Co-authored-by: claude <claude@jpaul.io> Co-committed-by: claude <claude@jpaul.io>
4.3 KiB
The Workflow
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, 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 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, the subject of Module 5), and each module is
built on a branch and merged through review — exactly the motion the modules teach.
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 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.
How the course is built
It's a dependency chain, not a topic list. Every module assumes only what the previous ones taught, and nothing references a tool before it's been introduced. The 27 modules group into five 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. |
| 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 is the expansion zone, where a fast-moving space keeps handing us new lessons. Volatile material lives toward the back so the front stays stable as the course grows.
See the-workflow-syllabus.md for the full module-by-module plan and
the reasoning behind the sequencing.
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 are language-agnostic; the labs just need something concrete to run.
- 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.
Repo layout
the-workflow-course/
README.md # this file
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
modules/
01-the-copy-paste-problem/
README.md
lab/
02-version-control-as-a-safety-net/
README.md
lab/
...
capstone/
README.md
assets/ # diagrams, images
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.