Day 1 · Wednesday, June 24

Building the Foundation & Getting to Work

8:30 AM — 5:45 PM

Block 18:30–9:00 AM30 min

Arrival + Stage-Setting

0:00

Goal

Calibrate the room, create psychological safety, and establish stakes before anyone touches AI.

Activities

Welcome and logistics (5 min)
Open with the intake data readout — show the room their own anonymous aggregate data. Key stats: avg prompt confidence 2.7/5, ~130 combined hours/week on tasks AI could help with, 8 of 16 said they don't know how to write effective prompts.
Frame the room: 'You're not behind. You're exactly where most smart people are right now. The gap isn't awareness — it's structure. That's what today is about.'
Introduce the workshop arc: Day 1 = foundation + hands-on building. Day 2 = stress-test + deploy.

Facilitator notes

Materials

Block 29:00–9:45 AM45 min

AI as a Thinking Partner

0:00

Goal

Establish the mental model shift: from AI as output machine to AI as thinking partner. Set the frame for everything that follows.

Activities

Walk through the core framing (existing deck, slides 1–5): the hype phase is over; the gap is skill, not software.
Introduce the Thinking Partner frame (slide 3): AI for diagnosing issues, exploring options, stress-testing ideas, planning next actions.
LIVE DEMO — The Two Asks. Run the same DSM scenario two ways.
Lazy: 'Help me prepare for my dealer visit tomorrow.'
Thinking partner: 'Act as a Toyota regional performance consultant. I'm visiting [fictional dealer] next Tuesday. Their inventory turn is below 28 days, CPO mix is down 8 points vs. prior year, and their internet lead close rate has dropped two months in a row. What are the 5 questions I should walk in with, and what data should I pull before I go?'
Show outputs side by side. Let the room react.
Bridge to RIPE: 'The difference between those results isn't the AI — it's the question. That's what RIPE teaches you to do.'
Introduce the New Hire frame (slide 6): AI does exactly what you tell it. Vague direction, vague work. Structured direction, structured results.

Facilitator notes

Materials

Break · 9:45–10:00 AM · 15 min

Block 310:00–11:30 AM90 min

RIPE Framework

0:00

Goal

Give the room a shared prompting language that anchors every exercise for the rest of 1.5 days.

Activities

Build RIPE live (15 min): Introduce Role, Instructions, Parameters, Exceptions using slides 6–7.
Role: Who is the AI being? Context + perspective.
Instructions: What exactly should it produce, for whom, by when?
Parameters: Format, tone, length, constraints, data sources.
Exceptions: What to avoid? What should it sound like? What samples should it mirror?
Lazy vs. Better Demo (15 min): Use a SET-specific scenario — a DSM drafting a dealer performance communication for a store 12% below monthly objective with CPO below mix targets. Show lazy version then RIPE-structured version. Let the outputs do the teaching.
RIPE REBUILD EXERCISE (40 min): Each participant uses the RIPE Builder (bit.ly/ripe-bw). They write ONE lazy prompt first — drawn from their intake magic wand answer. Then rebuild it with full RIPE structure. Partner check: swap and give one specific piece of feedback.
Debrief (20 min): 3–4 people share before/after. Coach in real time. Surface 2–3 teachable moments — voice specificity, role precision, what happens when Parameters are vague.

Facilitator notes

Materials

Break · 11:30–11:45 AM · 15 min

Block 411:45 AM–1:00 PM75 min

The Morning Report Problem

0:00

Goal

Solve the #1 stated time drain for 80% of the room using AI. The practical payoff for the RIPE framework they just built.

Setup — how to open this block

'Almost every one of you said your biggest time drain is the morning report, daily data review, or email triage that kicks off your day. You spend somewhere between 3 and 10 hours a week on this. Let's cut that in half, right now, in this room.'

Activities

Teams of 3–4 receive a sample DSM morning data packet (see Materials): a Cognos-style daily inventory/sales snapshot, turn rate report for three dealer accounts, two dealer emails (one requesting inventory support, one reporting a weekend miss).
Challenge: Use AI to go from raw data to an actionable morning brief in under 10 minutes — what to focus on, which dealers need a call today, one-line message for each.
Secondary deliverable: Draft an outbound text or email to one dealer in the packet — using their name and specific numbers — that doesn't read like it was written by a bot.
Compare outputs across tables (15 min debrief): What prompts worked? What was still generic? Where did RIPE make the biggest difference?

Facilitator notes

Materials

Lunch · 1:00–2:00 PM · 60 min

Block 52:00–2:45 PM45 min

Trust, Accuracy & The Easy Button

0:00

Goal

Address the hallucination/accuracy fear that 7+ participants flagged. Build a verification muscle that makes participants more confident, not more cautious.

Activities

Open by naming the elephant: 'More than half of you said you don't fully trust AI outputs. That's the right instinct. The problem isn't whether to trust it — it's knowing what to verify and how fast you can do it.'
LIVE DEMO — The Confident Wrong Answer (15 min): Run a prompt where AI produces a plausible-but-verifiable error in a SET/Toyota context. Let the room identify it. Make it feel like a game, not a lecture.
Introduce the 3-Question Verification Habit: (1) Can I check this against something I already know? (2) Does this make operational sense? (3) What would change in my decision if this is wrong? Practice applying these to one output from the morning exercise.
The Easy Button Response (10 min): Address Jim McEachern's concern directly. 'AI literacy isn't about trusting the tool more — it's about using it in a way that requires you to think harder about what matters, so you can verify faster.'
Data Privacy — The Two Buckets (10 min): What goes in, what doesn't. Bucket 1 = safe (public data, synthesized internal info, fictional scenarios). Bucket 2 = protect (customer PII, deal specifics, personnel data, anything under NDA or SET compliance requirements).

Facilitator notes

Materials

Break · 2:45–3:00 PM · 15 min

Block 63:00–5:00 PM120 min

The DSM Hackathon

0:00

Goal

Apply everything built today to a real DSM-specific challenge under time pressure, in teams. Every participant leaves with something they can actually use.

Three challenge options — teams pick one

Option 1 — THE DISTRICT MORNING BRIEF ENGINE: Build a repeatable AI workflow that takes raw daily report data and produces a prioritized morning brief in under 5 minutes. Deliverable: a RIPE prompt template the team can run tomorrow morning.
Option 2 — THE DEALER RECOVERY COMMUNICATION: Build an AI workflow that takes a dealer performance snapshot (volume miss, CPO gap, CSI dip) and drafts a structured dealer communication that sounds like a senior DSM, not a press release. Deliverable: the workflow + a sample output for a fictional underperforming dealer.
Option 3 — THE ALLOCATION PREP BUILDER: Build an AI workflow that takes an upcoming allocation scenario and produces a clear, pre-emptive explanation to a dealer that handles their most likely objections. Deliverable: the workflow + one sample dealer-facing communication.

Timing

Facilitator notes

Materials

Break · 5:00–5:15 PM · 15 min

Day 1 Close5:15–5:45 PM30 min

Overnight Prep

0:00

Goal

Capture outputs, seed the Prompt Library, give each person a specific overnight task. Set up Day 2 before they leave.

Activities

Prompt Library checkpoint: Pull 3 strongest prompts from the hackathon. Everyone names the prompt and writes one sentence: 'Use this when you need to [specific use case].'
Overnight commit: Each person identifies ONE prompt they'll actually try tonight or first thing tomorrow morning. They write it down.
Preview Day 2: 'Tomorrow we stress-test everything you built today, go deeper on strategic AI use — including a feature most of you already have in your Copilot license that changes how this works — and close with your 30-day plan.'

Facilitator notes