Prompt Chaining Architectures
Experts rarely use one mega-prompt.
The prompt
STEP 1 (extract): From the customer interview below, extract pains, desired outcomes, and objections as JSON: {"pains":[],"outcomes":[],"objections":[]}.
STEP 2 (generate): Using only that JSON, write 3 landing-page headlines that lead with the top pain.
STEP 3 (verify): Score each headline 1-5 on specificity and pain-relevance; output the winner only.
Interview: [PASTE]What to replace
Swap these placeholders for your own details before running the prompt:
[PASTE]your own value
Pro tip: One job per step. The moment a prompt does two unrelated things, split it — reliability jumps immediately.
How to use this prompt
- Copy the prompt using the button above.
- Replace [PASTE] with your own details — the more specific you are, the better the output.
- Paste it into Any model and run it.
- If the answer feels generic, add constraints: audience, length, tone, and what to avoid. That single change fixes most weak output.
Learn the technique
Prompt Chaining Architectures
Module 5 — Expert: Prompt Systems · Prompt Engineering Fundamentals
Related prompts
The 5-Part Prompt Framework — ChatGPT
Every strong prompt combines five parts: Role (who the AI should act as), Context (background info it needs), Task (the specific ask), Format (how you want the output structured), and Constraints (length, tone, things to avoid).
ClaudeThe 5-Part Prompt Framework — Claude
Every strong prompt combines five parts: Role (who the AI should act as), Context (background info it needs), Task (the specific ask), Format (how you want the output structured), and Constraints (length, tone, things to avoid).
ChatGPTZero-Shot vs Few-Shot Prompting — ChatGPT
Zero-shot means asking directly with no examples.
GrokZero-Shot vs Few-Shot Prompting — Grok
Zero-shot means asking directly with no examples.
ChatGPTChain-of-Thought Prompting — ChatGPT
Asking a model to "think step by step" before answering measurably improves accuracy on reasoning, math, and multi-step logic tasks because it forces the model to externalize intermediate steps instead of jumping to a guess..
ClaudeChain-of-Thought Prompting — Claude
Asking a model to "think step by step" before answering measurably improves accuracy on reasoning, math, and multi-step logic tasks because it forces the model to externalize intermediate steps instead of jumping to a guess..
Topics
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Prompt
A prompt is the input you give an AI model to produce an output. Effective prompts specify five things: the role the model should adopt, relevant context, the specific task, the output format, and any constraints.
Prompt caching
Prompt caching stores the processed form of a repeated prompt prefix so subsequent requests reusing it are cheaper and faster. Cached input tokens typically cost a fraction of normal input tokens.