Vague vs Specific Prompts Compared
Side-by-side examples showing the dramatic difference specificity makes.
Side-by-Side Comparison Method
The fastest way to internalize prompt quality is to study specific rewrites side by side and analyze why each improvement works.
In this lesson we examine five vague prompts and their specific rewrites. For each pair, we identify the exact changes made and the mechanism by which each improvement guides the model to better output.
Pair 1: The Blog Post
Vague: 'Write a blog post about remote work.'
Specific: 'Write a 600-word blog post titled "The 3 Remote Work Habits That Killed My Productivity (And What I Do Now)" for an audience of mid-level software developers. First-person voice, conversational tone. Structure: 1 intro paragraph, 3 sections with H2 headings, 1 closing CTA to download a free template.'
Why it works: Adds word count, title (and therefore angle), audience, voice, tone, structure, and a specific ending element. Zero dimensions left to chance.
import anthropic
client = anthropic.Anthropic(api_key='sk-ant-your-key-here')
response = client.messages.create(
model='claude-opus-4-5',
max_tokens=800,
messages=[{
'role': 'user',
'content': (
'Write a 600-word blog post titled '
'"The 3 Remote Work Habits That Killed My Productivity (And What I Do Now)" '
'for an audience of mid-level software developers. '
'First-person voice, conversational tone. '
'Structure: 1-paragraph intro, 3 H2 sections (one per habit), '
'1 closing paragraph with a CTA to download a free productivity template.'
)
}]
)
print(response.content[0].text[:400], '...')All lessons in this course
- Why Specificity Matters
- Removing Ambiguity from Prompts
- Adding Concrete Details
- Vague vs Specific Prompts Compared