How to write instructions Claude actually follows
The difference between vague prompts and great ones. Learn the pattern that works every time.
Video coming soon
How to write instructions Claude actually follows
This is the most important skill you'll learn. The difference between Claude producing garbage and producing exactly what you want comes down to how you write your instructions.
The pattern that works every time
Every good instruction has these parts:
- What to read — Tell it where the input is
- What to do — Be specific about the transformation
- What not to do — Explicitly tell Claude Code what to avoid
- What to output — Tell it exactly what file to create
Here's the template:
Read [input file/folder].
[Specific instructions about what to do].
[Optionally: what not to do]
Save the result as [output file].Bad vs. good instructions
Bad: "Summarize this data"
Good: "Read sales_q1.csv. Create a summary that includes: total revenue, average deal size, top 5 accounts by revenue, and month-over-month growth rate. Format as a markdown document. Save as q1_summary.md"
Bad: "Clean up this file"
Good: "Read contacts.csv. Remove rows where email is empty. Deduplicate by email address, keeping the most recent entry. Standardize all phone numbers to +1 (XXX) XXX-XXXX format. Save as contacts_clean.csv"
The specificity principle
Ask yourself: "If I gave this instruction to a new hire on their first day, would they know exactly what to do?"
If the answer is no, add more detail. Claude is capable, but it can't read your mind about your preferences.
Use examples when the format matters
If you care about the exact output format, show an example:
Format each entry like this:
**[Company Name]**
Contact: [First] [Last]
Revenue: $[amount]
Status: [active/churned]Tell it what NOT to do
Sometimes it's helpful to set boundaries:
- Do NOT modify the original file
- Do NOT include rows where status is "test"
- Do NOT round the numbersBreak complex tasks into steps
For bigger jobs, number your steps:
1. Read all CSV files in the /data folder
2. Merge them into a single dataset, matching by email
3. For each person, calculate total spend across all files
4. Flag anyone who spent more than $10,000
5. Sort by total spend, highest first
6. Save as high_value_customers.csvNext up
Now that you can write solid instructions, let's make them reusable. In the next episode, you'll create your first CLAUDE.md file — a saved instruction set you can run anytime.