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docs(blog): fill course-link placeholders + align learner-dir path

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- Replace all 24 [COURSE LINK] placeholders across the 17 posts with the course URL
  https://git.jpaul.io/justin/ai-workflow-course.
- Align the learner working-dir path in the posts to ~/ai-workflow-course (matches
  the modules after the repo rename).
- blog/README: mark the course-link checklist item done; flag publish-time
  refinements (GitHub-mirror swap; repoint inline cross-post links to real
  jpaul.me post URLs).

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 19:15:20 -04:00
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blog/15-unit4-extend-the-ai.md
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@@ -14,7 +14,7 @@ I'll admit this is the unit I was most excited to write, because it's the part I
So if the earlier units felt like careful infrastructure homework — version control, branches, review, CI — this is where it starts to feel like the future you were promised. Up to now everything we did kept the AI inside one box: **files in your repo.** It could read them, edit them, commit them. That's a lot. But the moment your question pointed one inch outside that box, the AI went blind.
This is the arc of **Unit 4 of [The Workflow]([COURSE LINK])** — four modules that take the AI from "edits my files" to "operates in my world." MCP gives it hands. Skills teach those hands a playbook. Then we secure the whole thing, because the day you give an AI hands is the day a stranger's code can use them. And finally we point all of it at the hardest, most common target there is: a giant codebase you didn't write. If you're new here, the [first post]([COURSE LINK]) lays out the thesis; this one stands on its own.
This is the arc of **Unit 4 of [The Workflow](https://git.jpaul.io/justin/ai-workflow-course)** — four modules that take the AI from "edits my files" to "operates in my world." MCP gives it hands. Skills teach those hands a playbook. Then we secure the whole thing, because the day you give an AI hands is the day a stranger's code can use them. And finally we point all of it at the hardest, most common target there is: a giant codebase you didn't write. If you're new here, the [first post](https://git.jpaul.io/justin/ai-workflow-course) lays out the thesis; this one stands on its own.
## MCP: the wall, and the way through it