Week 1 of 3

Basic AI Foundations

By end of this week, your Product and QA team will use AI to write release notes, craft stakeholder updates, structure Jira requirements, generate test cases, and run smarter meetings — in half the time.

▶ Watch: Basic AI Introduction
7 Days
Duration
4 Tools
AI Tools Covered
14 Use Cases
PM & QA Use Cases

What You'll Achieve

🎯Write FRDs & Acceptance Criteria in 30 min instead of 2hrs
📢Craft polished stakeholder updates from bullet points in 5 min
📋Generate release notes + test docs simultaneously per sprint
🧠Simulate stakeholder reactions before any meeting
🔎QA: Generate comprehensive test cases from AC in minutes, not hours
🐛QA: Write detailed, reproducible bug reports from rough notes instantly

14D AI Initiatives — Why This Matters

Our company goal is to become an AI-first product team. The immediate priority: reduce time spent writing documentation (FRDs, use cases, acceptance criteria, compliance) and creating UI mockups. AI won't replace your judgment — it will eliminate the grunt work so you can focus on collaboration and problem-solving.

Mandatory Privacy Setup
Complete this before using ANY AI tool for work. Non-negotiable. This protects our clients and company data.
⚠️ Before using ANY AI tool for work, you must complete all privacy settings below. Failure to do so risks exposing client data to third-party AI training systems.
🛡 Before Every AI Session — Precaution Checklist
👤Does this prompt contain client names, addresses, or PII? → REDACT IT
🔑Does this contain API keys, passwords, or credentials? → NEVER PASTE
🏢Am I sharing proprietary business logic or client algorithms? → USE GENERIC EXAMPLES
🏠Could this data identify a specific property or tenant? → ANONYMIZE IT
🔄Is my AI training/data sharing toggle still OFF? → VERIFY WEEKLY
AI Tools Guide
Know which tool to reach for — and when. Each tool has distinct strengths for different PM workflows.

Quick Reference: Which Tool for What?

ToolBest ForWhen NOT to Use
ChatGPT 5.2+Stakeholder comms, tone adjustment, brainstormingTechnical specs or structured Jira stories
Claude 4.6FRDs, acceptance criteria, structured documentationQuick one-off lookups or research tasks
PerplexityResearch with citations, competitive analysisContent generation or pasting any client data
TCREI Prompting Framework
The difference between bad AI output and great AI output is your prompt. Master this 5-step framework and every AI interaction improves.
🦀 Tiny Crabs Ride Enormous Iguanas
T · C · R · E · I — your prompting mnemonic

Full Example: TCREI in Action

Here's the complete 5-step TCREI flow for writing a sprint status update for a VP.


          

          
Expected AI Output (Summary)
EPIC: Work Order Excel Export Summary: Enable property managers to export filtered work order data to Excel for reporting and offline analysis. STORY 1: As a property manager, I want to export work orders to .xlsx so that I can share reports with building owners. Acceptance Criteria: - Given I'm on the Work Orders list, When I click "Export to Excel", Then a .xlsx file downloads containing all visible columns - Given I have date filters applied, When I export, Then only filtered results are included - Given there are 0 work orders matching my filter, When I click export, Then I see a message "No data to export" Edge Cases: Export with 10,000+ rows, special characters in work order titles, concurrent exports Out of Scope: PDF export, scheduled/automated exports, email delivery of exports Dependencies: Existing work order list API, file generation service STORY 2: As a property manager, I want to filter exports by date range... [continues with full structure] SPIKE: Investigate performance limits for large Excel exports (>5000 rows)

          
Expected AI Output (Summary)
KEY DECISIONS MADE: - Dashboard MVP will show 3 widgets: open work orders, overdue inspections, pending approvals - Mobile-first design — desktop is secondary for v1 - Launch target: Sprint 14 (internal) / Sprint 16 (client beta) ACTION ITEMS: [PM] Will create epic + stories in Jira by end of Sprint 12 [Designer] Will deliver mobile wireframes by Wednesday Sprint 13 [Engineer] Will spike on real-time data refresh approach by Thursday Sprint 12 [Stakeholder] Will provide list of top 5 KPIs from client advisory board by Monday OPEN QUESTIONS: - Should we support custom widget arrangement in v1 or hardcode the layout? - What's the data refresh interval — real-time, 5 min, or manual? - Do we need role-based dashboard views (PM vs Technician)? REQUIREMENTS (Given/When/Then): - Given a property manager opens the Dashboard, When the page loads, Then they see open work order count, overdue inspections, and pending approvals - Given a work order is completed, When the dashboard refreshes, Then the open count decreases by 1 [continues...] RISKS: - Real-time refresh may impact API performance on large portfolios - Designer bandwidth is tight — wireframes may slip - Stakeholder KPI list not confirmed yet — could change widget requirements CONTRADICTIONS FLAGGED: - Stakeholder mentioned "desktop-first" in minute 12 but PM confirmed "mobile-first" in minute 23 — needs alignment

Common Prompting Mistakes

Avoid these patterns — they produce weak output every time.

01
Being vague about output format
"Write me some acceptance criteria" vs. "Write 5 acceptance criteria in Given/When/Then format, covering happy path, error state, and empty state."
02
Skipping context about your product
AI doesn't know FacilGo exists. Always tell it: your role, your product, your users, the current situation.
03
Accepting the first output
Always add an Evaluate step: "What's missing? What would a senior engineer push back on? What edge cases aren't covered?"
04
Pasting raw data without sanitization
Never paste client names, tenant info, or real addresses. Replace with [CLIENT_NAME], [TENANT_001], [PROPERTY_A] before any AI interaction.
05
Not specifying the audience
"Write release notes" produces generic text. "Write release notes for non-technical property managers who use the system daily" produces focused, useful output.
Data Classification for AI
Know exactly what you can and cannot share with AI tools. When in doubt, sanitize first.
PM & QA Use Cases
Copy-paste AI workflows for your day-to-day Product and QA work. Each includes a real scenario, a complete prompt template, expected output, and pro tips.
Week 1 Checklist
Complete all items to be ready for Week 2.
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Week 1 Quiz
15 random questions from this week's content. Answer all to see your score.