Run of show

Minute-by-minute for a two-day delivery. The instructor guide covers what learners get wrong and why each lab exists; this page covers what you do and when.

Written to be followed by someone who did not build the repo.

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Before the room arrives

Two days out

• Send setup.md. The pre-flight checklist is in the instructor guide.
• Provision workspaces and issue keys — docs/facilitator/keys.md. Keys cannot be created programmatically, so budget ten minutes for a room of 30.
• npm run workshop -- status --label <label> and confirm it is clean.

The morning of

• npm run smoke on the projector machine. It asserts now, so a green run means the key works, the cache is warm, and the guardrails are wired.
• Pre-warm the cache. The first call of the day pays a cache write and looks slow. Running smoke once does this for the projector; learners each pay their own first write in Lab 0, which is fine and is worth naming when someone asks why their first call took six seconds.
• Open these tabs: the storefront support form, the injection playground, the queue with your QUEUE_TOKEN already exchanged (it is readable without one, but you want the live board), and /ops.
• Submit one safety ticket on the support form now, so the queue has something in it when you demo it on Day 2 and you are not typing into silence.

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Day 1 — the capability spine

Six and a half hours including lunch and two breaks.

Time	Segment	Notes
0:00–0:20	The scenario	Read scenario.md beats aloud. The October 2025 incident is the spine of the whole course — spend the time.
0:20–0:35	Concept map	Everything is one endpoint. Four capabilities are four parameters.
0:35–0:55	Lab 0	Not optional. See below.
0:55–1:15	Lab 1
1:15–1:50	Lab 2	The conceptual spine. Never cut.
1:50–2:00	Break
2:00–2:45	Lab 3	Runs long. See below.
2:45–3:15	Lab 4
3:15–4:00	Lunch
4:00–4:35	Lab 5
4:35–5:20	Lab 6
5:20–5:30	Break
5:30–6:00	Architecture walkthrough	docs/architecture.md, ending on the omissions list.
6:00–6:30	Assessment + close

Lab 0 (0:35–0:55) — the beat that sets up the whole course

The temptation is to let people run the command. Do not.

1. Two minutes, silent. Everyone hand-labels NW-T-1045, NW-T-1047, NW-T-1060 on paper. No laptops.
2. Compare with a neighbour. Most rooms disagree on NW-T-1060.
3. Ask why. The disagreement is about the schema, not the ticket — it is a multi-intent message against a single-label field. That reframe is what makes Lab 2 land, and you get it for free in minute forty.
4. Then run npm run eval:quick, and -- --save to record the baseline.

If you skip the paper step, Lab 0 becomes a command demo and Labs 2 and 6 lose their setup.

Lab 3 (2:00–2:45) — where every room falls behind

The tool loop is the first genuinely fiddly thing. Two mitigations:

• Have the curl for Step 3 on screen ready to paste. Typing it live costs four minutes and produces a typo.
• If you are at 2:35 and Step 3 is not done, cut the extensions and move. Lab 4 does not depend on them.

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Day 2 — production

Four hours. Assumes Day 1's baseline exists; every measurement is a comparison against it.

Time	Segment	Notes
0:00–0:10	Recap	Put yesterday's evals/baseline.json on screen.
0:10–0:55	Lab 7	Model choice.
0:55–1:05	Break
1:05–1:55	Lab 8	The trust boundary.
1:55–2:10	Live demo	The queue. See below.
2:10–3:10	Lab 9	Shipping it. Longest lab.
3:10–3:20	Break
3:20–3:50	Patterns + what we left out	Lab 9 Q8, then the omissions list.
3:50–4:00	Where to go next

Lab 7 — the two beats that matter

• Make someone say the budget out loud. $137/month against $4,000. Cost is not the binding constraint, and the whole room arrived assuming it was.
• Put the eval-04 row on screen. Haiku returns the wrong answer on the child-swallowed-plastic case at 0.95 confidence. One cell, and it makes the calibration argument better than any explanation.

Lab 8 — the beat that matters

When the red-team gate goes green, do not move on. Show them data/injections.jsonl and the case notes recording that eight of the nine failures during development were mis-specified assertions, not model failures — one literally inverted. That is Lab 0's "check the label before the model" arriving where it is much easier to mistake a broken test for a broken defence.

Live demo (1:55–2:10) — the queue

Five minutes, and it lands better than any slide about human-in-the-loop.

1. Submit a casually worded injury report on the support form — "the bottle lining flaked and my kid swallowed a bit, probably nothing." That is the October 2025 incident, typed live.
2. Watch the pipeline reach persist and return a ticket id. Point out that a routine ticket produces no id at all: storage is a consequence of escalation, not of submission.
3. Open the queue. It is public and read-only by default, showing the course's seven fictional escalations — so learners can follow along on their own laptops rather than watching yours. Your QUEUE_TOKEN cookie swaps that for the real submissions and enables Claim and Resolve. Work the ticket you just filed.
4. Open /ops. The escalation panel is the only figure on that dashboard read from a database; everything below is invented history, and both are badged. Ask which they would put in a board deck.

Lab 9 — do not spoil Step 1

The whole room believes batch is half price. Let them run all three commands and read the table before you say anything. Batch came out slowest and 23% more expensive, because a cache read is 90% off and the batch discount is 50% off and the two compete.

Then immediately guard against the overcorrection: at 400,000 tickets the prefix stays hot for hours and it probably flips back. The lesson is measure, not avoid. That is Lab 9 Q3 and it matters as much as the result.

Have Claude Desktop or Claude Code pre-configured against npm run mcp on the projector, or Step 6 becomes reading a file.

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If someone asks about Python

There is a parallel implementation of /v1/triage and the scoreboard under python/, and a deltas page covering the four things that genuinely differ.

Do not send them off to run it mid-lab. It costs the same per run as the TypeScript harness, it puts one person on a different runtime while you are debugging everyone else's, and the deltas are better read than discovered. Give them the page at a break or at the close.

The one worth mentioning out loud, because it lands for everybody regardless of language: the first port paraphrased the schema field descriptions instead of copying them, dropping one clause from requires_human. Everything type-checked and ran, and accuracy went 11/12 to 8/12. Restoring one sentence restored the score. That is Lab 2's whole thesis, reproduced in a context where the mistake is much easier to make.

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If you are running behind

In the order you should cut:

1. Lab 3 extensions
2. Lab 4 Steps 5–6
3. Lab 9 Step 7 (the patterns exercise) — valuable, but it is discussion and discussion compresses
4. The architecture walkthrough, down to just the omissions list

Never cut: Lab 0 (the baseline everything else compares against), Lab 2 (the conceptual spine), or Lab 8 Step 5 (measuring what the hardening cost — without it the lab is security theatre).

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Costs and shared keys

Per learner: ~$1.50 Day 1, ~$2.50 Day 2, measured. Full table and the argument for a 3× cap in docs/facilitator/keys.md.

On a shared key, run eval:redteam and Lab 9 Step 1 once on the projector — about $0.95 of the $4.00 between them, and both are better watched together anyway. Point the room at the model matrix and batch planner, which render checked-in results from real runs.

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After

• npm run workshop -- teardown --label <label> --apply. This is the step that gets forgotten. Nobody forgets to hand out keys; everybody forgets to revoke thirty of them.
• npm run workshop -- status --label <label> to confirm nothing is outstanding.
• Note which labs ran long and correct this page. It is only as good as the last delivery that edited it.