docs: mine the four-month game-dev field report for supervision, tiering, and validation lessons (closes #98) (#184)

* docs: mine the four-month game-dev field report for supervision, tiering, and validation lessons (closes #98)

Re-lands the change that PR #179 carried. That PR was stacked on the
community-directory branch and merged into it, and the branch was then
closed and re-landed as #182 without these commits, so the field-report
edits never reached main. Same content as #179's reviewed head, plus one
grammar fix Copilot raised on the stacked branch ("with coding agents and
no coding experience").

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GMS285msTfSxnF4Cy9RkTE

* docs: scope the verification claim to the report and list the three cost levers

Copilot's round on #184: the sentence "No automated verification appears
anywhere in the project" asserted more than the report evidences, so it
now says what the report and its thread do not mention; the three cost
levers are a bullet list with the spend figure in its own sentence, per
the lab's list rule; and the new callout uses the same div syntax as the
one above it.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GMS285msTfSxnF4Cy9RkTE

* docs: cite the field report by its post permalink

The four citations linked the subreddit because the issue body carried
no permalink; a comment on issue #98 does carry it, so the citations now
link the post itself with the subreddit and date beside it.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GMS285msTfSxnF4Cy9RkTE

* docs: one clause per line in the three field-report sentences Copilot flagged

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GMS285msTfSxnF4Cy9RkTE

* docs: one clause per line in the field-report citation sentence

Copilot flagged the remaining long line in small-local-models-agentic.qmd.
The split is source-only: no blank line is added, so the paragraph renders
unchanged.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GMS285msTfSxnF4Cy9RkTE

* docs: caution callout and sentence-level lines for the field-report passages

Copilot's suppressed comments: the worked example in
responsibility-for-validation.qmd describes a failure mode, so it is a
callout-caution rather than a callout-tip; the "budget for it" item in
agents-best-practices.qmd now starts its continuation as a sentence and
carries one clause per line. The citation parentheticals in both files are
split at their separators to match the other two chapters.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GMS285msTfSxnF4Cy9RkTE

---------

Co-authored-by: Claude <noreply@anthropic.com>

Author: d-morrison

chapters/ai-tools/agents-best-practices.qmd

@@ -13,6 +13,14 @@ To work with coding agents safely and successfully:
 3. **Test thoroughly**:
    AI-generated code must be tested as rigorously as code you write yourself.
    Don't skip testing because "the AI wrote it."
+   Budget for it, too.
+   Two commenters on the same field report
+   (["Vibe coded this game in four months"](https://www.reddit.com/r/ClaudeCode/comments/1vvhrfq/),
+   r/ClaudeCode, 2026-08-22;
+   summarized in [issue #98](https://github.com/Morrison-Lab/wai/issues/98))
+   independently named manual testing as the dominant cost once generation is cheap.
+   One put it as needing either deep domain experience or heavy testing
+   to get a defect-free result.
 
 4. **Start small**:
    Begin with small,

chapters/ai-tools/relative-advantages-ai-humans.qmd

@@ -49,13 +49,29 @@ and AI agents will handle many of the computational and coding details.
 For most tasks,
 you won't need to step in and manipulate code yourself.
 However,
-you'll still need strong coding skills to:
+you'll still need enough domain judgment to:
 
 - Supervise and validate AI-generated code
 - Handle edge cases that agents struggle with
 - Make creative decisions about architecture and design
 - Understand when agent suggestions are incorrect or suboptimal
 
+Strong coding skills are one route to that judgment,
+and not the only one.
+A public field report from a non-programmer
+(["Vibe coded this game in four months"](https://www.reddit.com/r/ClaudeCode/comments/1vvhrfq/),
+r/ClaudeCode, 2026-08-22;
+summarized in [issue #98](https://github.com/Morrison-Lab/wai/issues/98))
+describes four months of building a browser racing game
+with coding agents and no coding experience at all,
+crediting knowledge of game technology and design,
+plus long practice with language models,
+for the planning and the early catches that kept the project on track;
+by the author's own account,
+lacking that knowledge as well would have stalled the project after a couple of prompts.
+The requirement is the supervision,
+whichever background supplies it.
+
 #### Future Developments: World Models
 
 As AI technology advances,

chapters/ai-tools/responsibility-for-validation.qmd

@@ -16,3 +16,29 @@ Never blindly use AI-generated code without fully understanding it.
 If you don't completely understand what the AI has suggested,
 take the time to learn or ask a colleague for help.
 :::
+
+::: callout-caution
+#### A worked example: the defects the builder cannot see
+
+A public field report from a non-programmer
+(["Vibe coded this game in four months"](https://www.reddit.com/r/ClaudeCode/comments/1vvhrfq/),
+r/ClaudeCode, 2026-08-22;
+summarized in [issue #98](https://github.com/Morrison-Lab/wai/issues/98))
+describes four months of building a browser racing game with coding agents,
+and reports that most things worked on the first try.
+The comment thread under it says otherwise.
+Players reported:
+
+- a minimap announcing a turn in the wrong direction
+- speed boosts invisible from any distance
+- an orbit track with no visible route
+- an accelerator with no consequences
+
+Every one of those defects looks correct to the person who built it,
+because the builder reads the underlying state in their own head
+and sees the display agree with it.
+They surface only on contact with someone who has nothing but the display.
+Neither the report nor its thread mentions any automated verification.
+That is the answer to "why bother instrumenting checks when the thing looks fine":
+the thing looks fine to you precisely because you know what it is supposed to do.
+:::

chapters/ai-tools/small-local-models-agentic.qmd

@@ -322,6 +322,25 @@ Two shapes of this pattern are worth knowing:
   wire a cloud-with-local-fallback endpoint,
   which composes with this split.
 
+The same split is the main cost lever in a public field report
+from a non-programmer
+(["Vibe coded this game in four months"](https://www.reddit.com/r/ClaudeCode/comments/1vvhrfq/),
+r/ClaudeCode, 2026-08-22;
+summarized in [issue #98](https://github.com/Morrison-Lab/wai/issues/98)),
+who built a browser racing game over four months with coding agents.
+The report names three levers:
+
+- plan with the strongest model available
+- implement with cheaper ones
+- keep the scope to what can realistically ship
+
+The reported total was roughly $200
+in project-specific subscriptions over the four months,
+on top of a general-purpose subscription the author already held.
+The lab's machine-facing configuration,
+[`Morrison-Lab/ai-config`](https://github.com/Morrison-Lab/ai-config),
+states the same routing rule for agents.
+
 None of these routing choices substitutes for the guardrails below.
 A well-chosen planner still hands off to an executor that can make a
 per-step mistake,