For: Support team leads · Group: 4–10 agents, one screen or everyone on their own laptop · Prep: 2 minutes (open the lesson, have one real anonymized draft ready if you have one)
This lesson is designed to run inside an existing huddle, not instead of one. The pedagogy is deliberate: consequence before instruction (Scene A shows a confident wrong draft), detection before procedure (Scene B hotspot hunt), procedure under feedback (Scene C ladder), choice with stakes (Scene D branch). Your job is to keep the pace and land the debrief — the lesson carries the content.
| Time | What happens | Your move |
|---|---|---|
| 0–2 | Scene A: read the draft aloud together | Ask: “Would you send this?” Take a quick show of hands. Do not reveal anything. |
| 2–6 | Scene B: hotspot hunt | Let people click and argue. If the room finds all 3 fast, ask why the decoys are safe — that distinction (invented fact vs. style) is the actual skill. |
| 6–11 | Scene C: Verify ladder | Run it as call-and-response: read the KB excerpt, ask “what do we do with this clause?” before clicking the answer. Wrong answers are good here — let them happen. |
| 11–13 | Scene D: the send decision | If anyone picks “send the original”, play the consequence email aloud without commentary. The email does the teaching; you do not scold. |
| 13–15 | Debrief — the only part that is yours | Three questions, 40 seconds each (below). Close on the #ai-catch tag. |
#ai-catch, no blame, the catch is the win. Volume of catches is our quality metric, not our shame metric.#ai-catch tag and uses it in the first week (check the count in your weekly ticket review).The lesson is a single offline HTML file — no LMS, no accounts, no network. To adapt it to your own product: swap the draft email, the KB excerpts, and the consequence email; keep the four scenes and the ladder structure. If you change the draft, keep exactly 3 real risks and 2 safe decoys — the decoys are what teach detection instead of paranoia.
Fictional disclosure: Nordwind Software and all referenced tickets/persons are a fictionalized composite for this portfolio. Note drafted with AI assistance; final judgment and copy are human-owned.
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