In today's episode, I chat with Mathew Joseph, founding GTM engineer at Rwazi (a 20-25M ARR Series A AI SaaS for enterprise retail decision-making), about how GTM engineers serve as the centerpiece between marketing, sales, and product teams to identify product-market fit, 10x existing success, and find what's being missed in the market.
We explore his creative social listening campaigns that generated 100K MRR monthly pipeline for a Google-funded 8.5M YC AI startup by focusing on golden influencers (relevant pages/people whose engaged audiences match your ICP on Reddit subreddits and Twitter), using AI to understand context rather than keywords since "the best thing in the AI age is having real interaction" per Sam Altman, and his spin stack approach to enterprise email infrastructure - personalizing emails in one Clay table, then randomizing those personalization in another so 20 daily sends from one mailbox all look different for longer lifespan, with sentiment analysis pushing only positive replies to CRM so sales focuses on selling instead of research and cleanup. Mathew shares his unconventional journey from instrumentation control engineer in India starting a five-year startup in 2015-2017 that failed but gave him "private MBA hard lessons" and business acumen, moving through nine-to-five roles to feel employee pain points, relocating to London when AI entered sales and Clay launched GTM engineering, and spending the past two years learning constantly because "Saturdays and Sundays is time for learning - if you're not, you're out of ammo." He predicts companies without GTM engineers in 2026 will be cavemen while those with them face tight competition as insights shared in communities get expiry dates before mass adoption, and billion-dollar companies will run with 55-100 people instead of thousands due to GTM engineering's 18:1 efficiency ratio (18 traditional roles = 1 GTM engineer + 2 salespeople). Mathew's advice: start with Clay but don't just become a Clay operator - keep learning constantly since both GTM engineering and AI are in early days, trust but verify everything (try tools like Claude Code even if you hate terminals initially), learn JSON/Python basics to understand how software engineers think and structure systems within systems, follow the 75% research / 20% testing / 5% execution approach to break and build things, and develop non-negotiable business acumen because moving the needle from 25M to 50M ARR requires asking the right questions and catching AI's 99% error rate with your eagle eye rather than swallowing everything it says.
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00:00) Introduction to Outbound Wizards
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00:26) What Rwazi Does: AI SaaS for Enterprise Retail Decision-Making
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01:01) "Who Doesn't Have Rwazi Is in Stone Age"
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01:20) Mathew's Role: First Week as Founding GTM Engineer
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01:48) Hired at Series A to Find and 10x Product-Market Fit
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02:16) GTM Engineer as Centerpiece: Marketing, Sales, Product
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02:44) Forward-Looking Clients Let You Define the Role
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03:31) Two-Sided Coin: Internal Analysis + External Market Research
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04:03) ICP Playbook Outdated, Building Agents to Find Middle Segment
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04:43) Varun from Clay Calls It "GTM Alpha"
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05:06) Creative Campaign: Social Listening for Google-Funded YC Startup
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05:28) Social Signals Are a Turnaround, Not Downgraded
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05:40) Sam Altman: "Best Thing in AI Age Is Real Interaction"
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06:03) Recreating Human Touch Generated 100K MRR Pipeline Monthly
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06:42) AI Understands Context, Not Just Keywords
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06:55) Golden Influencers: Relevant Pages with Your ICP as Engagers
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07:47) Fine-Tuning Approach to Find Right Signals in Noise
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08:03) Email Infrastructure: Don't Put All Eggs in One Basket
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08:47) SMBs/Startups Have Gmail, Enterprises Are Different Ballpark
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09:06) Enterprise Requires Warm-Up, Zero Sales Words, Spin Stack
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09:26) Spin Stack: One Table Personalizes, Another Randomizes
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09:45) 20 Daily Sends from One Mailbox All Look Different
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10:06) Sentiment Analysis: Only Push Positive Replies to CRM
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10:49) Sales Focuses on Selling, Not Research and Cleanup
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11:06) Journey from Instrumentation Control Engineer in India
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11:23) Five-Year Startup 2015-2017: Failed But Gave "Private MBA"
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11:44) Business Acumen from Hard Lessons Asking Right Questions
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12:19) GTM Engineering Existed Before, Clay Made It Sexier
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12:34) Data Is Broken, Holding Back Business Success
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12:46) Clay's Waterfall Method vs Single Vendor Reliance
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13:09) Employee View: Understanding Pain from Ground Level
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13:31) Moved to London When AI Entered Sales, Clay Launched
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14:11) Past Two Years: GTM Engineer Experience Same Age as Field
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14:25) Saturdays/Sundays for Learning or You're Out of Ammo
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15:04) Future Prediction: 18:1 Ratio (18 Traditional Roles = 1 GTM + 2 Sales)
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15:18) Companies Without GTM Engineers in 2026 Are Cavemen
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15:43) Insights Shared in Communities Get Expiry Dates
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16:03) Billion-Dollar Company Run by 55-100 People
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16:48) Advice: Starting with Clay Makes You Clay Operator, Not GTM Engineer
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17:20) Constant Learning, Keep Mind Open, Try Before Rejecting
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17:53) Claude Code Example: Hated Terminals, Now Uses Them Constantly
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18:23) Learn JSON/Python Basics to Understand Programming Structure
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18:54) Built Agency Inside Clay, Prompts Got Inefficient, Learned Tokens
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19:21) 75% Research / 20% Testing / 5% Execution
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19:44) Business Acumen Non-Negotiable: Can You Move the Needle?
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20:33) Don't Swallow Everything AI Says - Find Errors with Eagle Eye
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21:10) Closing and Contact Information
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