feat(course): build out all 27 modules, capstone, scaffold, and conventions
Scaffold the course repo and author the full curriculum in dependency-chain order, following the settled build decisions in handoff.md. - Scaffold: course README, vendor-neutral AGENTS.md (dogfoods Module 5), _TEMPLATE.md (the fixed 9-section module shape), root .gitignore, ship config. - Modules 1-2: reference exemplars (locked for tone/depth/lab style). - Modules 3-27: full lessons + runnable labs, each following the template, respecting the chain, vendor/model-agnostic, with "feel the pain" labs. - Module 8 hosting comparison web-researched and date-stamped (as of 2026-06-22), not written from memory; expansion-zone modules carry Verify-before-publish. - Capstone: the full loop end to end on the running tasks-app example. Lab code syntax-checked (Python/shell/YAML); every module has the 7 core template sections. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TfzV5QvtPDz8LJS3Pu5VLT
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# Module 12 lab — the deliberately BROKEN `clear` command.
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#
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# Paste the elif block below into cli.py's main(), alongside the other
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# `elif command == "..."` branches (e.g. right after the "done" branch).
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# Do NOT paste this header or the import line into cli.py if json is already
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# imported there (it is) — just the elif block.
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#
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# Why it's broken: it "works" once (prints a friendly message), but it writes
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# the state file in the WRONG SHAPE. The next time the app loads tasks.json,
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# load() tries to build Task(**t) from a plain string and crashes. Classic
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# AI plausibility trap: reviews fine, runs fine once, breaks the next command.
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#
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# This exists so the lab's bad merge is deterministic across every learner.
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elif command == "clear":
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# BAD on purpose: dumps a bare string list instead of a list of task
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# dicts, so the next load() -> Task(**t) blows up with a TypeError.
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STATE.write_text(json.dumps(["cleared"]))
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print("cleared all tasks")
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