claude
fbec36cb67
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
52 lines
2.6 KiB
Markdown
52 lines
2.6 KiB
Markdown
# Reviewing an AI-generated diff — working checklist
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Keep this open while you read a diff the AI produced. The point is not to re-read the whole
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file; it's to interrogate **the change** against the prompt you gave. Work top to bottom.
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## 0. Frame the review
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- [ ] **What did I actually ask for?** Write the request in one sentence. Every changed line
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should trace back to it.
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- [ ] **Read the diff, not the prose.** Ignore the AI's summary of what it did; the diff is the
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only ground truth. (`git diff main..<branch>`)
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## 1. Scope — did it change only what was asked?
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- [ ] Every hunk maps to the request. Anything outside it is **scope creep** until proven
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otherwise.
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- [ ] No unrelated files touched (formatting churn, import reshuffles, version bumps).
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- [ ] No "while I was here" refactors of code the request never mentioned.
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## 2. Deletions — what did it take away?
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- [ ] Read every `-` line. Deletions are higher-risk than additions and skim right past you.
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- [ ] **Edge-case handling still there?** Bounds checks, `None`/empty guards, `try/except`,
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validation, error returns — confirm none were dropped or weakened.
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- [ ] An error that used to be raised/logged isn't now silently swallowed (`except: pass`).
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## 3. Plausibility — does it only *look* right?
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- [ ] **Invented APIs.** Every function, method, kwarg, attribute, import, env var, CLI flag,
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config key, and endpoint actually exists. Confidence is not evidence — verify the
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unfamiliar ones against real docs/source.
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- [ ] **Invented behavior.** It isn't relying on a flag/option that doesn't do what the name
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suggests (e.g. assuming `list.pop` takes a default like `dict.pop`).
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- [ ] **Off-by-one / boundary logic.** Indexing, ranges, slicing, loop bounds, 0- vs 1-based.
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- [ ] **Inverted or weakened conditions.** `if not x` vs `if x`, `<` vs `<=`, `and` vs `or`,
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a filter quietly dropped from a comprehension.
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## 4. Behavior change — would the happy path hide it?
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- [ ] Does any existing command/function behave differently now? Trace one real call through.
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- [ ] **Run the failure case, not the success case.** The trap usually survives the happy
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path. Feed it bad input, an empty list, a missing file, a duplicate.
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- [ ] Return values / exit codes unchanged where callers depend on them.
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## 5. Decide
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- [ ] I can explain, in my own words, what every hunk does and why it's correct.
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- [ ] If I can't, I **request changes** — the burden of proof is on the diff, not on me.
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> Rule of thumb: a diff is guilty until proven correct. "It runs" is the weakest possible
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> evidence; "I read every `-` line and ran the failure case" is the bar.
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