In today's episode, I chat with Andrew, Head of GTM at Arda, about the context engineering layer that most outbound stacks completely ignore. Arda is the easiest way to implement Kanban for small and medium-size manufacturers — tying physical Kanban cards to a digital backend connected to supplier ordering so factories never hit a stockout.

Andrew's most valuable build isn't a campaign; it's the authoritative reference layer he's built beneath all of them. Most enrichment tools (Clay, DeepLine, Exa) do a solid job telling your machine everything about a prospect, but almost nothing tells it about you — your brand voice, verified proof points, which accounts to walk away from. Andrew has addressed this with a context graph that agents traverse via a decision tree rather than fetching fresh context every time, running the whole thing headless from the command line for fewer burned tokens and improving answers over time. We also talk about his path from founding AE to full-time GTM engineer, why sales experience matters more than an engineering background in this role, and why humanity and empathy are the one thing an agentic workflow can't afford to lose.

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:21) What Arda Does: Kanban for Small and Mid-Size Manufacturers
(1:14) Running GTM Like a Product Team: Sprints and Small Sample Sizes
(2:14) The Most Valuable Build: Context and Reference Layers, Not Campaigns
(5:11) Moving Headless: Agents, Decision Trees, and Fewer Burned Tokens
(6:49) Andrew's Journey: Founding AE to Full-Time GTM Engineer
(8:44) Predictions: Headless GTM, Context Engineering, and Keeping the Human Element
(14:13) Advice for New GTM Engineers: Stop Starting, Start Finishing

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🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

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📧 Email - saurabh@salesrobot.co

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