05 showrunner

Brightmoor Education — Claude Cowork for Finance & Accounting

Session: 3.5 hours | Audience: ~25 finance, accounting, payroll, and bursar team members
Tool: Claude Cowork only (no terminal, no desktop app — just the browser-based agent)
Data: Synthetic NetSuite data in Snowflake-shaped exports (Excel files)
Theme: Practical, workflow-first, zero theory — get stuff done

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The Core Framework (Talk → Jam → Make → Tune)

Every build follows the same repeatable loop. We'll reinforce it across all three demos:

1. Talk — Describe what you want in plain English. Be specific about inputs and outputs.
2. Jam — Go back and forth with Claude Cowork on the approach. Let it ask clarifying questions.
3. Make — Step back and let Claude build. Watch the files appear.
4. Tune — Small, specific requests to polish. "Make the header blue" or "Add a pivot table."

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Session Flow

1. Why We're Here (0:00–0:10) — 10 min

Opening frame. No vision statements, no AI hype. Just a simple message:

"Your friends at other companies told you Claude can do some of your actual work. Today we're going to prove it — on real finance tasks, with data that looks like your data."

Quick check-in: What's one task this week that felt like it should've taken half the time? (Chat answer, not spoken.)

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2. Claude Cowork vs. ChatGPT (0:10–0:20) — 10 min

Why not just use ChatGPT? Two things Claude Cowork can do that ChatGPT can't:

Can do	Why it matters for your work
Reads your files	Point it at an Excel file on your computer. It sees every row, every sheet
Writes code that runs	It can run Python to do analysis, build HTML dashboards, update Excel, create PowerPoints — all from your machine

Demo: Open Claude Cowork. Drag in an Excel file. Ask: "How many rows and columns does this have? Give me a summary of each column."

~Hands-on (3 min): Everyone opens Claude Cowork and uploads an Excel file. Ask a simple question about it.

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3. Build 1: Financial Dashboard (0:20–1:00) — 40 min

Use case: Creating a visual dashboard from a NetSuite GL export.

The scenario: Brightmoor has monthly GL data in an Excel export from Snowflake. You want a single-page HTML dashboard that shows the key financial picture to your executive — no BI tool required.

Synthetic data: brightmoor_gl_summary.xlsx — 12 months of revenue, expense, and headcount data by department and entity. 4 sheets (P&L by month, Revenue breakdown, Expense detail, Headcount).

Step-by-step:

1. (Talk — 5 min) Ask Claude Cowork about the data: "Open the GL summary file and tell me what's in each sheet. What are the key things I'd want to track monthly?"

2. (Jam — 5 min) In Plan Mode: "I want to build a single HTML dashboard showing revenue vs expenses by month, department breakdown, and a quick summary table. What data do you need from me?" Let Claude ask questions and converge on a plan.

3. (Make — 15 min) Let Claude build. It will:

   • Read the Excel file
   • Write Python to aggregate and reshape
   • Generate a self-contained HTML file with charts (Chart.js)
   • Open it in the browser

4. (Tune — 10 min) Individual customization:

   • "Change the colors to match Brightmoor's palette (dark navy, gold, white)."
   • "Add a YTD variance column to the summary table."
   • "Show me the month where expenses were highest."

5. Quick share (5 min) — Turn to a neighbor. Show your dashboard. One thing you changed.

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4. Build 2: Financial Analysis in Excel (1:00–1:50) — 50 min

Use case: Using Python (via Claude Cowork) to do reconciliation and trend analysis, outputting results back into Excel.

The scenario: Month-end reconciliation. You have a NetSuite trial balance export and a bank statements export. You need to flag differences, identify trends, and produce a clean output file.

Synthetic data:

• brightmoor_trial_balance.xlsx — GL account balances by entity
• brightmoor_bank_transactions.xlsx — bank statement lines
• About 2,000 rows each — messy enough to feel real

Step-by-step:

1. (Talk — 5 min) Upload both files. "I have trial balance data and bank transaction data. I need to find accounts where the GL balance doesn't match the bank balance. Can you show me the differences?"

2. (Jam — 5 min) "I want a new Excel file with three sheets: 1) accounts with differences over $1,000, 2) a trend analysis of expenses this quarter vs last quarter, 3) a summary dashboard sheet with key metrics. Walk me through what you'd build."

3. (Make — 20 min) Claude Cowork:

   • Loads both Excel files
   • Performs the reconciliation (merge, compare, flag differences)
   • Computes quarter-over-quarter trends
   • Writes a new Excel file (brightmoor_reconciliation_output.xlsx) with formatted sheets and conditional formatting
   • Creates a summary dashboard sheet with sparklines and conditional formatting

4. (Tune — 15 min) Customization:

   • "Add a pivot table on the differences sheet grouped by account category."
   • "Show me any accounts where the variance has grown for 3+ consecutive months."
   • "Highlight cells in red where variance > 5%."
   • "Add a cover sheet with a summary paragraph describing what you found."

5. Quick share (5 min) — Open the output Excel file. Show one insight you found.

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☕ Break (1:50–2:10) — 20 min

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5. Prince of PowerPoint (2:10–2:55) — 45 min

Use case: Taking existing Brightmoor data and automatically generating a monthly presentation — charts, tables, formatted slides — via Claude Cowork.

The scenario: Every month you need to produce a 6-slide finance review deck for leadership. Same template. Same data sources. You want Claude to do the heavy lifting.

Synthetic data: brightmoor_monthly_data.xlsx — same NetSuite-shaped data but framed as "this month's numbers."

Step-by-step:

1. (Talk — 5 min) "I have this month's financial data in Excel. I need a 6-slide PowerPoint deck: cover slide, executive summary, revenue by category, expenses vs budget, headcount vs plan, and a key metrics slide. I'll give you a template if you need one — but try your best without it first."

2. (Jam — 5 min) Claude may ask: "Do you have a template .pptx file I can use as a base? What font do you use? What colors?" If no template, it will create from scratch with reasonable defaults.

3. (Make — 20 min) Claude Cowork:

   • Reads the Excel data
   • Uses python-pptx to build the deck
   • Creates charts (bar charts, line charts) directly on slides
   • Applies consistent formatting
   • Saves brightmoor_monthly_review.pptx

4. (Tune — 10 min) Refinement:

   • "Change the color scheme to navy and gold."
   • "Add a footnote on every slide: 'Confidential — Brightmoor Education'."
   • "Add a new slide: Top 5 expense variances this month, with explanations."
   • "Make the revenue chart a stacked bar showing each department."

5. Show (5 min) — Open the .pptx. Flip through the slides. Compare before/after tuning.

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6. Open Build — Your Own Workflow (2:55–3:20) — 25 min

Free build time. Pick one of the three patterns and apply it to something real you worked on this week.

Prompt starters they can paste:

If you want to…	Start with this prompt
Dashboard from data	"I have a spreadsheet of [describe data]. Build me an HTML dashboard that shows [key metrics]."
Analyze in Excel	"Take this file. Clean it, analyze trends, and output a new Excel file with a summary sheet and a detail sheet. Flag anything unusual."
Make a slide deck	"Take this data and create a 5-slide PowerPoint. Each slide should show one key insight with a chart."

TAs/helpers circulating to assist. If someone gets stuck, ASK Ladder:

• "Ask Claude to fix it." — Paste the error, say "fix this."
• "Simplify." — "Explain what you're doing in simple terms, then try a different approach."
• "Kill and restart." — Start a fresh session. Paste the prompt again.

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7. Wrap-Up & What's Next (3:20–3:30) — 10 min

Recap the three patterns:

Pattern	When to use	Prompt template
Dashboard	Data needs to be seen, not just read	"Build an HTML dashboard from this file showing [X], [Y], [Z]."
Analysis	You need to clean, compare, or find trends	"Analyze this data and output a formatted Excel file with findings."
Slides	You need to report data to someone else	"Create a PowerPoint from this data with [X] slides."

One action item: Before next week, pick one repetitive task and try the relevant pattern. Use the prompt starters above.

Materials they walk away with:

• The three synthetic data files + their own built dashboards, analysis files, and slide deck
• A one-page cheat sheet with the prompt starters

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Prep Notes for the Facilitator

Synthetic data to generate

1. brightmoor_gl_summary.xlsx — 4 sheets:

   • P&L by month (12 months × revenue/expense lines × 3 departments: Academics, Operations, Admin)
   • Revenue breakdown (tuition, grants, other — monthly)
   • Expense detail (payroll, facilities, software, professional services — monthly)
   • Headcount by department (monthly, FTE and contractor split)

2. brightmoor_trial_balance.xlsx — Account, entity, GL balance, period — ~1,000 rows

3. brightmoor_bank_transactions.xlsx — Date, description, amount, entity — ~1,500 rows with intentional mismatches

4. brightmoor_monthly_data.xlsx — Clean, presentation-ready summary — P&L, budget vs actual, headcount

Formatting tips

• Keep synthetic data "NetSuite-shaped": account codes like 4000-Revenue-Tuition, entities like Brightmoor-Academy and Brightmoor-Online
• Include realistic education-specific line items: tuition revenue, grant revenue, facilities expense, software subscriptions, payroll by department
• Add some intentional variance (accounts where GL ≠ bank) so the reconciliation exercise works
• Put budget vs. actual columns in the monthly data so the PowerPoint can show variance

Key talking points (keep punchy)

• Claude Cowork reads and writes files — that's the whole superpower vs. a chatbot
• You don't need to know code — you describe what you want in English, Claude writes the code
• Excel stays the source of truth — Claude works with what you already have
• The Talk → Jam → Make → Tune loop is the repeatable process they take home

Timing guardrails

• If build 1 runs long, skip the tune step and move to build 2 — 15 min of tune is optional
• If build 2 runs long, the Excel output alone is the win — the trend analysis and dashboard sheet are bonus
• PowerPoint build is the most impressive to execs — protect that time even if it means cutting open build short
• Keep the "why we're here" and "Claude vs ChatGPT" segments tight — these people want to build, not listen

What to avoid

• No terminal, no CLI, no VS Code — Claude Cowork is the entire tool
• No GitHub, no deployment — irrelevant for this audience
• No theory about how LLMs work — they don't need it
• No "Claude Code" terminology — use "Claude Cowork" consistently
• No ASCII art or "fun" icebreakers — the icebreaker is "what's a task that took too long this week"