Prompt Chaining

Prompt Chaining

Break complex tasks into sequential prompts where each output feeds the next — more reliable than one mega-prompt.

# Document analysis chain
import anthropic

client = anthropic.Anthropic()

def call_llm(prompt: str) -> str:
    return client.messages.create(
        model='claude-opus-4-5', max_tokens=1000,
        messages=[{'role':'user','content':prompt}]
    ).content[0].text

# Step 1: Extract key facts
facts = call_llm('Extract the 5 most important facts from:
' + document)

# Step 2: Identify themes from facts
themes = call_llm('Given these facts:
' + facts + '
Identify 3 main themes.')

# Step 3: Write executive summary from themes
summary = call_llm('Given themes:
' + themes + '
Write a 100-word executive summary.')

# Benefits of chaining:
# - Each step is focused and reliable
# - Easier to debug intermediate outputs
# - Can validate between steps
# - Use different models per step