If you've ever wondered why some people get amazing outputs from Claude while yours feel generic, I've got news for you. Anthropic just shared their official prompt engineering template, and it's a game-changer.

After implementing this structure, my outputs went from "decent AI response" to "wait, did a human expert write this?"

Here's the exact structure Anthropic recommends:

1. Task Context

Start by clearly defining WHO the AI should be and WHAT role it's playing. Don't just say "write an email." Say "You're a senior marketing director writing to the CEO about Q4 strategy."

2. Tone Context

Specify the exact tone. "Professional but approachable" beats "be nice" every time. The more specific, the better the output.

3. Background Data/Documents/Images

Feed Claude relevant context. Annual reports, previous emails, style guides, whatever's relevant. Claude can process massive amounts of context and actually uses it.

4. Detailed Task Description & Rules

This is where most people fail. Don't just describe what you want; set boundaries and rules. "Never exceed 500 words," "Always cite sources," "Avoid technical jargon."

5. Examples

Show, don't just tell. Include 1-2 examples of what good looks like. This dramatically improves consistency.

6. Conversation History

If it's part of an ongoing task, include relevant previous exchanges. Claude doesn't remember between sessions, so context is crucial.

7. Immediate Task Description

After all that context, clearly state what you want RIGHT NOW. This focuses Claude's attention on the specific deliverable.

8. Thinking Step-by-Step

Add "Think about your answer first before responding" or "Take a deep breath and work through this systematically." This activates Claude's reasoning capabilities.

9. Output Formatting

Specify EXACTLY how you want the output structured. Use XML tags, markdown, bullet points, whatever you need. Be explicit.

10. Prefilled Response (Advanced)

Start Claude's response for them. This technique guides the output style and can dramatically improve quality.

Pro Tips

The Power of Specificity

Claude thrives on detail. "Write professionally" gives you corporate buzzwords. "Write like Paul Graham explaining something complex to a smart 15-year-old" gives you clarity and insight.

Layer Your Context

Think of it like an onion. General context first (who you are), then specific context (the task), then immediate context (what you need now). This hierarchy helps Claude prioritize information.

Rules Are Your Friend

Claude actually LOVES constraints. The more rules and boundaries you set, the more creative and focused the output becomes. Counterintuitive but true.

Examples Are Worth 1000 Instructions

One good example often replaces paragraphs of explanation. Claude is exceptional at pattern matching from examples.

The "Think First" Trick

Adding "Think about this before responding" or "Take a deep breath" isn't just placeholder text. It activates different processing patterns in Claude's neural network, leading to more thoughtful responses.

Why This Works So Well for Claude

Unlike other LLMs, Claude was specifically trained to:

1. Handle massive context windows - It can actually use all that background info you provide

2. Follow complex instructions - The more structured your prompt, the better it performs

3. Maintain consistency - Clear rules and examples help it stay on track

4. Reason through problems - The "think first" instruction leverages its chain-of-thought capabilities

Most people treat AI like Google - throw in a few keywords and hope for the best. But Claude is more like a brilliant intern who needs clear direction. Give it the full context, clear expectations, and examples of excellence, and it'll deliver every time.

This is the most practical framework I've seen. It's not about clever "jailbreaks" or tricks. It's about communication clarity.

For those asking, I've created a blank template you can copy:

1. [Task Context - Who is the AI?]
2. [Tone - How should it communicate?]
3. [Background - What context is needed?]
4. [Rules - What constraints exist?]
5. [Examples - What does good look like?]
6. [History - What happened before?]
7. [Current Ask - What do you need now?]
8. [Reasoning - "Think through this first"]
9. [Format - How should output be structured?]
10. [Prefill - Start the response if needed]

Why This Works So Well for Claude - Technical Deep Dive

Claude's Architecture Advantages:

• Claude processes prompts hierarchically, so structured input maps perfectly to its processing layers

• The model was trained with constitutional AI methods that make it exceptionally good at following detailed rules

• Its 200K+ token context window means it can actually utilize all the background information you provide

• The attention mechanisms in Claude are optimized for finding relationships between different parts of your prompt

Best Practices:

• Always front-load critical information in components 1-4

• Use components 5-6 for nuance and context

• Components 7-8 trigger specific reasoning pathways

• Components 9-10 act as output constraints that prevent drift

The beauty is that this template scales: use all 10 components for complex tasks, or just 3-4 for simple ones. But knowing the full structure means you're never guessing what's missing when outputs don't meet expectations.

Want more great prompting inspiration? Check out all my best prompts for free at Prompt Magic