Spreadsheets on easy mode | Master AI Automation in 4 hours Master AI Automation in 4 hours Course About Ayush Modules Sample chapter Toolbox The Microcap Minute Classroom / Module 08: Documents, Data & Research / Chapter 2 Spreadsheets on easy mode Watch first, then read. Same lesson, your pace. What you will learn – The three spreadsheet jobs AI does best – Asking for formulas that actually work – Analysis by description, verified by spot-check What AI is genuinely great at here Spreadsheets intimidate because syntax punishes memory slips, one wrong comma, #REF!. But describing what you want is easy. That gap is AI’s home turf: 1. Formula writing. Describe the goal, get the syntax: “Excel formula: in column C, if B2 > 5000 return ‘high’, elif B2 > 1000 return ‘mid’, else ‘low’” → =IF(B2>5000,”high”,IF(B2>1000,”mid”,”low”)) Always add your column letters, sample row values, and expected output for one row, then paste the returned formula into a real cell and confirm it produces that expectation. The verification loop makes formula hallucination harmless. 2. Data cleaning. Real data arrives filthy: “Rs 1,200/-“, “12-03-2026”, stray spaces. Ask for a cleaning recipe (“give me step-by-step + exact formulas to normalise column A to plain numbers”), or paste a messy sample and request the cleaned version plus the rule it applied. 3. Explanation and analysis. Paste a table (or upload the file), then ask in English: “What pattern do you see in monthly spend? Which category grew fastest? Suggest two charts.” For deeper work, ask it to write the analysis as steps you execute, keeping your hands on real cells. The division of labour The professional split: AI proposes; the spreadsheet computes. Never let chat-AI do arithmetic on large numbers directly (Module 1’s math warning), have it write formulas, then let the sheet calculate thousands of rows flawlessly. Description up top, computation down below, spot-check where they meet. Try it yourself Make a 15-row sheet of imaginary monthly expenses (date, item, category, amount, include deliberately messy amounts). Ask Kimi or Claude for: (1) a formula tagging amounts above average as ‘above’, (2) a pivot-style summary by category, (3) one insight worth acting on. Apply everything manually, verify the ‘above’ tags against eyeballing two rows. Save the prompt set to prompts/spreadsheet-kit.md . Key takeaways – AI excels at formulas-on-description, cleaning recipes, and plain-English analysis. – Feed columns letters + sample rows + one expected output; verify before trusting. – Let sheets compute; let AI describe, never reverse that for bulk numbers. Download the exercise sheet (PDF) Module workbook (PDF) ← Prev: Feed it right Next: Messy text in, tidy data out → Classroom / Module 08: Documents, Data & Research / Chapter 2 Spreadsheets on easy mode What you will learn – The three spreadsheet jobs AI does best – Asking for formulas that actually work – Analysis by description, verified by spot-check What AI is genuinely great at here Spreadsheets intimidate because syntax punishes memory slips, one wrong comma, #REF!. But describing what you want is easy. That gap is AI’s home turf: 1. Formula writing. Describe the goal, get the syntax: “Excel formula: in column C, if B2 > 5000 return ‘high’, elif B2 > 1000 return ‘mid’, else ‘low’” → =IF(B2>5000,”high”,IF(B2>1000,”mid”,”low”)) Always add your column letters, sample row values, and expected output for one row, then paste the returned formula into a real cell and confirm it produces that expectation. The verification loop makes formula hallucination harmless. 2. Data cleaning. Real data arrives filthy: “Rs 1,200/-“, “12-03-2026”, stray spaces. Ask for a cleaning recipe (“give me step-by-step + exact formulas to normalise column A to plain numbers”), or paste a messy sample and request the cleaned version plus the rule it applied. 3. Explanation and analysis. Paste a table (or upload the file), then ask in English: “What pattern do you see in
Spreadsheets on easy mode
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