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Lock the course direction before applying it across modules: - AGENTS.md: the git reframe (concepts + "the AI drives git"; arithmetic-by-hand in M1-3, calculator/AI from M4 on; don't re-teach basics); Claude Code as the concrete worked example while staying model-agnostic in principle; lesson-vs-lab rule (lesson = theory only); no-slop voice rule (kill "prose" etc.). - _TEMPLATE.md: Key concepts = theory with example output (never "run this"); Hands-on lab is the only place things run, and from M4 on the learner directs the AI to do git/setup and verifies. Foundation for the M1-6 fixes and the M7-27+capstone sweep. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TfzV5QvtPDz8LJS3Pu5VLT
95 lines
2.9 KiB
Markdown
95 lines
2.9 KiB
Markdown
<!--
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Module template for *The Workflow*.
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Copy this file to modules/NN-slug/README.md and fill every section. The shape is fixed on purpose:
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it makes the course feel coherent and lets partial drafts be reviewed against a known structure.
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Keep the section headings; delete these HTML comments and the guidance italics as you write.
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Voice: direct, concrete, rigorous. Lead with the pain. Show the command and the failure mode.
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No padding. See AGENTS.md for the full conventions.
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-->
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# Module NN — <Title>
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> **<One-line hook.>** *Why this module exists for an IT pro — the pain it removes or the payoff it
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> unlocks. One sentence. Make them want to keep reading.*
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---
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## Prerequisites
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*Which prior modules this one depends on, named explicitly (the dependency chain). If a reader could
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parachute in here with only some of the course, say what they minimally need.*
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- Module X — <what it gave you that this module uses>
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---
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## Learning objectives
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*3–5 outcomes, action verbs, phrased as what the reader can **do** afterward — not "understand X."*
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By the end of this module you can:
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1. …
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2. …
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3. …
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---
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## Key concepts
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*The teaching content — **theory only**. Explain the concept and why it matters; reframe an ops
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instinct the reader already has. To show a command, show it **with example output** as illustration —
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do NOT tell the reader to run anything here (all hands-on is the lab, and the lesson must not
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duplicate it). No "prose"/slop words. No fixed length — go as deep as the topic needs, no further.*
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---
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## The AI angle
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*The module's AI-specific reason for existing — the thing that makes this more than a generic devops
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lesson. Pull it from the syllabus entry for this module and make it concrete. This section is the
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differentiator; never skip it.*
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---
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## Hands-on lab
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*The only place the reader runs things. End at a keyboard, not a quiz. State the lab language
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(Python or shell) once; provide starter files in `lab/` and reference them by path. **From Module 4
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on, the learner directs the AI agent (Claude Code as the worked example) to do the git/setup work
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and then verifies it — they don't type the commands by hand.** In Modules 1–3 the learner still
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runs git manually, on purpose.*
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**You'll need:** *<tools/setup required for this lab>*
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**Steps:**
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1. …
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2. …
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---
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## Where it breaks
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*The honest caveats — limits, pitfalls, where a tool or analogy stops holding. This section builds
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trust with a skeptical audience. Always present; never sanded off.*
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---
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## Check for understanding
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*A short self-check or a concrete "you're done when…" criterion. Self-assessment only — no grading.*
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**You're done when:** …
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---
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## Verify-before-publish
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*For fast-moving topics only: what to re-check at build/publish time — versions, pricing, tool
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behavior, UI labels that drift. Omit this section for durable-core modules with nothing volatile.*
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- [ ] …
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