Mountain View Events
Owner, venue coordinator, and two sales assistants
Format: remote half-day
Generated from setupyour-workshop-products
AI team workshop plan demo
This is a static proof packet generated from the private workshop product repo. It turns a team profile into agenda modules, exercises, approval boundaries, follow-up actions, and a next-build recommendation path without pretending production integrations are part of the workshop.
3.88/5
customize_first
Foundations workshops start around $2,500 remote.
AI foundations for real work
Team understands useful AI patterns, limits, and review habits.
Approved facts and answer boundaries
Team separates approved business facts from guesses and exceptions.
Prompt patterns and reusable drafts
Team leaves with reusable prompts for drafts, summaries, and checks.
Workflow discovery and ROI triage
Team identifies the first workflow worth automating after training.
Agent operations and human approval
Team knows where AI can draft, where people approve, and when to escalate.
Generated workshop plan
Training artifact with guardrails.
The plan names non-goals for production launches, autonomous sends, and system writes.
# AI Workshop Plan: Mountain View Events Operator: Jim Format: remote half-day Audience: Owner, venue coordinator, and two sales assistants ## Readiness - 3.88/5 - customize_first ## Team goals - Use AI to answer common tour and availability questions faster - Create safer prompts for follow-up drafts and internal summaries - Find the first workflow automation candidate after training ## Current tools - Gmail, Google Calendar, Squarespace, Google Drive ## Agenda modules 1. AI foundations for real work: Team understands useful AI patterns, limits, and review habits. 2. Approved facts and answer boundaries: Team separates approved business facts from guesses and exceptions. 3. Prompt patterns and reusable drafts: Team leaves with reusable prompts for drafts, summaries, and checks. 4. Workflow discovery and ROI triage: Team identifies the first workflow worth automating after training. 5. Agent operations and human approval: Team knows where AI can draft, where people approve, and when to escalate. ## Exercises - AI foundations for real work: Rewrite one real internal request into a clear AI task with context and constraints. Success check: Each participant can explain what the AI should and should not do. - Approved facts and answer boundaries: Build a mini approved-facts sheet for common customer questions. Success check: Risky questions are flagged for human review instead of guessed. - Prompt patterns and reusable drafts: Turn a messy customer request into a structured reply draft and review checklist. Success check: Draft includes missing details, risk flags, and next action. - Workflow discovery and ROI triage: Score three repeated workflows by value, repeatability, data readiness, and risk. Success check: One first-build candidate is selected and one no-build call is named. - Agent operations and human approval: Classify sample customer messages into safe draft, needs owner approval, or stop. Success check: External-send and customer-system-write boundaries are explicit. ## Guardrails - Use approved facts and customer-provided context; do not invent policies, prices, availability, or commitments. - A human approves external customer messages, customer-system writes, payment-affecting decisions, legal answers, refunds, and policy exceptions. - No private customer data, credentials, or sensitive transcripts are copied into tools that are not approved for that data. - Escalate these boundaries immediately: pricing exceptions, legal questions, refunds, contract changes. ## Desired outcomes - Team can draft safe replies from approved facts - Owner gets a prioritized follow-up build recommendation - Everyone leaves with three reusable prompts ## Follow-up actions - Jim: Send the workshop recap, reusable prompts, and risk-boundary checklist. Proof: Recap packet names prompts, guardrails, and selected first-build candidate. Window: 14 days. - Mountain View Events: Pick one team habit and one workflow candidate to test for two weeks. Proof: Team names the owner, representative examples, and success metric. Window: 14 days. - Jim: Recommend whether the next paid step is an Opportunity Map, automation sprint, or agent build. Proof: Follow-up recommendation includes price anchor and non-goals. Window: 14 days. ## Non-goals - No production agent launch during the workshop. - No autonomous external sending or customer-system write access. - No CRM, calendar, email, payment, or website integration unless separately scoped. ## Pricing anchor - Foundations workshops start around $2,500 remote.