theme |
|------|---------|-------|
| **1 — Get out of the chat window** | 1–7 | The local foundation: version control, committing the AI's config, getting the AI editing real files safely. |
| **2 — Make it shareable, reviewable, recoverable** | 8–12 | The team layer: hosting, issues, review, collaboration, recovery. |
| **3 — Automate the checking and shipping** | 13–19 | The pipeline: tests, CI, security scanning, containers, secrets, delivery, runners. |
| **4 — Extend the AI into your systems** | 20–23 | The frontier: MCP, skills, securing them, existing codebases. |
| **5 — AI in the loop** | 24–27 | Agents inside the pipeline, from assistive to autonomous, plus the evals that make it trustworthy. |
| **1: Get out of the chat window** | 1–7 | The local foundation: version control, committing the AI's config, getting the AI editing real files safely. |
| **2: Make it shareable, reviewable, recoverable** | 8–12 | The team layer: hosting, issues, review, collaboration, recovery. |
| **3: Automate the checking and shipping** | 13–19 | The pipeline: tests, CI, security scanning, containers, secrets, delivery, runners. |
| **4: Extend the AI into your systems** | 20–23 | The frontier: MCP, skills, securing them, existing codebases. |
| **5: AI in the loop** | 24–27 | Agents inside the pipeline, from assistive to autonomous, plus the evals that make it trustworthy. |
| **Capstone** | finale | One real feature taken end to end. |
**Durable core vs. expansion zone.** Modules 1–14 are the stable foundation. From Module 15 onward
@@ -58,17 +59,29 @@ the reasoning behind the sequencing.
---
## How git works in this course
You don't memorize git commands here. Modules 1–3 have you run the basics by hand so you build
intuition (the AI is still in a browser chat). Module 4 puts the AI in your editor/CLI, and from
there you **direct the AI to do the git work** (commit, branch, merge, revert) and verify the
result. Think arithmetic by hand first, then a calculator. You learn that git is critical and how it
works; the AI drives the keystrokes.
---
## Format and conventions
- **Written lessons + interactive labs.** Every module is a README you read *and* a lab you run at
the keyboard. There are no quizzes; there's a "you're done when…" check.
- **Run labs on your own machine, any OS.** No sandbox or cloud account required. Where a lab needs
code, it leans on **Python or shell** — picked per lab, kept as small as possible. The *concepts*
code, it leans on **Python or shell**, picked per lab, kept as small as possible. The *concepts*
are language-agnostic; the labs just need something concrete to run.
- **Claude Code as the worked example.** Commands and labs use Claude Code as the concrete agent
(`claude --version # sub your own agent`); the concepts stay model- and tool-agnostic.
- **GitHub is the default, not the requirement.** Hosting examples use GitHub because nearly
everyone will encounter it, but the course is provider-neutral and includes an optional
**self-hosted-forge track** for on-prem and air-gapped environments.
- **Self-checks only.** No grading, no certification — each module ends at a concrete done-criterion.
- **Self-checks only.** No grading, no certification; each module ends at a concrete done-criterion.
---
@@ -77,7 +90,7 @@ the reasoning behind the sequencing.
```
ai-workflow-course/
README.md # this file
AGENTS.md # committed AI instructions — dogfoods Module 5 (vendor-neutral name)
AGENTS.md # committed AI instructions; dogfoods Module 5 (vendor-neutral name)
the-workflow-syllabus.md # the full course plan (source of truth for structure)
handoff.md # build-context notes for the authoring sessions
_TEMPLATE.md # the shape every module follows
@@ -98,5 +111,6 @@ ai-workflow-course/
## Status
Planning is complete (27 modules + capstone). Authoring is in progress, built in dependency-chain
order. Modules 1–2 are drafted as the reference exemplars; the rest follow.
All 27 modules and the capstone are written and reviewed. The lessons render to the
[Wiki](https://git.jpaul.io/justin/ai-workflow-course/wiki) as a textbook, kept in sync from
`modules/` by CI. Blog drafts for jpaul.me live under [`blog/`](blog/).