AGENTS.md

@@ -21,9 +21,11 @@ course content and a dogfooded example of the practices it teaches.
 
 ## Core promises (do not violate)
 
-- **Model- and vendor-agnostic.** Never pin a lesson to one LLM vendor. Never hardcode a specific
-  tool's config filename — say "your agentic tool's committed instructions file." Examples must
-  survive a model swap.
+- **Model-agnostic in principle; Claude Code as the concrete example.** The concepts and workflow
+  never depend on one LLM or tool. Name the common agentic tools once, then use **Claude Code** as
+  the worked example in commands and labs — e.g. `claude --version  # sub your own agent`. Keep the
+  *concepts* vendor-neutral; use a concrete tool so steps aren't abstract. Examples must survive a
+  model swap.
 - **GitHub is the default, not the requirement.** Keep hosting content provider-neutral; name the
   alternatives and the self-host track. Do not reintroduce a single specific forge as *the* answer.
 - **The dependency chain is load-bearing.** A module may assume only what precedes it. Never
@@ -33,11 +35,36 @@ course content and a dogfooded example of the practices it teaches.
 - **Don't pad.** This audience reads fast and trusts concrete over comprehensive. Lead with the
   pain, show the command and the failure mode.
 
+## What the course teaches about git (the reframe)
+
+This is **not** a "memorize git commands" course. The reader should finish knowing git is
+*critical*, understanding the *concepts* and the *basics*, and — above all — that they don't have to
+memorize commands because **the AI drives git for them**. The analogy: learn arithmetic by hand,
+then use a calculator.
+
+- **Modules 1–3 teach the mechanics by hand, on purpose.** The AI is still in the browser; the
+  learner types git to build intuition. Keep that.
+- **Module 4 is the pivot.** It puts the AI in the editor/CLI. From there on the learner **directs
+  the AI** to do the git work (commit, branch, merge, revert, decide what to commit) and **verifies**
+  the result — they don't type the commands by hand, and modules must not tell them to.
+- **Don't re-teach basics.** Once a concept is introduced, later modules build on it through the AI;
+  they don't re-explain how to create a branch, etc.
+
+## Lesson vs. lab (keep them separate)
+
+- The **lesson / Key-concepts** section is **theory**. To show a command, show it *with example
+  output* as illustration — never instruct the reader to *run* it there.
+- **All hands-on execution lives in the lab.** The lesson must not duplicate commands the lab runs.
+
 ## Voice
 
 Direct, concrete, rigorous. Reframe ops instincts the reader already has toward AI-assisted work.
 No motivational filler. When in doubt, show the command and what goes wrong without it.
 
+**No slop.** Don't write like an AI. Avoid "prose" (say "writing", "words", or "docs"), "unlock",
+"leverage" as filler, "delve", "dive in", "seamless", "in today's fast-paced", "it's worth noting".
+Don't lean on em-dashes — at density they read as a machine tell; vary the punctuation.
+
 ## Conventions for labs
 
 - Labs run on the learner's **own machine, any OS**. Don't assume a sandbox, cloud account, or

_TEMPLATE.md

@@ -39,9 +39,10 @@ By the end of this module you can:
 
 ## Key concepts
 
-*The actual teaching content, in prose, with commands and snippets inline. This is the bulk of the
-module. No fixed length — go as deep as the topic needs and no further. Use subheadings freely.
-Reframe an ops instinct the reader already has wherever you can.*
+*The teaching content — **theory only**. Explain the concept and why it matters; reframe an ops
+instinct the reader already has. To show a command, show it **with example output** as illustration —
+do NOT tell the reader to run anything here (all hands-on is the lab, and the lesson must not
+duplicate it). No "prose"/slop words. No fixed length — go as deep as the topic needs, no further.*
 
 ---
 
@@ -55,9 +56,11 @@ differentiator; never skip it.*
 
 ## Hands-on lab
 
-*A practical exercise that uses AI **and** the tool together, run on the reader's own machine. This
-is a tools course — end at a keyboard, not a quiz. State the lab language (Python or shell) once.
-Provide starter files in `lab/` where useful and reference them by path.*
+*The only place the reader runs things. End at a keyboard, not a quiz. State the lab language
+(Python or shell) once; provide starter files in `lab/` and reference them by path. **From Module 4
+on, the learner directs the AI agent (Claude Code as the worked example) to do the git/setup work
+and then verifies it — they don't type the commands by hand.** In Modules 1–3 the learner still
+runs git manually, on purpose.*
 
 **You'll need:** *<tools/setup required for this lab>*