First discovery: they're obsessed with XML tags. Not markdown. Not JSON formatting. XML. Why? Because Claude was trained to recognize structure through tags, not just content. Look at how Anthropic writes prompts vs how everyone else does it: Everyone else: You are a legal

Second pattern: they separate thinking from output. Most prompts mix everything together. Anthropic isolates the reasoning process. Standard prompt: Analyze this data and create a report. Anthropic's structure: <analysis> First, analyze the data following these steps: 1.

Third technique: role definition goes way deeper than "you are an expert." Anthropic specifies expertise granularly. Weak role definition: You are a software engineer. Anthropic's method: <role> Senior backend engineer with expertise in: - Distributed systems architecture -

Fourth pattern: examples are structured as complete documents, not fragments. Most people do this: Example: The cat sat on the mat. Anthropic does this: <example> <input> Translate "The cat sat on the mat" to French </input> <reasoning> - "The cat" = "Le chat" - "sat" = past

Fifth discovery: they use thinking tags for complex reasoning. When the task requires multi-step logic, Anthropic explicitly asks Claude to show its work. <instructions> Before answering, wrap your reasoning in <thinking> tags. Include: - Assumptions you're making - Alternative

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: <guidelines> Write a professional email that: - Is concise (under 150 words) - Has a

Seventh pattern: output format specification at surgical precision. Anthropic doesn't say "give me a summary." They define exact structure. <output_format> Provide your response as: [Title: Max 8 words] Key Insight: [One sentence, under 20 words] Analysis: - Point 1:

Eighth technique: they use document tags for multi-file context. When working with multiple sources, Anthropic wraps each in document tags. <document index="1"> <source>Q4 2024 Financial Report</source> <content> Revenue: $45M Growth: 23% YoY [...] </content> </document>

Ninth discovery: error handling is built into prompts. Anthropic anticipates edge cases and tells Claude how to handle them. <error_handling> If the input data is: - Incomplete: State what's missing and make reasonable assumptions - Contradictory: Identify the contradiction and

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: { "messages": [ {"role": "user", "content": "Analyze this contract"},

How to implement this in your workflow: Step 1: Stop writing prompts from scratch Use the 10 templates above as starting points Customize the sections for your use case Keep the XML structure intact Step 2: Build a prompt library Save your best-performing prompts Tag them by

The meta-lesson from reverse-engineering Anthropic's library: Prompt engineering isn't about clever tricks. It's about clear communication of: WHO should respond (role) WHAT they should do (task) HOW they should do it (process) WHAT format to use (structure) WHAT to avoid

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@AlexanderFYoung dope

@AlexanderFYoung Anthropic's prompts are basically the cheat codes to prompting. $300 courses can't compete

@AlexanderFYoung Bookmarked the guide man

@AlexanderFYoung Anyone paying $300 for a prompt course is out of their mind. The technology is going to change by tomorrow morning. We always charged $30 max (most of the time we do it for free, to generate leads and relationships), but now we've moved completely away from prompting to mindset

@AlexanderFYoung @threadreaderapp unroll me

@AlexanderFYoung This is what separates toy prompts from production-grade systems.

@AlexanderFYoung saving this for later