AI Automation Blueprints: SDR System + Content Engine + Claude Prompt Engineering Guide

Hey!

I'm sharing three automation systems with complete implementation files—no marketing fluff, just working workflows and documentation.

System 1: Automated SDR Workflow (n8n-based)

This system handles cold outreach from form submission through follow-up sequences.

What It Actually Does:

• Captures leads via webhook and verifies emails (Hunter API)

• Enriches leads with website content, LinkedIn profiles, and social data

• Generates personalized emails using GPT and Claude

• Sends 4-email sequence over 96 hours with automatic reply detection

• Pauses sequence if prospect responds

Technical Implementation:

• Email verification fallback: If email invalid, requests correction via Telegram

• Domain extraction: Handles both corporate and personal emails

• Data aggregation: Apify scrapers for website/LinkedIn/Instagram

• LLM routing: Different models for different tasks (analysis vs. writing)

• Gmail integration: Labels threads and checks for replies before follow-ups

Real Value: Automates the repetitive parts of outreach while maintaining personalization quality. One workflow handles what typically requires multiple tools and manual coordination.

System 2: Video Content Automation

Generates "Family Guy explanation" style videos—a format proven to get high engagement on short-form platforms.

Technical Components:

• Voice synthesis: Uses Replicate API for character voices

• Video composition: JSON2Video API for rendering

• Asset management: Google Drive for clips and character images

• Dynamic timing: Calculates audio duration to sync with video

How It Works:

1. Chat interface accepts script input

2. Splits dialogue by character

3. Generates voice audio for each line

4. Composites with background video

5. Adds styled subtitles

6. Outputs finished video

Engineering Note: The workflow handles parallel processing, state management across webhooks, and dynamic scene generation. All source files included.

Bonus: Claude Prompt Engineering Guide

A practical guide covering:

• System prompt architecture

• Role-based prompting

• Temperature and parameter optimization

• Multi-shot examples

• Context management

• Safety considerations

Includes tested templates and real examples from production systems.

What You're Getting:

✅ Complete n8n JSON workflows - Import and run immediately
✅ Setup documentation - API requirements, folder structures, dependencies
✅ Technical notes - Edge cases, optimization tips, customization points
✅ Prompt templates - Production-tested Claude prompts

Access Everything Here: https://drive.google.com/drive/folders/1PjMy8Cj-K1cvVIY6D8PcsEIVmoVEUTBT?usp=sharing

For Technical Decision Makers:

These aren't black-box solutions. You get full source code, can modify everything, and own the implementation. Each system is designed to be:

• Modular: Swap components as needed

• Debuggable: Clear node structure with error handling

• Scalable: Same workflow handles varying volumes

• Cost-conscious: Optimized API usage patterns

Common Use Cases We've Seen:

• SaaS companies automating demo scheduling

• Agencies scaling personalized outreach

• Content teams increasing output without hiring

• Engineering teams freeing up time from repetitive tasks

Want Custom Implementation?

These blueprints are starting points. If you need:

• Integration with your existing stack

• Custom modifications for your use case

• Team training on prompt engineering

• Full deployment support

Reply to this email. We help engineering teams implement and customize these systems, typically seeing first results within days, not months.

Best, Ghiles

P.S. The SDR system is actively used by B2B companies to automate their outreach. The video system addresses the content volume challenge. The prompt guide ensures your team maximizes their AI tool investment. Which problem are you looking to solve first?