How We Built an AI Marketing Agent That Finds 2,700+ Leads and Sends Personalized Emails

July 13, 2026 TormentNexus case-study
marketing_agent: The AI That Markets AI

⚡ marketing_agent: The Autonomous AI That Markets AI

In a world where every startup claims "AI-first," one open-source project has taken the mandate literally. marketing_agent (github.com/robertpelloni/marketing_agent) is a self-contained Go agent that autonomously runs marketing for AI tools — from lead scraping to deal closure. It's meta-marketing: an AI system designed to market other AI products, and it's already processed 2,698 deals across a 7-state pipeline.

🔍 How It Works: The Full-Stack Marketing Robot

The agent operates as a perpetual background worker with no human-in-the-loop. Its architecture is modular, written in Go for concurrency and speed. Here's the data flow:

Pipeline State Machine (7 stages):
1. Scrape → 2. Enrich → 3. Score → 4. Draft → 5. Send → 6. Follow-up → 7. Closed
Total deals processed: 2,698

Stage 1: Lead Scraping

It crawls Hacker News (Show HN/Ask HN), GitHub Trending, Reddit (r/MachineLearning, r/SideProject), and LinkedIn for posts that mention AI tools, requests for "alternatives," or builders actively promoting their products. Each lead is stored with context — the exact post, timestamp, and metadata.

Stage 2: Enrichment

For every lead, the agent calls:

This yields a rich profile: "Founder of X, 2-10 employees, posted on HN 6 hours ago, last commit 2 days ago on Y repo".

Stage 3: AI-Powered Outreach

The agent generates personalized cold emails using DeepSeek (their own LLM, via API). Each email references the lead's specific product, recent activity, or pain point. Example: "I noticed your Show HN for 'Supervisor' — we built a similar tool but struggled with onboarding. May I share how we solved that?" It then sends via SMTP with smart delays to avoid spam filters.

Stage 4: Social Media Amplification

Beyond one-to-one emails, the agent autonomously posts to:

It cross-posts the same content with platform-specific formatting, hashtags, and timing.

Stage 5: Content Factory (30+ SEO Blog Posts)

The agent auto-generates long-form blog posts (1,500–2,500 words each) on topics like "10 Ways to Use LLMs for Customer Support" or "Comparing GPT-4 vs DeepSeek for Code Generation". These are optimized for SEO with keyword clusters, and then auto-published to a static site or CMS. The project currently boasts 30+ automatically generated posts.

Stage 6: Stripe Billing

For any leads that convert (or for the AI tool itself), the agent integrates Stripe for subscription management — pay-per-outreach or flat monthly fee. It handles invoicing, failed payments, and plan upgrades autonomously.

🤖 The Meta Angle: AI Marketing AI

The project's own homepage and documentation are themselves generated by the agent. It markets itself using the same pipeline it offers to others. This creates a recursive loop: the agent sells AI marketing services using AI marketing. It's a perfect demonstration of its own capability — a Go-powered, self-sustaining growth engine.

Technically, it's built with:

📊 Real Results

From the project's logs and metadata:

It's not a toy. It's a production-ready marketing engine that runs 24/7 with zero human intervention.

🔧 Getting Started

Clone the repo, set your API keys in a .env file, and run go run main.go. The agent immediately begins scraping and will start the pipeline. Configure sources via config.yaml (custom subreddits, GitHub topics, etc.).

This is the ultimate "dogfooding" project: an AI built to sell AI, selling itself. It's both the tool and the proof.

Built with TormentNexus — where AI meets autonomous marketing.

Project: github.com/robertpelloni/marketing_agent