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How We Built LangChain's GTM Agent

Kacper Włodarczyk · · 1 min read · Updated on March 20, 2026
ai-agents langchain sales-automation deep-agents

This article details how LangChain built an internal GTM (Go-To-Market) agent that automates the end-to-end outbound sales process: triggering on new Salesforce leads, researching context across CRM, Gong transcripts, and LinkedIn, then drafting personalized emails for rep approval via Slack. Key results include a 250% increase in lead-to-qualified-opportunity conversion, 40 hours per month reclaimed per sales rep, and 86% weekly active usage. The system is built on Deep Agents for multi-step orchestration with a memory system that learns from rep edits, subagent delegation for parallel account intelligence, and comprehensive evaluations in LangSmith. What started as an SDR tool organically spread across the company as engineers, customer success, and AEs discovered they could query the same connected data sources conversationally.

Source: How we built LangChain’s GTM Agent

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