The specificity matters. Claude adjusts its knowledge retrieval based on expertise depth.
Generic roles = generic outputs. Specific roles = specialist-level responses.
Fourth pattern: examples are structured as complete documents, not fragments.
Most people do this:
Example: The cat sat on the mat.
Anthropic does this:
Translate "The cat sat on the mat" to French
- "The cat" = "Le chat"
- "sat" = past tense of "s'asseoir" = "s'est assis"
- "on the mat" = "sur le tapis"
This shows Claude the complete reasoning path, not just input/output pairs.
Few-shot prompting jumps from ~60% to ~85% effectiveness with this structure.
Fifth discovery: they use thinking tags for complex reasoning.
When the task requires multi-step logic, Anthropic explicitly asks Claude to show its work.
Before answering, wrap your reasoning in tags.
Include:
- Assumptions you're making
- Alternative interpretations considered
- Potential edge cases
- Confidence level in your conclusion
Then provide your final answer in tags.
This is basically Chain-of-Thought, but formalized into the prompt structure.
For reasoning tasks (math, logic, analysis), this improved accuracy by 34% in my tests.
Sixth technique: constraint specification using negative examples.
Don't just say what you want. Say what you don't want.
Standard approach:
Write a professional email.
Anthropic's method:
Write a professional email that:
- Is concise (under 150 words)
- Has a clear call-to-action
- Uses active voice
Do NOT:
- Use corporate jargon ("synergy," "leverage," "circle back")
- Include multiple requests in one email
- End with "let me know if you have questions"
The negative constraints are just as important as positive ones.
Claude learns boundaries, not just targets.
Seventh pattern: output format specification at surgical precision.
Anthropic doesn't say "give me a summary." They define exact structure.
Provide your response as:
[Title: Max 8 words]
Key Insight: [One sentence, under 20 words]
Analysis:
- Point 1: [Evidence]
- Point 2: [Evidence]
- Point 3: [Evidence]
Recommendation: [One specific action item]
Confidence: [Low/Medium/High] because [brief reason]
This eliminates 90% of formatting inconsistency.
You get exactly what you ask for, every single time.
Eighth technique: they use document tags for multi-file context.
When working with multiple sources, Anthropic wraps each in document tags.
Compare Q3 and Q4 performance. Reference documents by index.
This prevents Claude from mixing up sources or hallucinating attribution.
It can cite exactly: "According to document 1..."
Ninth discovery: error handling is built into prompts.
Anthropic anticipates edge cases and tells Claude how to handle them.
If the input data is:
- Incomplete: State what's missing and make reasonable assumptions
- Contradictory: Identify the contradiction and ask for clarification
- Outside your knowledge: Say "I don't have reliable information about X" (never make up facts)
- Ambiguous: Interpret both ways and note the ambiguity
This prevents hallucination and creates graceful failure modes.
Claude admits limitations instead of confidently bullshitting.
Tenth pattern: they use prefilled assistant responses.
This is the most underrated technique in the entire library.
Instead of just sending a prompt, Anthropic starts Claude's response.
API structure:
10 prompts → idea validation, MVP, GTM, competitor analysis, and more:
1. Validate your SaaS idea
Most ideas fail because they solve the wrong problem.
Prompt:
“You are a startup strategist.
Validate this SaaS idea by identifying the core problem, target audience, urgency level, and willingness to pay.”
→ [Insert your idea]
2. Define your ideal customer
You need to know who you’re building for - not just what.
Prompt:
“Create 3 ideal customer profiles (ICPs) for this SaaS product.
Include job title, industry, daily pain points, and buying behavior.”
If you want to build n8n agents, you don’t need to overcomplicate it.
After building 47 with n8n and Claude, I’ve found 3 prompts that make the process simple and repeatable:
(Steal these prompts) 👇
1. The Blueprint Maker
"I want to build an AI agent that [your specific goal]. Using N8N as the workflow engine and Claude as the AI brain, give me:
- Exact workflow structure
- Required nodes and connections
- API endpoints I'll need
- Data flow between each step
- Potential failure points and how to handle them
Be specific. No generic advice."
This prompt forces Claude to think like an engineer, not a content creator. You get actionable steps, not theory.
I use this for every new agent idea. Takes 2 minutes, saves 2 weeks of trial and error.
ChatGPT just generated startup ideas that made me want to quit my job.
Here’s the exact prompt I used:
Here’s the exact mega prompt we use:
"You are a world-class entrepreneur, market analyst, and product strategist.
Your task is to generate 10 startup ideas based on my input.
For each idea, include:
– A 1-sentence elevator pitch
– Target user or customer segment
– Key pain point it solves
– Monetization method
– Unique angle or moat
Make the ideas specific, creative, and executable.
Ask follow-up questions to refine if needed."
We tested this with multiple angles:
• “I’m a designer who wants to build a B2B tool”
• “Give me AI startup ideas in healthcare”
• “What’s a solo business I can start with no code skills?”
• “Startup ideas based on Reddit pain points”
• “Generate ideas that don’t rely on ad spend”
