Facilitator Guide¶

How to deliver this workshop to enterprise customers and internal teams.

Pre-Session Checklist¶

• [ ] Environment tested: Run ./setup.sh on a clean clone within the last 24 hours
• [ ] Auth verified: gemini -p "Hello" returns a response (no auth errors)
• [ ] Demo app running: cd demo-app && npm run dev starts without errors
• [ ] Conductor installed: gemini extensions install https://github.com/gemini-cli-extensions/conductor
• [ ] Terminal setup: Font size 16+, dark theme, no transparent background
• [ ] Backup plan: Have pre-recorded terminal sessions for network failures
• [ ] MCP tokens: GitHub Personal Access Token configured if demoing MCP
• [ ] Rate limits: Check free tier quotas — Vertex AI recommended for full-day workshops

Timing Options¶

Quick Demo (2 hours)¶

Standard Workshop (4 hours)¶

Full Day (8 hours)¶

Audience-Specific Delivery¶

Live Demo Tips¶

Terminal Setup¶

• Font size: 16pt minimum (18pt recommended for conference rooms)
• Theme: Dark background, high contrast
• Terminal width: At least 120 columns
• No transparency: Solid background so projectors work
• Split panes: Keep the walkthrough doc visible alongside the terminal

Pacing¶

• Show, don't tell: Run the command first, explain after
• Wait for output: Let the agent complete before narrating
• Acknowledge latency: "This is thinking — it's analyzing the entire codebase right now"
• Have fallbacks: If the agent gives an unexpected response, use it as a teaching moment: "See how we can steer it?"

Common Issues During Live Demos¶

Customizing for a Customer¶

Before the Workshop¶

1. Clone their repo (or a representative sample) into demo-app/
2. Write a custom GEMINI.md encoding their coding standards
3. Write a custom PRD targeting a real feature they want to build
4. Configure MCP servers for their tool chain (Jira, GitHub Enterprise, etc.)

During the Workshop¶

• Replace ProShop examples with their codebase
• Use their coding standards in GEMINI.md demos
• Demo MCP against their actual Jira/GitHub instance
• Have them write policy rules for their security requirements

After the Workshop¶

• Share the repo link for self-paced follow-up
• Offer to review their GEMINI.md files
• Connect them with the Google Cloud AI team for Vertex AI setup

Bonus: gemini-cli-scanner¶

The gemini-cli-scanner is a TUI tool that scans a developer's Gemini CLI installation and generates a maturity report.

Use it as: - Pre-workshop audit: Scan participant environments to identify setup issues - Closing activity: Have participants scan their setup after the workshop to see their "maturity score" - Team assessment: Aggregate scans across a team to identify standardization opportunities

Key Talking Points¶

On Context Window¶

"Other tools only see the files you manually open. Gemini CLI reads your entire codebase — architecture, dependencies, test suites, configs — and reasons across all of it at once. Your agent doesn't just autocomplete lines. It understands how your systems connect."

On Governance¶

"Claude Code and Cursor don't have a policy engine. They don't have hooks. They don't have tool isolation for subagents. When your CISO asks 'how do we prevent the AI from running rm -rf?' — you need guardrails-as-code, not just a checkbox."

On Cost¶

"Gemini CLI with a personal Google account is free. Free. With token caching, your enterprise Vertex AI costs are a fraction of what you'd pay for comparable tools. Full-codebase awareness means fewer sessions and less back-and-forth — you stop explaining context and start shipping code."

On Conductor¶

"Most AI tools generate code one prompt at a time. Conductor gives you persistent specs, phased plans, and progress tracking that survives across sessions. It's the difference between giving a contractor verbal instructions and handing them architectural blueprints."