The GTM Engineer Podcast

In today's episode, I chat with Yuval Canfi, GTM Engineer at Celery, about building custom outbound machines for internal sales teams. Yuval walks through the platform he built at his previous company, Eko: type in a company name and Clay finds the website, pulls threshold signals like headcount, location, and vertical, and ranks accounts by likelihood to close. 

Only the top-ranked companies get the pricier people enrichment, so thousands of prospects get worked efficiently, with agents checking websites and office locations to refine the score. We discuss why the GTM engineer's real customer is internal, the sales or CSM team, and why the job is scaling what top reps already do manually. Yuval shares his path from SDR to business operations to GTM engineering, why GTM knowledge matters more than engineering now that Claude writes the code, and his prediction that Claude becomes the orchestration layer while tools like HubSpot and Clay retreat to their core functions. His advice: start with one small, focused automation in n8n. 

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:29) What Celery Does: Payroll Automation for Enterprises and Yuval's New Role
(1:14) Most Creative Campaign: An End-to-End Outreach Platform Built in Claude
(2:22) What Eko Does: Recapturing Galleries for E-commerce Sellers on Walmart
(2:54) Threshold Signals and Ranking: Clay Enrichment That Only Pays for the Best-Fit Companies
(4:11) Agents for Website and Office Checks Feeding a Custom Scoring Model
(4:51) Why the GTM Engineer's Customer Is Internal: Building for Sales, CSM, and Marketing
(7:15) Scaling What the Top 10% of SDRs Do Manually
(8:20) Yuval's Journey: From SDR and Business Ops to GTM Engineer, n8n to Claude
(10:53) Why GTM Knowledge Matters More Than Engineering
(11:21) Predictions: Tool Consolidation and Claude as the Orchestration Layer
(15:07) Advice: Start Small with One Focused n8n Automation

🔗 CONNECT WITH YUVAL

 👥 LinkedIn 

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW
 If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH
 You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

In today's episode, I chat with Lennart, GTM Engineering Lead at Moss, about running fast-moving SMB outbound across Germany, the Netherlands, and the UK. Lennart supports both BDRs, who focus purely on outbound, and SDRs, who handle marketing handoffs. 

His strongest SDR play targets funnel drop-offs: when someone enters an email but doesn't finish, his team reverse-enriches the account and contact, then personalizes follow-up around what they entered. He also explains why website visitor de-anonymization is much harder under European privacy rules. By prepping accounts with AI, Moss cut BDR research time by 50%, and some signal-based plays convert at roughly double the usual rate, around 10% vs 5%. Lennart shares his path from sales ops at an HR consultancy to building a data team at Moss, then back to IC as AI reshaped the stack. He predicts companies will need multiple GTM engineers to grow without adding headcount, explains why Moss runs production automations in n8n and GitHub Actions while keeping Clay for experiments, and warns new GTM engineers against blindly trusting AI. 

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:31) What a GTM Engineering Lead Does at Moss: High-Velocity SMB Sales in Germany, the Netherlands, and the UK
(1:35) Two Motions: BDRs on Pure Outbound, SDRs on Marketing Handoffs
(1:55) The Funnel Drop-Off Play: Reverse-Enriching Abandoned Signups for Personalized Follow-Up
(2:26) Website Visitor De-Anonymization in Europe: Company-Level Data and Best-Guess Contacts
(3:21) Results: 50% Less BDR Research Time and Signal Plays Converting at 10% vs 5%
(5:05) Lennart's Journey: From Manual Outbound in Google Sheets to Sales Intelligence to GTM Engineer
(8:11) Predictions: Multiple GTM Engineers per Team, Claude Code, n8n, and the "GTM Brain"
(10:37) Why Moss Uses Clay for Experiments but Runs Production in n8n and GitHub Actions
(11:04) Advice: Don't Blindly Trust AI, Keep Doing Manual Checks, and Stay Creative

🔗 CONNECT WITH LENNART
 
👥 LinkedIn 

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW
 If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH
 You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

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

🔗 CONNECT WITH ANDREW

 👥 LinkedIn 

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW
 If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH
 You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

In today's episode, I chat with Aamir Massoud, GTM Lead at Numero, about running precise, signal-driven outbound with a lean team inside one of the more complex enterprise sales environments — the office of the CFO. 

Numero is a vertical AI platform that deploys agents into finance and accounting workflows without ripping out ERPs or CRMs. Aamir breaks down why he starts every GTM build not with a tool but with a written story — who you're selling to, how they're tiered, and why — and how that document becomes the foundation for everything built on Claude after. He walks through a specific campaign where they scraped data on CFOs who had published podcasts, interviews, or articles in the past 90–180 days (via Floid and their connectors), then used those signals to write personalized emails in the prospect's own language — with a human-in-the-loop review step before anything goes out. He shares his prediction that lean GTM pods will keep getting more powerful by pulling signals from product, support, and CS, and closes with practical advice: define the ICP yourself, write the story before you touch any tooling, then pick one workflow, finish it, and move on. 

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast 
(0:21) What Numero Does: Vertical AI for the Office of the CFO 
(2:33) GTM Strategy: Story-First, Then Tooling 
(3:43) Signal-Led Outreach: Triggers, PE Acquisitions, and the Right Timing 
(5:44) The CFO Campaign: Scraping Podcasts and Articles for Deep Personalization 
(7:07) Aamir's Background: Old-School BD Meets Signal-Driven Outbound 
(9:20) 30 Precise Emails vs. 300 Spray-and-Pray 
(10:20) Outbound + Events as a Combined GTM Motion 
(11:14) Filling the Middle of the Funnel Before Asking for a Meeting 
(13:03) Predictions: Lean, Multi-Dimensional GTM Pods Hitting New Heights 
(15:49) Advice for Aspiring GTM Engineers: Start With the Story, Not the Stack

🔗 CONNECT WITH AAMIR

👥 LinkedIn 

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

In today's episode, I chat with Cory Blumenfeld, founder at BlueMoso, about giving business owners their time back by providing virtual talent for ops, admin, SDR, and client-facing roles, mostly for small business owners looking to scale past doing everything themselves. 

Cory breaks down his client acquisition mix, where warm referrals and affiliates lead but personal brand content on LinkedIn drives real pipeline, and why he's exploring Substack to pull his audience off algorithm-dependent platforms and into owned channels. He shares how BlueMoso actually started: after exiting two businesses, he began posting on LinkedIn, brought on a VA he set up for success with real systems, and when other creators kept telling him their VAs weren't working, he realized the systems were the product. That VA is now his business partner, and together they've built a talent pool of over 70 virtual workers in under two years. Cory predicts outsourcing grows alongside AI rather than losing to it, with human experience becoming the premium tier as AI-only interactions become the default, and closes with advice for business owners: not adopting AI now is the real risk. 

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast 
(0:26) What BlueMoso Does: Virtual Talent for Business Owners 
(2:17) Client Acquisition: Referrals, Affiliates, and Building a Personal Brand 
(3:07) Why Cory Is Exploring Substack Over Chasing Viral LinkedIn Content 
(7:20) Cory's Journey: From Two Exits to Building BlueMoso With His VA 
(10:12) Predictions: Outsourcing Grows Alongside AI, Human Experience Becomes Premium 
(16:19) Advice: The Risk Is Not Adopting AI

🔗 CONNECT WITH CORY

👥 LinkedIn 
💻 Website 

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

In today's episode, I chat with Tamara Omomo, GTM engineer at Everphone, a device-as-a-service company that manages end-to-end device procurement for mid-size to enterprise fleets. 

Tamara walks through her account-monitoring build for enterprise buying committees: an agent that tracks news, podcasts, and LinkedIn activity for mapped stakeholders and alerts her team to engage in a relationship-first way, paired with synthetic personas built from years of past sales transcripts so outreach is tailored by job title down to the individual contact. She shares her path from growth marketing, where broken attribution and disconnected systems pushed her toward automation, HubSpot dashboards, and eventually Clay, before rebranding herself into GTM engineering two years ago. She also talks about Berlin's growing GTM engineering scene versus the more saturated US market. Tamara predicts agentic AI will increasingly absorb SDR work, more teams building in-house tools over relying on SaaS, and personalization at scale becoming the norm, and closes with advice for beginners: relax, pick one or two tools instead of chasing every new one, solve the actual problem before reaching for a tool, and stay off LinkedIn hype. 

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast 
(0:33) Tamara's Role as In-House GTM Engineer at Everphone 
(2:04) What Everphone Does: Device-as-a-Service for Enterprise Fleets 
(3:16) Campaign: Monitoring Buying Committees and Building Synthetic Personas 
(8:09) Tamara's Journey: From Growth Marketing to GTM Engineering 
(10:36) The GTM Engineering Scene in Berlin vs. the US 
(11:28) Predictions: Agentic AI, In-House Tools, and Personalization at Scale 
(15:07) Advice: Relax, Pick Your Tools, and Solve the Problem First

🔗 CONNECT WITH TAMARA

👥 LinkedIn 
💻 Website 

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

In today's episode, I chat with Himanshi Shah, founding GTM engineer at Scaletopia, about running outbound exclusively for marketing agencies that are too busy serving their own clients to book new business for themselves. 

Himanshi walks through two campaigns: one pulling Product Hunt launch data into automation tools to reach founders right as they ship, and another sourcing companies that just went ISO 27001 compliant straight from news releases and LinkedIn, then enriching and targeting the right people inside each one. She shares her unplanned path into GTM, from a data analyst offer at PayPal that fell through after an accident, to an insurance job, to a US startup where she taught herself make.com in five days and became an automation engineer, eventually landing the founding GTM engineer title at Scaletopia. She predicts AI agents will become the decision makers in outbound while humans shift into operating them, and closes with advice for beginners: take things one step at a time, learn the sales fundamentals before jumping into Clay and automation tooling. 

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast 
(0:27) What Scaletopia Does: Outbound for Marketing Agencies 
(1:27) Why Himanshi Chose This Niche and Now Handles 15 Clients Solo 
(2:07) Campaign: Sourcing Leads from Product Hunt Launches 
(2:54) Campaign: Targeting Companies That Just Went ISO 27001 Compliant 
(4:26) Himanshi's Journey: From a PayPal Offer to Learning Make.com in 5 Days 
(6:49) How Scaletopia Happened After a Leadership Change 
(7:43) Predictions: AI Agents as Decision Makers, Humans as Operators 
(8:58) Advice: Learn the Sales Basics Before Jumping Into Automation

🔗 CONNECT WITH HIMANSHI

👥 LinkedIn 

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

In today's episode, I chat with Jay, a go-to-market engineer at Clay, about implementing AI across roughly 50 companies in the past year, from five-person shops in West Texas to 3,000-person organizations. 

Jay walks through his favorite recent build: an AI agent for an electronic sign company that pulls Google Street View images of churches and retail locations, scores the quality of their existing signage, checks zip code wealth and traffic, then hands reps a qualification status, cutting a 15 to 60 minute manual process down to seconds. We get into his signals-driven prospecting framework, where static ICP scoring gets layered with real-time buying triggers so reps wake up to a prioritized account list every Monday. Jay shares his path from private equity to scaling ThredUp's B2B arm to zero to double-digit million ARR, then falling for Clay as an early user before joining. He predicts go-to-market is splitting into an orchestration layer for data infrastructure and an app layer reps build themselves, and closes with advice for new GTM engineers: learn CRM architecture first, then just do it. 

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast 
(0:32) What Jay Does as a GTM Engineer at Clay 
(1:04) The Clients: 50 Companies Implemented in a Year 
(1:52) Creative Campaign: AI Agent Qualifies Electronic Sign Leads via Street View 
(5:21) The Framework: Signals-Driven Prospecting 
(7:12) Jay's Journey: From Private Equity to ThredUp to Clay 
(9:58) Predictions: The Orchestration Layer vs. The App Layer 
(12:39) Advice: Learn CRM Architecture, Then Just Do It

🔗 CONNECT WITH JAY

👥 LinkedIn 

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

In today's episode, I chat with Taiwo, founder at JourneyWise, about building a unified "allbound" platform that captures every touchpoint across marketing and sales instead of treating inbound and outbound as separate stories. 

Taiwo shares a client story where an Australian prospect ghosted after a demo, then returned nine months later citing their LinkedIn content, showing how non-linear the real buyer journey actually is. We get into JourneyWise's guerrilla marketing tactics, from bar-style table cards in co-working spaces to QR codes at coffee stations, and how thinking offline first helped the brand stand out. Taiwo walks through her path from marketing analyst, sitting at the intersection of marketing and sales, to noticing that outbound touchpoints were missing from attribution models entirely and that ICPs diverged between teams. She predicts the next shift is unified execution layers and buyers represented by AI agents evaluating vendors directly, and closes with advice for new GTM engineers: experiment constantly, remix ideas from other creators, and learn how systems, APIs, and workflows connect. 

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast 
(0:33) What JourneyWise Does: The "Allbound" Sales Execution Platform 
(1:44) Client Story: An Australian Prospect Returns Nine Months Later 
(4:16) Guerrilla Marketing: Table Cards and Coffee Station QR Codes 
(6:06) Taiwo's Journey: From Marketing Analyst to Founder 
(9:37) The ICP Misalignment Problem Between Marketing and Sales 
(12:49) Predictions: Unified Execution Layers and AI Agents as Buyers 
(17:56) Advice for New GTM Engineers: Experiment and Learn the Systems

🔗 CONNECT WITH TAIWO

👥 LinkedIn  

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

In today's episode, I chat with Fahad, a GTM engineer with a background in B2B sales, about running signal-based outreach at scale for an enterprise client. 

Fahad breaks down how he built a Clay table pulling multi-location account data through Serpo.dev's HTTP API, running parallel Clay agents to qualify accounts against the client's criteria and segment them into tier one, tier two, and tier three before sourcing contacts. He walks through why precision matters at that scale, since a poorly constrained AI query can hand back the wrong signals and hurt a client's credibility. We trace his path from B2C high-ticket sales, discovering Clay back in 2022, and eventually leaving a stable job to go through Clay's own 101 cohort and AI Skills cohort to build his foundation. His prediction: GTM engineers who over-focus on tools will lose their edge, since AI now handles most of the technical heavy lifting, so the real value going forward sits in strategy, spotting bottlenecks, and knowing how to stitch tools together. His advice for anyone starting out is to cut the noise and focus on learning Clay first, since it teaches you the full process happening behind the scenes. 

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast 
(0:31) What a GTM Engineer Does: infrastructure, messaging, and iteration for revenue growth 
(1:31) Understanding ICP: why the right channel differs by client, from email to LinkedIn 
(3:02) Fahad's Standout Campaign: signal-based outreach using Clay and Serpo.dev's HTTP API 
(4:26) The Account Qualification Process: tiering multi-location accounts for a scaled outbound campaign 
(6:42) Fahad's Journey: from B2C high-ticket sales to Clay's 101 and AI Skills cohorts 
(9:43) AI Agents vs. Clay: comparing Codex-driven list building to traditional Clay workflows 
(10:48) Predictions: why strategy and tool-stitching will matter more than technical skill alone 
(10:54) Advice: cut the noise and focus on learning Clay first

🔗 CONNECT WITH FAHAD

👥 LinkedIn 

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - [email protected]

🙏 LEAVE A REVIEW If you enjoyed listening to The GTM Engineer Podcast, we'd love for you to leave a 5-star review on Apple Podcasts to help others discover the show :)

👋🏼 GET IN TOUCH You can also reach out with any feedback, ideas or thoughts about the lessons you've learned from the episodes.

Fahad's LinkedIn link isn't in the transcript — drop it in and I'll swap it into the connect block.