Every B2B founder knows cold email works. But writing 1000 personalized emails? That takes weeks.
What if an AI could research each prospect and write a unique email -- not just "Hi {name}" but genuinely personalized based on their company, role, and recent activity?
The Problem
Generic cold emails get 2% reply rates. Personalized ones get 15-25%. But manual personalization at scale is impossible.
The Solution: AI Research + Personalization Pipeline
Step 1: Prospect List
Start with a CSV: name, company, LinkedIn URL, website.
Step 2: AI Research
For each prospect, the agent scrapes their company website with Firecrawl, reads their LinkedIn summary, and identifies what they do, recent news, tech stack, and pain points.
Step 3: Personalized Email
Claude writes a unique opener for each prospect based on the research. Not template-y. Not generic. Actually relevant.
Step 4: Send + Track
Send via Resend with custom domain. A/B test subject lines. Track opens and replies. Auto-pause when prospect replies.
Results
- 1000 personalized emails in 4 hours (vs 2 weeks manually)
- 18% reply rate (vs 2% generic)
- Cost: about 15 dollars in API calls
Read the Full Guide
Complete code, email templates, and Resend setup:
Build Cold Email Personalization with AI
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Whats your cold email reply rate? Has AI improved it? Share below!
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