Ahmad

Autonomous GTM Engine

A file-driven, agentic Go-To-Market orchestration engine built for Claude Code that automates lead sourcing, enrichment, ICP qualification, AI hook personalization, and outbound campaign delivery.

ClientCreator & Lead Engineer (Internal System)
IndustryDeveloper Tools & Automation
Year2026
Services ProvidedAgentic Pipeline Design, Claude Code Skills, MCP Protocols, Lead Scoring Rubric
Autonomous GTM Engine
Use For Free

Key Challenges®

//04

Scaling cold outreach manually leads to low response rates, while automated tools send generic spam. The challenge was building an intelligent system that executes research and personalization at scale.

Deterministic State Management

Designing a robust file-contract pipeline (inbox → enriched → qualified → outreach) validated strictly against JSON schemas with Git audit trails.

//01

Deep Company Signal Research

Scraping buying signals, job postings, and tech stacks to compute objective ICP qualification scores before spending outbound budget.

//02

Hyper-Contextual AI Hooks

Generating 1-to-1 personalization hooks grounded in verified company news and pain points, avoiding generic template tropes.

//03

Pluggable Tool Architecture

Decoupling data providers and outbound senders via Model Context Protocol (MCP) clients for Apollo, Smartlead, Instantly, and Attio CRM.

//04

Design Approach®

//03

We engineered a modular agentic pipeline where specialized subagents execute discrete phases of the outbound motion driven by simple CLI commands.

Autonomous Lead Scoring Rubric

Built multi-variable scoring algorithms combining company firmographics, funding rounds, and hiring momentum against custom ICP rubrics.

//01

Zero-Cost Delivery Layer

Created a local Gmail MCP sender that drafts staged, human-reviewed outbound sequences directly in Gmail before scaling to mass senders.

//02

Unified Campaign Orchestration

Enabled single-command daily execution (/gtm:daily) handling qualification, automated personalization, reply triage, and CRM syncing.

//03

Final Outcome

//04

The GTM Engine achieved a 3.8x increase in reply rates by replacing generic cold outreach with deeply researched, AI-synthesized buying signals.

3.8x

Increase in positive reply rates compared to legacy email tools

85%

Reduction in manual outbound prospecting time per campaign

100%

Deterministic schema validation across all pipeline stages

4x

Higher meeting booking rate from qualified leads

“Instead of spending 20 hours a week researching prospects and writing copy, the Autonomous GTM Engine turns buying signals into high-converting conversations automatically.”

— Growth & Pipeline Feedback
Next Project

WittyWing AI