GTM Engineer School Podcast

About our guest — Laurens NysLaurens Nys is the founder of GTM Sigma, a studio that builds AI-led GTM systems. He is a prominent voice in the GTM engineering community, known for his practical job descriptions for the role and his advocacy for dynamic, signal-based TAM lists. Laurens is an expert in N8N a workflow automation tool, and uses it to create powerful and efficient GTM motions.He is passionate about building systems that help companies acquire, retain, and grow their customer base. Laurens —  also a lead instructor at GTM Engineer School cohort 2 — is a a strong proponent of using automation to drive efficiency and growth.Core takeawaysGTM Engineering from First Principles: A GTM engineer is someone who builds systems to get, keep, or make customers worth more. It’s about applying an engineering mindset to the entire go-to-market process.The Convergence of Factors: The rise of GTM engineering is the result of several factors, including the end of the “growth at all costs” era, the increasing importance of efficiency, and the advent of AI.The System is Key: The specific CRM or tools used are less important than the underlying system. As long as the tools have a decent API, a GTM engineer can build an effective system around them.The Intelligence Layer: The core of a modern GTM stack is the intelligence layer, which for Laurens is N8N coupled with AI. This is where the data is processed, and the decisions are made.Finding the Constraint: To effectively design a GTM system, it’s crucial to identify the bottleneck in the customer journey. This allows the GTM engineer to focus their efforts on the area that will have the greatest impact.Top quotesOn GTM engineering: “A GTM engineer is just someone that builds systems to get, keep, or make customers worth more.”On the importance of systems: “I don’t really care about CRM as long as I can interact with it, meaning it has an API that’s not complete s**t. I’m fine.”On the modern GTM stack: “You have a database where obviously all the data lives. And then two, you have kind of the intelligence layer or kind of the brain of the operation. And for me, that’s N8N coupled to either workflows or some sort of an AI system.”On identifying the bottleneck: “The top of the bottle usually is the bottleneck. So outbound is a very common one.”Referenced tools and resourcesCRM: Atio, HubSpotLLM: OpenAI (ChatGPT), ClaudeEnrichment/Scraping: Bright Data, Rapid APIWorkflow Automation: N8NTimestamps(02:08) Laurens’ definition of GTM engineering(03:07) The factors that led to the rise of GTM engineering: efficiency and AI(04:33) Lightning Round: Favorite CRM (Atio, HubSpot)(05:13) Lightning Round: Top LLM (OpenAI/ChatGPT, Claude)(05:46) Lightning Round: Top enrichment tool (Bright Data, Rapid API)(06:54) Laurens’ top overall GTM engineering tool (N8N)(07:09) The most underrated GTM engineering tool (Bright Data)(08:22) The building blocks of Laurens’ GTM stack: database, intelligence layer (N8N), and interaction layer(10:14) Identifying the bottleneck in the customer journey(12:53) A deep dive into a GTM play for a company with a planning API(16:19) A walkthrough of the N8N workflow for the planning API use case(20:27) How to get good at N8N: project-based learning(21:53) Emerging skills for GTM engineers: GTM knowledge and technical fundamentals(23:16) The importance of mental models and learning how to think(26:18) Advice for aspiring GTM engineers: figure out your skill gaps and fill them(28:42) Why Laurens switched from Clay to N8N(29:48) How to build maintainable GTM systems in a rapidly changing tool landscape(31:33) The future of GTM engineering: will we be rebuilding systems every year?How to connect with LaurensLinkedInGTM Sigma This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit gtmengineerschool.substack.com

About our guest — Nico DruelleNico Druelle is the founder of The Revenue Architects, a consultancy that helps B2B SaaS companies build and scale their revenue engines. He is a leading voice in the GTM engineering community, recognized for his early advocacy of the role and his expertise in building signal-driven GTM motions for companies like Attention, Descript, and Preply. Before launching The Revenue Architects, he led GTM ops at Melio, scaling pipeline with advanced workflow tools.Core takeawaysThe Evolution of Rev Ops: GTM engineering is a consolidation of skills from traditional Rev Ops, Marketing Ops, and data engineering. The modern GTM engineer is an architect, a data expert, and an executor, all in one.The Power of Consolidation: A single GTM engineer can replace a team of specialists, leading to increased speed, efficiency, and ROI. This consolidation reduces friction and allows for faster iteration and validation of growth experiments.The Modern GTM Stack: The core components of a modern GTM stack include a data layer (data warehouse), an orchestration layer (Clay, Cargo), an engagement layer (Unify), and a CRM (Salesforce).The Scarcest Resource: The ability to set up and iterate on a holistic GTM system is the most valuable and scarce resource, not the data or the tools themselves.Top quotesOn GTM engineering: “Go-to-market engineering is a discipline of orchestrating first party data and third party data into a system of action, system of engagement to execute a given vision, a given go-to-market strategy.”On the GTM engineer’s role: “He’s that glue that comes in, just runs experiments, know, test things out, get some results filled back from the market and keep on iterating. And ultimately the uniqueness of that position is that he generates pipeline.”On the evolution from Rev Ops: “If rev ops was the before and go to market is the now or after, I think there is a bit of a consolidation of function of skills.”On the value of a GTM engineer: “The scarce resource is basically the ability to set up that system altogether as a holistic solution and iterate on it to build a defensible system to design growth. That is the real value in this.”Referenced tools and resourcesCRM: SalesforceLLM: OpenAI (ChatGPT), ClaudeEnrichment & Orchestration: Clay, CargoEngagement: UnifyWorkflow Automation: N8NTimestamps(02:13) Nico’s definition of GTM engineering(03:58) The before and after of GTM engineering(06:24) The GTM engineer as an architect, plumber, and electrician(08:19) Why the GTM engineer role is a consolidation of multiple roles(09:45) The benefits of consolidation: speed and less friction(12:10) Lightning Round: Favorite CRM (Salesforce)(14:18) Lightning Round: Top LLM (OpenAI/ChatGPT)(16:19) Lightning Round: Top enrichment tools (Cargo and Clay)(17:23) Nico’s top GTM engineering tools (Unify)(19:16) The core building blocks of Nico’s GTM stack(23:12) The role of a tool like Default for PLG companies(24:25) Tradeoffs in designing GTM stacks: modularity vs. speed(27:13) A deep dive into a PQL nurturing flow built for Descript(31:26) The importance of evaluations (evals) in AI model performance(37:53) Essential skills for aspiring GTM engineers: data literacy, tool fluency, and business acumen(40:10) How to acquire GTM engineering skills(42:14) The importance of feature engineeringHow to connect with NicoWhere to find NicoLinkedInThe Revenue Architects This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit gtmengineerschool.substack.com

About our guest — Jason PulliamJason Pulliam is a fractional CMO and founder of Vitality Marketing Firm, specializing in helping early to mid-stage B2B companies ($1-20M revenue) develop differentiated messaging and execute high-ROI outbound campaigns.As one of Octave’s most vocal power users, Jason has built a reputation for diving deep into deliverability, leveraging AI for prospect research, and proving that campaign quality always beats volume. His approach combines old-school direct response copywriting principles with modern GTM engineering tools to deliver predictable revenue outcomes—often within 90 days.Core takeawaysGTM Engineering defined: “Building the infrastructure that turns signals into revenue. It’s sales ops and marketing automation, but the tooling and the data are where the decision-making converges to move the money.”The stack transformation: Before GTM engineering, we were slaves to our tools. APIs didn’t exist, Zapier was the only power user option, and your stack dictated your motion. Now the stack conforms to the motion—builders design for control, not convenience.Clay as infrastructure: “Clay is the Zapier of our time. I’m not even using their native enrichment tools—I’m using their API to bring in my own tools. At some point we’ll look back and say Clay was the Zapier of yesteryear.”Messaging is non-negotiable: “No matter what else you do, if you don’t have your messaging right, it doesn’t matter how cool and automated and signal-led your whole GTM is.”The $40K case study: A lower mid-market M&A client with only 6,000 targetable prospects. Jason’s team sent signal-stacked emails mentioning overnight packages, got 50 replies, sent 50 physical packages, and converted 5 deals worth several hundred thousand in fees—10x ROI.Deliverability over warm-up: Email Bison and Email Guard are underrated tools that give granular control over deliverability. They’re designed for power users who already know how to send cold email, not first-timers.The 60-day learning curve: For every client, Jason spends the first 60 days capturing every reply variation and objection. After building 50-60 different reply templates, the subject matter expert can step back—the system knows all the answers.AI as knowledge base: Jason uses Typing Mind to load entire copywriting books, client playbooks, and reply templates. This creates a constantly-improving knowledge base that educates virtual assistants and SDRs on how to respond to any scenario.Build your database: Track every email subject, body, and reply rate. After 50+ campaigns, dump it into AI and ask: “What are the patterns? Why did these work?” This is how you develop true campaign intelligence.Study the greats: Read direct response copywriters like John Caples, Eugene Schwartz, Gary Halbert, and David Ogilvy. Load their books into AI and ask them to help you think through problems. Their logic still holds because it’s based on fundamental human psychology.Top quotesOn messaging: “Octave helps you figure out who your target market is and how to talk to them. Even at a fundamental level, it helps you think out what problems you solve for different categories of people.”On Clay’s role: “Clay is kind of the Zapier of our time. It’s just a connector into everything. Even if I think about Clay, I’m not even using the enrichment tools that they have native—I’m using their API and going and bringing in my own tools.”On authenticity in AI: “In an age where everything is now free and unlimited and looks real but it’s fake—an age of ‘frake’—being authentic now stands out. Your brand now matters more because if everybody’s selling the same stuff, what makes you different? It’s your brand and your history.”On learning from clients: “Every single time I start with a new client, I’m like, I don’t know what the answer is, but I’m going to be able to solve it. After 60 days, I normally can eliminate the subject matter expert from the loop because we already know all the answers.”On campaign quality: “I care more about how it works than how fast it scales. I can’t afford to just keep trying different things at high volume. Every single time something doesn’t work, I go all the way back.”On direct response wisdom: “80% of the answers are within 20 feet of where the work’s being done. If you can figure out how your ICP thinks, it answers a lot of other downstream problems.”On the weekend reading assignment: “If you have eight hours, read ‘Made to Stick.’ That book will make you understand why some of your campaigns and messaging work and others don’t.”Referenced tools and resourcesTyping Mind: Multi-LLM interface that lets Jason run Claude, ChatGPT, and other models side-by-side for the best output per taskOctave: Messaging platform for structuring ICP, playbooks, and value props—Jason’s top GTM engineering toolClay: Data orchestration and enrichment platform (”the Zapier of our time”)Email Bison: Underrated sequencer with granular deliverability controlEmail Guard: Partner tool to Email Bison for deep email deliverability managementInstantly / Smartlead: Alternative email sequencers (Jason prefers Email Bison for control)AirScale: Obscure enrichment tool for accessing founder dataBetterEnrich: Custom data enrichment sourceOcean.io: Lookalike enrichment providerCopywriting Books“Made to Stick” by Chip Heath and Dan Heath: Jason’s #1 weekend reading recommendation“Breakthrough Advertising” by Eugene SchwartzJohn Caples (”They Laughed When I Sat Down at the Piano”)Gary Halbert (direct response legend)David Ogilvy (advertising fundamentals)OtherCommercial scanner: Jason uses this to gut books and load them into AI (cuts the spine, scans pages)OpenRouter: Subscription service for accessing multiple LLM APIs through one accountTimestamps(00:00) Introduction to Jason Pulliam and Vitality Marketing Firm(01:56) Jason’s definition: GTM engineering as “RevOps and growth hacking having a baby”(04:43) The shift from tools controlling motion to motion controlling tools(06:38) Lightning Round: CRM preferences—why Jason avoids HubSpot and Salesforce(07:24) LLMs: Typing Mind as the “cockpit” for all models(07:52) Top enrichment tool: “Clay all the way baby, I’m married”(08:43) Most underrated tool: Email Bison and Email Guard for deliverability(10:05) Current GTM stack: Typing Mind, Email Bison/Guard, Octave, Clay(13:40) Why Octave is Jason’s #1 GTM tool—messaging before automation(15:11) How Jason uses Octave playbooks to build reply knowledge bases(18:14) The M&A campaign case study: 6,000 prospects, 50 replies, $40K spend,hundreds of thousands in revenue(21:27) Building reply intelligence: 60 days to capture every objection(24:12) Emerging GTM skill: Patience—workflows take time to tune(25:09) Communication clarity: Explaining technical concepts to average users(27:28) Learning advice: Real-life use cases beat endless LinkedIn scrolling(30:42) Where to find JasonHow to connect with JasonLinkedInVitality Marketing This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit gtmengineerschool.substack.com

In this engaging discussion, Patrick Spychalski, co-founder of The Kiln and a former Clay team member, shares his unique insights on GTM engineering. He defines the role of a GTM engineer, emphasizing the importance of merging technical skills with market strategy. Patrick reveals his 'Avengers assembly' approach to custom software, focusing on best-in-class tools like Lovable and n8n. He also details how smart API use can drastically reduce project costs and underscores the necessity of CRM data cleaning for effective operations.

Kellen Casebeer, founder of The Deal Lab, brings his diverse background from luxury tech to health startups to the forefront as he discusses achieving message-market-fit. He emphasizes the importance of systematic outbound testing and market segmentation. Kellen advocates for experimentation over perfection, revealing how running 13 simultaneous campaigns can yield greater insights than perfecting one message. Listeners will be captivated by his innovative strategies, including using AI to enhance outreach and the power of creative signal detection in generating leads.

About our guest — Josh WhitfieldJosh Whitfield is founder of Content Marketing Media (CMM), the only agency globally certified across Clay, Instantly, HeyReach, and Octave—the four cornerstone platforms powering modern outbound strategy. He's also building Signaliz.com while sharing innovative GTM workflows and AI agents across LinkedIn and X.Before diving into go-to-market engineering, Josh spent 15 years in insurance leading agile teams focused on intelligent automation solutions including process mining, API integrations, and robotic process automation. His technical background in AI and automation—before it was mainstream—gives him unique perspective on what truly matters as these technologies democratize.Josh's philosophy centers on creativity over technical prowess, arguing that as AI handles the complex technical work, success comes from institutional knowledge, business understanding, and the ability to orchestrate innovative solutions that others haven't thought of.Core takeaways* The creativity revolution — Why prompt engineering is dead and creative business thinking is the new differentiator* Institutional knowledge over coding — How understanding business fundamentals matters more than technical skills* The alpha signal methodology — Moving beyond basic demographic targeting to find unique buying indicators* AI-powered research workflows — Using Manus AI and other tools to deliver PhD-level competitive intelligence* The democratization paradox — As tools get easier, differentiation comes from creative application not technical mastery* Strategic retention model — How agencies evolve from email senders to trusted AI advisors for sustained growth* The 25% learning rule — Why dedicating a quarter of your time to exploring new tools is non-negotiable* Robotic handwritten notes case study — The wild workflow that automatically sends real handwritten notes to high-value prospectsTop quotesNew Reality of Skills: "If you'd asked me that six months ago, I'd have said prompt engineering. Today, I would tell you, I think it's creativity because you know, I don't write any of my own prompts anymore. I just ask the models to write the prompts for me."On Institutional Knowledge: "The future true impactful GTM engineer has enough institutional knowledge of the business, knows how to go find out and fill in the gaps of what they don't know."The Alpha Signal Philosophy: "Clay calls it the alpha signal and really find that thing that really defines, like, this person is telling me they need to get or be involved in the solution that's being offered and that they have the means or will to do so."On Creative Differentiation: "It takes creativity to not be like everybody else and pull news and funding and job changes. It takes creativity to say, look, I'm gonna go out and I'm going to figure out every time someone inserts a geocode radius outside of a conference location in San Jose."The Learning Imperative: "I spent 25% of my existence doing that... When you take the 10 rich companies in the world and they're all focused on the same thing, that's a clue that you probably should be paying attention to it too."On Accessible Learning: "You could, this could be the first time you've ever heard the word GTM engineering. And if you spend enough time, even just open AI with web search, you can, it can teach you how to build clay tables."Referenced tools and resources* Clay: The orchestration powerhouse that can make 72 API calls per row for enrichment* Octave: Most underrated GTM tool for messaging and copywriting* Claude: Superior for copywriting and email generation over other LLMs* Instantly/Maildoso: Email infrastructure and sequencing platform combination* Manus AI: Advanced research platform delivering PhD-level competitive analysis* Apify & Firecrawl: Web scraping tools for unique data acquisition* PandaMatch: Lookalike modeling for prospect identification* HubSpot/Salesforce: CRM platforms (Josh uses both depending on client needs)* Model Context Protocol (MCP): Advanced Claude integration for enhanced workflows* Cursor & Lovable: No-code development tools for rapid prototyping* Delphi: AI training platform Josh used to build his 560,000-word personal AI assistantTimestamps* (01:24) Josh's background: 15 years in insurance building AI before it was cool* (02:07) Definition deep dive: Why GTM engineering is broader than people think* (04:31) The evolution question: From structured enterprise AI to democratic vibe coding* (07:03) Lightning Round: CRM agnostic, Claude for copywriting, Clay for orchestration* (08:55) Most underrated tool: Octave's game-changing impact on messaging* (09:57) System design: Octave brain, Clay orchestration, Instantly distribution* (12:18) The alpha signal methodology: Finding unique intent signals* (14:07) Technology trade-offs: Managing vendor reliability and rapid AI evolution* (16:14) Client adaptation: Balancing multiple stacks and varying organizational maturity* (18:34) First play strategy: Using demo-quality builds to prove value before onboarding* (21:21) Impact metrics: Retention over conversion as agencies become advisors* (24:37) New skills: From prompt engineering to creativity and institutional knowledge* (27:15) Defining creativity: Balancing business understanding with new tool application* (29:30) The 25% rule: Why Josh dedicates 25% of his time exploring new tech* (32:38) Practical advice: Using free ChatGPT as your learning starting point This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit gtmengineerschool.substack.com

Wesley Hoang, co-founder of Cymate and founder of Akaiza, shares insights from his extensive engineering background at Twitter, Apple, and Experian. He emphasizes the importance of a balanced GTM tech stack, centered on infrastructure, copywriting, data, and operations. Wesley advocates for simple, results-driven workflows over complex ones. He discusses the psychology behind effective copywriting, strategies for market outreach, and the value of communication in GTM engineering. Listeners gain practical tips to overcome analysis paralysis and start building effective workflows.

Bobby Offterdinger, CEO of TAM to Target and former teacher, shares his insights on orchestrating successful go-to-market systems. He likens his work to conducting an orchestra, emphasizing that effective strategy is more than just tools. Bobby discusses the evolution of lead generation, the importance of precision in outreach, and how AI-powered messaging transformed his agency's approach. He highlights innovative strategies for K-12 outreach and stresses the need for a buyer-led mindset in 2025, showcasing his complete system design from signal detection to re-targeting.

About our guest — Jorge B. MacíasJorge Macias is an industrial engineer turned GTM engineering wizard who scaled the first Puerto Rican YC-backed startup from zero to $3M ARR.He's now a go-to-market engineering consultant and advisor helping B2B SaaS companies turn messy data into synchronized revenue engines.Jorge operates and advises multiple startups on sales, PLG, and GTM engineering while sharing his workflows with thousands of GTM operators on LinkedIn. We recorded this just one month after he became a dad — proving that if he can revolutionize go-to-market operations with a newborn, there's no excuse for the rest of us.Core takeaways* The perfect definition of GTM engineering: "RevOps and growth hacking having a baby"* How to replicate your best seller's "secret sauce" and scale it across your entire team* The Series A GTM stack: Essential tools for companies approaching $1M ARR* His favorite technographic play using job descriptions for targeted campaigns* The two emerging skills every GTM engineer needs: patience and clarity* Why real-life use cases beat endless LinkedIn scrolling and course consumption* The simple LinkedIn data hack that revives stale leads every 3-6 months* How AI transforms manual 45-minute meeting prep into automated prospect research* Why GTM engineering is "more art than science" and what that means for youTop quotesBest definition of GTM Engineering: "If RevOps, marketing operations, sales operations, data engineering and growth hacking had a baby... It's turning messy data, tools that are scattered around, half-baked playbooks into one automated synchronized work."The transformation: "Instead of having one awesome seller and a lot of mediocre salespeople, you're gonna have a lot of average salespeople, which is good for business models because it's gonna be more predictable."On tool selection: "Look for the tools that are right for the stage that you are in your company and the stage that you are in your go-to-market journey."Learning philosophy: "The real value in go-to-market engineering comes from practice and from building workflows that are going to be living out there in the world... New skills are like sports—you need to get the reps."Referenced tools and resources* HubSpot: Jorge's go-to CRM for most clients* Salesforce: Enterprise CRM option* Attio: Modern CRM Jorge wants to test* Clay: Primary data orchestration and enrichment platform* Lemlist: Preferred sequencer for multi-channel outreach (LinkedIn + email)* Smartlead & Instantly: Alternative email sequencers* RB2B: Website visitor tracking and identification* Notion: Jorge's current CRM and wiki repository* Apify: Go-to scraping tool with extensive actor library* Phantom Buster: LinkedIn automation and network growth* ChatGPT: Browser-based AI conversations* Claude (Anthropic): API integrations within other tools* Gemini, DeepSeek: Additional AI model options* Reoon: Underrated email verifier ($80 for 100k verifications + 500 daily credits)* NeverBounce: Alternative email verification* Apollo, Lead Magic, Prospeo: Lead generation databasesTimestamps* (00:00) Introduction to Jorge Macias and GTM engineering fundamentals* (01:56) Jorge's definition: "RevOps and growth hacking having a baby"* (02:57) The biggest transformation: Replicating your best seller's secret sauce* (04:43) How AI scales what already works without reworking everything* (06:38) Lightning Round: CRM preferences - HubSpot vs Salesforce vs Attio* (07:24) LLMs: Claude vs ChatGPT for different use cases* (07:52) Top enrichment tool: "Clay all the way baby, I'm married"* (08:43) Most underrated tool: Reoon email verifier at $0.0008 per verification* (10:05) Jorge's current GTM stack: Notion CRM, Clay orchestration, RB2B tracking* (13:40) Why Notion as CRM: 8 years of familiarity and wiki integration* (15:11) Series A GTM stack recommendations for $1M ARR companies* (18:14) Jorge's favorite GTM plays: Technographic data + job description mining* (21:27) Automated meeting prep: From 45 minutes to AI-generated prospect research* (24:12) Emerging GTM engineering skills: Patience with complex workflows* (25:09) Communication clarity: Explaining technical concepts to average users* (27:28) Learning advice: Real-life use cases beat endless content consumption* (28:42) Sports analogy: Practice builds mental connections, not just watching* (29:19) Practical tip: Download LinkedIn data for automated prospect revival* (30:42) Where to find Jorge and his new GTM engineering consultancySubscribe to never miss the next episodes, playbooks, frameworks, or deep dive. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit gtmengineerschool.substack.com

I sat down with Jared Brickman to find out what he’s been learning from having helped half of the 550 Insight Partners portcos implement AI to drive more growth and efficiencyHere are 10 key lessons learned.1. Buying Tools Isn’t a StrategyToo many leaders assume that buying ChatGPT or Copilot and handing it to their teams will yield breakthrough performance. It won’t. Brickman emphasized that real results require systemic workflows tied to core KPIs—not just generalized tool access."We’re well past the prompt-sharing stage. You need coordinated systems to move the needle."2. From Prompts to Playbooks to Deep InterventionsInsight’s journey evolved from prompt training in 2023, to replicable "recipes" in 2024, and now to hands-on deployments. The difference-maker? Structured use cases that tackle specific business problems.Case studies became playbooks. Playbooks became MVPs. That’s the flywheel that creates repeatable success.3. How Insight Engages with PortCosInsight works in two ways:* Structured design: Mapping processes, finding bottlenecks, and building from there.* Solution-led prototyping: Bringing working templates and helping companies deploy fast.One LA-based portfolio company built a working AI-powered campaign system in a single-day hackathon—Ops upstairs, marketing downstairs, launching side-by-side.4. A Simple GTM AI Prioritization FrameworkBrickman’s 4-part approach:* Automate inbound lead response.* Engage high-intent outbound signals.* Scale campaign capacity.* Support the deal team with co-pilots and admin tools.Post-sale? Apply the same lens, with a bonus focus on Tier 1 customer support.5. Real Examples of Real Results* 6sense: Moved from 50% to 100% SLA compliance by deploying conversational bots when reps didn’t respond in time—generating 20% of pipeline.* Cybersecurity firm: 10x’ed campaign output with a self-serve campaign builder.* E-commerce platform: 100x’ed first-page keyword rankings by auto-generating long-tail SEO content from support docs.6. Don’t Default to New ToolsIf you’re locked into an existing stack, don’t jump ship. Brickman recommends mapping pain points and evaluating if your current tools (like Zapier or Make) can handle it—especially with the new LLM-based extensions.7. Build vs. Buy Varies WidelyLarger companies often build in-house using Snowflake or AWS. But some early-stage companies skip hiring altogether and start with AI agents. Brickman sees success in both paths.8. Structure and Coordination Matter More Than TitlesAn AI committee or center of excellence is essential at scale. One cautionary tale: a PortCo built their own Clay-like tool—without realizing the CMO had already bought Clay.9. The Power of the PortfolioInsight fosters cross-company collaboration through its Onsite Expert Hour series, cohort training, and shared libraries of prompts and Zaps. It’s a living lab of what’s working.10. The Rise of the AI Org ChartBrickman sees a future where employees direct—not operate—AI agents. Multi-agent architectures are already mimicking org charts. Humans are stepping up into strategic roles while agents handle coordination and execution."Think of it as managing an intern—one that can scale."Final ThoughtsThe takeaway? Don’t chase the shiniest tools. Start with business problems, build systems around them, and scale what works. As Brickman puts it, "It’s not hype anymore. It’s traction."Want more sessions like this? Learn more at GTM Engineer School.Watch the full interview here at our Youtube channel: This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit gtmengineerschool.substack.com