🚀 나는 잠자는 동안 리드, 의사 결정권자를 찾고 아웃리치를 작성하는 AI 팀을 만들었습니다.

Lead generation is one of those tasks everyone knows they should automate… but most teams still do it manually.

Every week the process looks something like this:

🔎 Search LinkedIn for companies

🌐 Visit dozens of websites

👤 Find the CTO, VP, or Director

📧 Hunt for contact information

✍️ Write personalized outreach emails

⏳ Lose half a day doing repetitive work

What if all of that happened automatically?

What if you woke up Monday morning to find:

✅ A list of companies matching your ICP

✅ Decision makers already identified

✅ Company research already completed

✅ Lead qualification scores calculated

✅ Personalized outreach drafts ready to send

That’s exactly what I built using Hermes Agent.

Full Video Walkthrough:

🤖 The Goal

I wanted a system where I could provide a simple campaign brief and have a team of AI agents handle the entire lead generation workflow.

Something like:

“Find SaaS startups with 10-200 employees that build AI developer tools. Identify decision makers and prepare personalized outreach.”

Instead of manually managing every step, a multi-agent workflow handles the process from start to finish.

🏗️ Architecture Overview

The pipeline consists of six specialized AI agents:

🎯 Orchestrator Agent

Acts like a sales manager.

Responsibilities:

• Creates execution plans
• Creates tasks
• Assigns work to specialist agents
• Tracks progress
• Manages dependencies
• Controls workflow phases

🔍 Prospector Agent

Finds companies that match your ICP.

Input:

• Keywords
• Industry
• Company size
• Target market

Output:

• Qualified company list

Example keywords:

• AI Developer Tools
• LLM Infrastructure
• DevOps Automation
• AI Engineering Platforms

🌐 Scraper Agent

Researches every company discovered during prospecting.

Collects:

• Products
• Services
• Company descriptions
• Locations
• Social profiles
• Technology signals

All data gets enriched and stored automatically.

👥 Contact Finder Agent

Identifies the right people inside each company.

Targets:

• CTOs
• VPs
• Directors
• Founders

Then gathers available contact information from multiple sources.

✉️ Outreach Agent

Generates personalized outreach emails.

Instead of generic templates, it references:

• Company initiatives
• Product offerings
• Technology stack
• Industry positioning

Result:

Much more relevant outreach messages.

📊 Analyst Agent

Scores every lead against the Ideal Customer Profile (ICP).

Evaluation criteria:

• Company size
• Industry fit
• Product relevance
• Buying potential
• Strategic alignment

Each company receives a qualification score between 0 and 1.

This helps prioritize outreach efforts.

🧠 Why Multi-Agent Systems Work So Well

Most people try to build lead generation using a single AI agent.

The problem?

One agent becomes responsible for:

• Research
• Scraping
• Qualification
• Personalization
• Coordination

That quickly becomes messy.

Instead, I use specialist agents.

Each agent focuses on one responsibility only.

Benefits:

✅ Better task quality

✅ Easier debugging

✅ Better scalability

✅ Parallel execution

✅ Cleaner workflows

📋 Workflow State Machine

The workflow runs in phases:

Campaign Brief
      │
      ▼
 Prospecting
      │
      ▼
 Research & Enrichment
      │
      ▼
 Contact Discovery
      │
      ▼
 Outreach Generation
      │
      ▼
 Lead Qualification
      │
      ▼
 Campaign Report

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The orchestrator only unlocks the next phase once the previous phase is completed successfully.

This prevents bad downstream data from contaminating later stages.

🗂️ Hermes KANBAN Board = Shared Agent Memory

One of my favorite parts of Hermes Agent is its Kanban workflow system.

The Kanban board acts as a shared coordination layer between agents.

Every agent can:

📖 Read task status

✍️ Update progress

🔄 Create follow-up tasks

🚦 Track dependencies

The orchestrator uses the board to understand:

• What is complete
• What is blocked
• What should happen next

This creates a surprisingly robust autonomous workflow.

⚡ Running a Campaign

To launch a campaign I simply provide:

Product

What I’m selling

ICP

Who I want to target

Discovery Keywords

Where prospecting should begin

Goal

What outcome I want

Example:

Run a full B2B lead generation campaign for ShipMe Agent, an AI agent for QA and DevOps automation. 
ICP: AI SaaS startups, 10-200 employees. 
Keywords: AI Developer Tools, LLM DevOps Automation. 
Goal: 10 ranked qualified leads with decision-maker contacts and personalized outreach emails drafted

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The orchestrator takes over from there.

📈 End Result

At the end of a run I receive all information organized in CSV files:

Companies

• ICP matched companies
• Enriched company data

Contacts

• Decision makers
• Contact information

Outreach

• Personalized email drafts

Qualification

• Lead scoring
• Prioritized opportunities

Report

• Campaign summary
• Workflow results

All generated automatically from a single task.

🔥 Real Value

The biggest win isn’t saving a few minutes.

It’s eliminating repetitive work entirely.

Instead of spending hours every week:

❌ Searching

❌ Researching

❌ Copy-pasting

❌ Writing first drafts

I can focus on:

✅ Sales conversations

✅ Closing deals

✅ Improving campaigns

✅ Building relationships

The AI team handles the operational work.

🛠️ Resources

🔗 Agents SOUL.md files & Custom Hermes Skills: https://github.com/vivekshetye/hermes-lead-generation-pipeline

💬 What Would You Automate?

If you had a team of AI agents working for you 24/7, what business workflow would you automate first?

Lead generation?

Customer support?

Market research?

Content creation?

I’d love to hear what you’re building.