Session Guide
Session Agenda
Introductions + Concerns Discussion
Round robin introductions followed by open discussion using the Concerns Guide.
- Keep intros tight: name, role, one sentence on hopes for the program
- Open with: "What's your biggest concern about AI in your work?"
- Let the group respond to each other
- Reference Concerns Guide for honest responses
- Validate concerns while providing perspective
This sets the tone for the entire program. Don't rush it. If it runs long, cut from other sections rather than short-changing this discussion.
Why AI Matters
Frame the transformation. AI as performance enhancer, not replacement.
- "Right now you spend 9 hours organizing for every 1 hour of real thinking. We flip that ratio."
- "Your experience doesn't become worthless. It becomes leverage."
- "What you're good at, you'll become great at. What you're great at, you'll become exceptional at."
The Intelligence Crossover
AI provides fluid intelligence on demand. You bring the crystallized half.
Adapted from Arthur C. Brooks, From Strength to StrengthThis should be memorable, not exhaustive. Plant the vision, then move to hands-on work.
Getting Started: Perplexity Setup
Get everyone set up with Perplexity and demonstrate replacing a Google search.
- Everyone opens perplexity.ai
- Walk through account creation if needed
- Live demo: Pick a question relevant to the room (insurance-adjacent works well)
- Show the answer, sources, suggested follow-ups
- Have everyone ask one question they'd normally Google
Use an actual question, not a hypothetical. The more genuine, the more impactful. First hands-on success matters.
Query Refinement Practice
Teach the difference between weak and strong queries. Hands-on practice with real questions.
Query Progression Example
- Walk through the progression: bad → better → best
- Have participants practice with real questions from their work
- Key point: "If the first answer isn't right, don't start over. Refine."
If short on time, skip the sharing. The practice itself is what matters. Let advanced users share their techniques, but don't let them dominate.
Source Evaluation
Brief introduction to verification. Plant the seed for multi-model validation later.
- "AI doesn't know things. It predicts plausible things."
- "Check claims that matter. Citations are starting points, not proof."
- "We'll go deeper on verification in Module 5."
This is just planting a seed. Don't over-explain. The goal is awareness, not mastery.
Time-Boxing + Homework
Introduce time-boxing discipline and assign homework.
- "It's easy to fall down rabbit holes. Set a timer. Give yourself constraints."
- Homework: Use Perplexity instead of Google for one week. Document 3 wins and 3 losses.
- Homework: Read "The Shape of Meaning" - be ready to discuss reactions at Module 2.
- Optional: "The Two Roads of AI" for historical context.
- Preview Module 2: "Next week we introduce Claude. Context management, why Claude specifically."
Participants Should Leave With
- Reduced anxiety about AI through open discussion
- Understanding of why AI matters for their work
- Perplexity account set up and working
- Experience refining queries to get better answers
- Awareness that verification matters (deeper coverage later)
- Clear homework: use Perplexity for one week, read "Shape of Meaning"
