The GTM Engineer Podcast

Agencies Need Retention Systems, Not Better Outreach ft. Brian Attarbashi

21 min · 29 de jun de 2026
Portada del episodio Agencies Need Retention Systems, Not Better Outreach ft. Brian Attarbashi

Descripción

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 AI Ark came out of watching agencies hammer outdated Apollo scraper data and never knowing which client a contact was used for—so they built fresh 30-day-max data with keyword search on profiles, eating their own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Nurture  (2:39) What AI Ark Does: 30-Day-Fresh Data and Keyword Search on Profiles  (4:18) Why Brian Built AI Ark: Outdated Scraper Data and No Campaign Attribution for Agencies  (7:01) The Real Talk on Churn: Clients Leave Even When You Do a Perfect Job  (9:10) The Churn System: AI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 [https://www.linkedin.com/in/brian-h-attarbashi/]  💻 Website [https://ai-ark.com]  🔗 CONNECT WITH SAURAV 🎥 YouTube Channel [https://www.youtube.com/@_sauravgupta/videos] 🐦 X (Twitter) [https://x.com/saguppa] 📸 Instagram [https://www.instagram.com/saurav_salesrobot] 💻 Website [https://www.salesrobot.co/] 👥 LinkedIn [https://www.linkedin.com/in/saurav-g-43b959225]📧 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.

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157 episodios

Portada del episodio Agencies Need Retention Systems, Not Better Outreach ft. Brian Attarbashi

Agencies Need Retention Systems, Not Better Outreach ft. Brian Attarbashi

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 [https://www.linkedin.com/in/brian-h-attarbashi/]  💻 Website [https://ai-ark.com]  🔗 CONNECT WITH SAURAV 🎥 YouTube Channel [https://www.youtube.com/@_sauravgupta/videos] 🐦 X (Twitter) [https://x.com/saguppa] 📸 Instagram [https://www.instagram.com/saurav_salesrobot] 💻 Website [https://www.salesrobot.co/] 👥 LinkedIn [https://www.linkedin.com/in/saurav-g-43b959225]📧 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.

29 de jun de 202621 min
Portada del episodio Learn Sales Before You Learn Clay ft. Sashank Koundinya

Learn Sales Before You Learn Clay ft. Sashank Koundinya

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 [https://www.linkedin.com/in/sashank-koundinya/]  🔗 CONNECT WITH SAURAV 🎥 YouTube Channel [https://www.youtube.com/@_sauravgupta/videos] 🐦 X (Twitter) [https://x.com/saguppa] 📸 Instagram [https://www.instagram.com/saurav_salesrobot] 💻 Website [https://www.salesrobot.co/] 👥 LinkedIn [https://www.linkedin.com/in/saurav-g-43b959225]📧 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.

26 de jun de 202621 min
Portada del episodio AI Makes Customer Research More Important ft. Maitri Gandhi

AI Makes Customer Research More Important ft. Maitri Gandhi

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 [https://www.linkedin.com/in/maitrigandhi00/]  🔗 CONNECT WITH SAURAV 🎥 YouTube Channel [https://www.youtube.com/@_sauravgupta/videos] 🐦 X (Twitter) [https://x.com/saguppa] 📸 Instagram [https://www.instagram.com/saurav_salesrobot] 💻 Website [https://www.salesrobot.co/] 👥 LinkedIn [https://www.linkedin.com/in/saurav-g-43b959225]📧 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.

23 de jun de 202619 min
Portada del episodio The Future Of Sales Is More Human ft. Tom Dingwall

The Future Of Sales Is More Human ft. Tom Dingwall

In today's episode, I chat with Tom Dingwall, AI Growth Manager at Passionfruit, about why the future of GTM engineering is human connection enabled by AI — not AI replacing humans.  Passionfruit is a freelance marketplace helping companies flexibly resource their teams, with an AI tool (PIP AI) built on top to help marketers free up time from repetitive work and focus on real relationships. Tom's role sits somewhere between SDR and AE — he runs outbound, takes calls, and works deals through to close — and he walks through what that looks like day to day, including how Passionfruit's cold calling unit of four optimizes not just on list quality but on what they're saying in the first few seconds and when they're calling. He makes a strong case for AI as a calendar-clearing tool rather than a headcount-cutting one: use it to find the right companies, research why they're a fit, and then show up to the call with nothing to do but actually connect. We also get into his path — PPE at uni, six months in recruitment, then a co-founder at Passionfruit reached out — and why he ended up in sales specifically because of how human the job is. His predictions for the next few years are clear: companies will split into those that overshoot on AI and lose the human side, those that ignore it and fall behind, and the ones that get the balance right and compound hard. He closes with two pieces of advice: if you don't genuinely enjoy talking to people all day, GTM isn't for you — and if you do, go deep on AI tools, because the people who combine both will be world-class. Enjoy 🙂 (0:00) Introduction to The GTM Engineer Podcast  (0:21) Tom's Role as AI Growth Manager at Passionfruit: SDR, AE, and Everything Between  (1:29) Creative Campaigns and Cold Calling Optimization at Passionfruit  (3:59) How Tom Uses AI to Build Lists — and When He Steps Away From It  (5:18) Why Teams Enabling SDRs With AI Beat Teams Replacing Them  (7:31) Tom's Journey: PPE, Recruitment, and Landing at Passionfruit  (9:49) Predictions: The Three Types of Sales Teams That Will Emerge in the AI Era  (13:35) Advice for Aspiring GTM Engineers: Grit, People Skills, and AI Literacy 🔗 CONNECT WITH TOM 👥 LinkedIn [https://www.linkedin.com/in/thomas-dingwall/]  💻 Website [https://www.linkedin.com/company/usepassionfruit/]  🔗 CONNECT WITH SAURAV 🎥 YouTube Channel [https://www.youtube.com/@_sauravgupta/videos] 🐦 X (Twitter) [https://x.com/saguppa] 📸 Instagram [https://www.instagram.com/saurav_salesrobot] 💻 Website [https://www.salesrobot.co/] 👥 LinkedIn [https://www.linkedin.com/in/saurav-g-43b959225]📧 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.

19 de jun de 202615 min
Portada del episodio Your Offer Matters More Than Your Tools ft. Mohamed Hamdi

Your Offer Matters More Than Your Tools ft. Mohamed Hamdi

In today's episode, I chat with Mohamed Hamdi, GTM Engineer at ISkala Business Solutions, about how clean data and strong offer framing can drive thousands of qualified leads — including 7,000+ interested signups for a single US client.  ISkala builds continuous outbound systems for B2B companies across the MENA region (and select US/UK clients) in SaaS, services, and agency models. Mohamed walks through their Modern Guild case study in detail: the client helps sophomore and junior university students break into finance and consulting internships, and the campaign worked because the offer matched exactly what the audience already wanted. The data source was unconventional — LinkedIn groups where students had publicly left their university emails while asking for internship opportunities, scraped via PhantomBuster, enriched through Clay, and deployed on Dripify. He also breaks down his full campaign process: discovery questionnaires, two-week domain warmup on Smartlead, copy structured around hook → value prop → credibility line → low and high friction CTAs, and their in-house tool InReach which pulls contacts across 30+ vendors including Apollo, ZoomInfo, and BetterContact. We get into his journey into GTM engineering through ISkala's CEO — one of the earliest people to define the role in the MENA region — why LinkedIn groups are one of the most underrated data triggers available today, and how Claude has cut his campaign creation time from four hours down to five minutes. He closes with the same advice he'd give any beginner: learn to build a strong offer first, then learn to work with data. Enjoy 🙂 (0:00) Introduction to The GTM Engineer Podcast  (0:22) What ISkala Business Solutions Does and Who They Serve  (1:43) Modern Guild Case Study: Scraping LinkedIn Groups for University Emails and 7,000+ Signups  (3:52) Full Campaign Build: Data Enrichment, Copy Structure, and Tool Stack  (5:56) Breaking Down the Modern Guild Offer and Why It Worked  (7:47) Mohamed's Path Into GTM Engineering at ISkala  (9:24) AI and Claude: From 4-Hour Campaigns to 5 Minutes  (11:42) Prompt Engineering as the Differentiator in an AI-First Outbound World  (13:26) Advice for Aspiring GTM Engineers: Offer First, Then Data 🔗 CONNECT WITH MOHAMED 👥 LinkedIn [https://www.linkedin.com/in/mohamedhamdiperformancemarketing/]  🔗 CONNECT WITH SAURAV 🎥 YouTube Channel [https://www.youtube.com/@_sauravgupta/videos] 🐦 X (Twitter) [https://x.com/saguppa] 📸 Instagram [https://www.instagram.com/saurav_salesrobot] 💻 Website [https://www.salesrobot.co/] 👥 LinkedIn [https://www.linkedin.com/in/saurav-g-43b959225]📧 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.

18 de jun de 202615 min