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 - saurabh@salesrobot.co

🙏 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.

In today's episode, I chat with Neil Milne, who runs his own GTM agency about running B2B GTM systems for newly funded startups.

Neil breaks down how his agency steps in when founders are trying to decide between hiring a VP or a rev ops person, and instead helps them segment their ICP and build a repeatable system from scratch. He shares his favorite recent campaign for a London-based client: instead of pitching services cold, they built an event-based outbound campaign, inviting high-ticket prospects to in-person gatherings where the real conversions came from conversations on the floor, not RSVPs. We trace his path from a university clothing brand with zero marketing knowledge, into SEO, then rev ops, and finally GTM engineering as the label that tied it all together. Neil's prediction is that the engineers who stay ahead won't be the ones chasing every new tool, but the ones who stay curious and keep adapting. His advice for anyone starting out: don't wait to have it all figured out, get in and run your first campaign, since burning through a few thousand tokens on a failed test teaches you more than any amount of reading.

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:44) What Neil's Agency Does: helping newly funded B2B startups build a GTM system and refine ICP
(3:02) Neil's Standout Campaign: an event-based outbound campaign for a London client
(4:44) Why Trust Ladders Beat Cold Pitches: applying old marketing principles to modern GTM
(7:35) The Multi-Touchpoint Journey: lessons from e-commerce and D2C marketing
(7:39) Neil's Journey: from a university clothing brand to SEO to rev ops to GTM engineering
(10:37) Predictions: why curiosity, not tool mastery, will define the best GTM engineers
(12:54) Advice: get in and run your first campaign, learn by doing

🔗 CONNECT WITH NEIL

👥 LinkedIn

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - saurabh@salesrobot.co

🙏 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 Robert Li, director of AI at Australia GTM, about what happens to GTM engineering once agent swarms start doing the work tools used to do. Robert breaks down how Australia GTM takes founder-led, scrappy startups from GTM strategy through to GTM and AI engineering, often working with VC-backed companies out of the Vesta community.

He walks through a client project building a conversational intelligence platform inside a Claude project driven entirely by Markdown files, used by non-technical operators for scheduled call prep, semantic theme tracking, and even generating L&D courses on demand. He shares the stat that orgs spend roughly $1.90 on training for every $1 spent on SaaS, and why cutting that complexity into a chat interface is the real creative work now. Robert also talks through his own path from solutions architecture, his current workflow of running ideas through Perplexity's deep research and multi-model councils before ever building anything, and why he thinks thinking, not doing, is where the value has shifted. He closes with his prediction that agent swarms and MCP servers will handle more of the glue work, and his advice to build GTM strategy skills underneath the tools, since tools change fast and the underlying thinking doesn't.

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:44) What Australia GTM Does: from GTM strategy to GTM and AI engineering for VC-backed startups
(2:53) Why GTM Engineer Is a "Unicorn" Role: systems thinking meets go-to-market sense
(6:37) Building Their Own LinkedIn Automation System Before Tools Like Sales Robot Existed
(8:05) The SaaSpocalypse: embedding Claude as an AI operating system for clients
(8:31) Case Study: a conversational intelligence platform built on Markdown files inside a Claude project
(11:02) The $1.9-per-$1 SaaS Training Cost and Why Cutting Complexity Is the New Creativity
(13:12) Rethinking Business Models When Agents, Not Humans, Are the New Users
(18:19) Robert's Workflow: Perplexity deep research, model councils, and Claude planning mode before building anything
(21:35) Predictions: agent swarms, MCP servers, and why GTM strategy still matters underneath the tools

🔗 CONNECT WITH ROBERT

👥 LinkedIn
💻 Website

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - saurabh@salesrobot.co

🙏 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 Nicolas Goehler, who leads GTM and ops at MPM Labs, about breaking out of email and LinkedIn entirely and building outreach around Telegram for the web3 and blockchain space.

We get into why MPM Labs focuses on connecting crypto-native startups (prediction markets, perp DEXs, trading platforms) with the right users and partners, and why Telegram now outperforms LinkedIn for reply rates in that world. Nicolas walks through the flow he built over the past three months to pull Telegram and Twitter usernames for LinkedIn prospects, so cold outreach can move to the channel busy executives actually check. We also trace his path from building "Duolingo for crypto" as a teenager, to working b2b sales in commercial real estate finance on Wall Street, to landing in GTM engineering by merging tech, sales, and content skills. He shares why he thinks GTM engineering is one of the few roles AI won't shrink over the next five to ten years, why fractional GTM work is a smart path for young professionals, and his advice: don't limit yourself to what seems possible, keep pushing Claude Code with follow-up questions, and build your own playbook instead of copying what you see online.

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:21) What MPM Labs Does: full-circle web3 consultancy for prediction markets, perp DEXs, and trading platforms
(1:50) MPM's Internal Campaign: shifting from LinkedIn to Telegram for crypto outreach
(3:00) The Flow: pulling Telegram and Twitter usernames from LinkedIn prospects
(4:50) Choosing Channels: WhatsApp in India vs. Telegram in web3, and why unsaturated channels win
(6:59) Nicolas's Journey: from teenage crypto trader to "Duolingo for crypto" founder
(8:31) Pivot to B2B Sales: Wall Street commercial real estate finance
(9:36) Becoming a GTM Engineer: merging tech, sales, and content skills
(12:01) Predictions: why GTM engineering will grow, not shrink, over the next 5-10 years
(12:52) Fractional GTM Work: why it's a strong path for young professionals
(16:02) Advice: don't limit yourself, keep pushing Claude Code, and build your own playbook

🔗 CONNECT WITH NICOLAS

👥 LinkedIn

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - saurabh@salesrobot.co

🙏 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 CheeTung Leong, founder at The GTM Architects, about helping mid-size B2B software and services companies build genuinely AI-native go-to-market systems—not just bolting AI onto the same old ZoomInfo and Outreach pipeline.

The campaigns he walks through are real problem-solving exercises: finding car washes and narrowing a massive TAM down by digging into public records for how much each one actually spends on water, and building first-party signal systems for a 100K-user client by pulling together HubSpot, Postgres, and product analytics to define custom lead states and the next best action for each one. CheeTung's background is 10 years as a tech founder—enterprise consulting selling to Fortune 500s, a venture-funded startup raised to Series A and $3M ARR with a 14-person GTM team, a bootstrapped SaaS attempt, and eventually building The GTM Architects after deciding not to push a dying edtech business uphill. He's now running 70% of his work through Claude Code, building a skill that pulls from nine or ten sources—DKIM/DMARC settings, website HTML stack detection, social posts—into an Opus-strategist agent that outputs full pre-call research documents, and he's publishing fully-sourced 3,700-word blog teardowns weekly using the same system, work that used to take a month per article. His prediction: the bleeding-edge GTM engineers will burn out as starving artists while tools like Clay move upmarket toward enterprises who'd rather hire average operators than chase geniuses—but the fundamentals of people-to-people selling won't change, just the speed at which the tooling evolves. His advice: take on early clients for free to build proof, then charge, and remember the build itself is commoditized now—your own thinking is the only thing that isn't.

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:27) What The GTM Architects Does: AI-Native GTM Systems for Mid-Size B2B Companies
(2:06) The Car Wash Campaign: Narrowing TAM by Digging Into Public Water Spend Records
(3:05) First-Party Signal Systems: Combining HubSpot, Postgres, and Product Analytics for 100K Users
(7:08) CheeTung's Journey: Enterprise Consulting, a Series A Startup, and Shutting Down to Build GTM Architects
(9:06) Running 70% of Work Through Claude Code: The Pre-Call Research Skill Across 10 Sources
(11:46) Publishing Fully-Sourced 3,700-Word GTM Teardowns Weekly With Fable 5
(14:03) Predictions: The Starving Artist GTME, Clay Moving Upmarket, and Why the Fundamentals Won't Change
(19:22) Advice: Take Early Clients for Free, Then Charge—The Build Is Commoditized, Your Thinking Isn't

🔗 CONNECT WITH CHEETUNG

👥 LinkedIn
💻 Website

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - saurabh@salesrobot.co

🙏 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 Brian Attarbashi, founder at AI Bees and AI Ark, about what it actually takes to run a 50-person outbound agency across 17 countries while simultaneously building a data tool designed to fix the exact problems you keep running into as an agency.

AI Bees delivers what Brian calls "meet me leads"—qualified replies handed to an AI that takes the conversation from interested to booked meeting—across cold email, LinkedIn outreach, and a content-plus-engagement layer where AI jumps in on every like, comment, or share to start a conversation. AI Ark came out of watching agencies hammer outdated Apollo scraper data and never knowing which client a contact was used for—so they built fresh 30-day-max data with keyword search on profiles, eating their own dog food with every campaign. The most honest part of this episode is Brian's breakdown of churn: clients leave even when you deliver perfect results, because the sales team doesn't close, the product isn't ready, or they just run out of budget—so AI Bees built a churn risk score from bi-weekly account manager calls, an AI that scores the conversation 1-10 and triggers a recovery plan when it gets high. His path started in 2018 with his brother, discovered the math of recurring revenue through a white-label LinkedIn tool, hit a million in 18 months, and put all the profits into building AI Ark. His advice: master data hygiene and inbox delivery before touching tools, and stay on top of the game through YouTube University.

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:22) What AI Bees Does: Meet Me Leads, LinkedIn Content, and AI-Powered Conversation Nurture
(2:39) What AI Ark Does: 30-Day-Fresh Data and Keyword Search on Profiles
(4:18) Why Brian Built AI Ark: Outdated Scraper Data and No Campaign Attribution for Agencies
(7:01) The Real Talk on Churn: Clients Leave Even When You Do a Perfect Job
(9:10) The Churn System: AI Risk Scores on Account Manager Calls, Recovery Plans, and Review Psychology
(13:04) Brian's Journey: White-Label LinkedIn Tool, the Million-Dollar Math, and Reinvesting Into AI Ark
(15:38) Predictions: Personalization Becomes the Norm, Signal Data Grows in Importance, LinkedIn Still Has an Edge
(19:04) Advice: Master the Basics First, Then Stay on Top via YouTube University

🔗 CONNECT WITH BRIAN

👥 LinkedIn
💻 Website

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - saurabh@salesrobot.co

🙏 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 Sashank, GTM engineer at Interact, about what it looks like to run 15 simultaneous demand-generation engines for a category-creation product—where the job isn't capturing existing demand but making people care about a problem they don't yet know they have.

The standout campaign is a segmentation approach that buckets prospects by how urgently the product solves their specific problem, reconstructing their HubSpot in the background from LinkedIn data to simulate their customer base—producing 35-40% reply rates and cutting average sales cycles from 45-50 days down to 18-20. Alongside email and LinkedIn, Sashank is running gifting campaigns, field marketing with Hallmark cards that link directly to the AI agent they're selling, and a "show don't tell" philosophy where every campaign ends with the prospect actually talking to the product. His path is one of the wildest on the show: professional musician, artist manager at 17 with an eight-figure exit he donated, keyframe animation studio founder, pre-sales engineer, SDR, CSM at Factors where he built 200+ automations in 14 months, and now sitting on $1.6M in pipeline solo at Interact within one month. His prediction: the "I'll build it myself" wave will die when people discover the maintenance reality—software ages like fish, not frozen meat. His advice: GTM engineering is an evolution, not an escape from sales—understand GTM deeply before touching the engineering side.

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:21) What Sashank Does: 15 Demand-Gen Engines for a Category-Creation Product at Interact
(1:40) The Psychological Bucketing Campaign: Simulating Prospect HubSpots, 35-40% Reply Rates
(4:39) Show Don't Tell: Every Campaign Ends With the Prospect Talking to the Agent
(6:43) Field Marketing, Gifting, and Hallmark Cards That Link Directly to the Product
(7:51) Sashank's Journey: Musician to Animation Studio to SDR to CSM to GTM Engineer
(12:00) 1,500 Applications, 392 Interviews, 18 Offers—and $1.6M in Pipeline in One Month
(15:49) Predictions: The Build-It-Yourself Wave Will Die When Maintenance Reality Hits
(19:27) Advice: GTM Engineering Is an Evolution, Not an Escape—Understand GTM Before the Engineering

🔗 CONNECT WITH SASHANK

👥 LinkedIn

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - saurabh@salesrobot.co

🙏 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 Maitri Gandhi, product marketer at Hoshizaki America, about what GTM looks like in one of the most traditional B2B industries out there—commercial ice machines and refrigeration.

Hoshizaki sells through a layered channel model spanning dealers, distributors, end users, and consultants, each with completely different priorities, which means Maitri is managing multiple ICPs and messaging frameworks simultaneously rather than one clean persona. She walks through how trade shows are still the primary outreach channel, how sales enablement—brochures, one-pagers, decks, trainings—is where most of her creativity goes, and how ice itself is a surprisingly rich messaging challenge: eight different ice types, each with different density and dilution properties, and a key angle around replacing expensive packed ice with an on-site machine that pays for itself over time. Her path ran from fashion design at NIF in India to fashion marketing in the US to content marketing in fintech and agency roles, until she started asking "who's reading this and why" about every blog she wrote—which led naturally into product marketing. Her prediction: AI is helping sales teams narrow to the right ICP faster and enrichment tools like Clay are solving the data accuracy problem, which frees everyone to focus on what actually matters—the messaging. Her advice: know your ICP before you know your product, because real understanding only comes from actual conversations, not sitting at a desk.

Enjoy 🙂

(0:00) Introduction to The GTM Engineer Podcast
(0:22) What Maitri Does: Product Marketing at Hoshizaki Across Ice Machines and Refrigeration
(0:35) The Layered Channel Model: Dealers, Distributors, End Users, and Consultants — All Different ICPs
(3:52) Sales Enablement as the Creative Engine in a Relationship-Driven Industry
(5:28) Ice as a Messaging Challenge: Eight Types, Density, Dilution, and the Packed Ice Angle
(7:01) Maitri's Journey: Fashion Design in India to Content Marketing to Product Marketing
(10:14) Predictions: AI Narrows ICP Faster, Enrichment Solves Data Accuracy, Messaging Becomes the Focus
(14:18) Advice: Know Your ICP Before You Know Your Product — Real Understanding Comes From Conversations

🔗 CONNECT WITH MAITRI

👥 LinkedIn

🔗 CONNECT WITH SAURAV

🎥 YouTube Channel

🐦 X (Twitter)

📸 Instagram

💻 Website

👥 LinkedIn
📧 Email - saurabh@salesrobot.co

🙏 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.