How My AI Agent Decides Which Leads Are Worth Replying To

Build an AI agent that doesn't just respond, but thinks. In this session, we deploy a lead scoring system that categorizes inquiries as hot, warm, or cold and drafts personalized responses instantly. Full video: https://youtu.be/CmbwUNwTUgw

Stop wasting time on manual qualification. We are building a production-ready workflow using n8n and OpenAI to automate the high-intent lead funnel for service-based businesses. This is how you take back hours of your day while ensuring every "hot" lead gets a high-quality reply immediately.

🔗 WHAT YOU'LL LEARN

→ Designing a lead scoring prompt for AI agents

→ Implementing GPT-4o Mini for optimal credit consumption

→ Using Set Nodes to parse and map complex JSON data

→ Setting up Logic Filters to isolate high-intent "Hot" leads

→ Automating personalized email outreach with strong CTAs

🔗 TIMESTAMPS

0:00 Defining the lead data requirements

0:18 Setting up the Lead Scoring Agent

0:46 Selecting the brain: OpenAI 4o Mini

1:50 Building lead criteria (Hot vs. Cold)

3:19 Mapping dynamic variables in the prompt

4:10 Analyzing the AI-generated "Hot" lead response

5:34 Using Set Nodes to split JSON output

6:31 Prompting ChatGPT to help with nested scripts

8:45 Adding the "If Node" filter for lead priority

9:35 Visualizing the True vs. False logic paths

🔗 TOOLS MENTIONED

n8n
OpenAI API
ReqBin
ChatGPT

🔗 ABOUT ME

I'm Rushabh — I train enterprise teams on building real AI systems and run automation projects for businesses across BFSI, pharma, IT services, and more. This channel is where I share what actually works in production — not theory.

🔗 WORK WITH ME

→ Corporate AI Training: mehta.rushabh25@gmail.com

→ LinkedIn: https://www.linkedin.com/in/rushabhsmehta/

→ Instagram: specialforcesofai

#n8n #AIAgents #LeadScoring #Automation #SalesOps

Видео How My AI Agent Decides Which Leads Are Worth Replying To канала Rushabh Mehta