GTM Engineer School Podcast

S2E6: "Your List Is the Strategy" | Benjamin Douablin

Listen now | The CEO of FullEnrich unpacks why one data vendor is never enough, how cold calling still wins when the list is right, and why audience-first beats GTM-engineering-first. Brought to you by This could be your logo! Reach out to Jared [https://cal.com/jaredwax] to sponsor the next episode of this podcast and reach 5000+ modern GTM operator and founders. About our guest — Benjamin Douablin Benjamin Douablin is the CEO and co-founder of FullEnrich, the waterfall enrichment platform serving 3,000+ customers across the US, Europe, APAC, MENA and Latam. FullEnrich aggregates 20+ data vendors and queries them sequentially until you get the email or mobile number you actually need — then plugs into the CRM, data warehouse, automation tool, or MCP server you already run. Ben came up through pure sales tech with stints at Sales Ramp and Jellyfish before building an internal data-aggregation tool that became FullEnrich two and a half years ago. Core Takeaways * One Data Provider Is Never Enough: A generalist returns roughly a 30% enrichment rate against most addressable markets. Coverage breaks down by region, by vertical, and by segment. The winning shape is a managed orchestration layer that picks the right provider per query in real time, not a stack of disconnected vendors that operators have to manually benchmark. * Your List Is The Strategy: FullEnrich’s first 40 customers came through cold calls Ben placed himself. The unlock wasn’t the script. It was the prep — convincing yourself the call is a blessing for the prospect before you dial. If there’s no real issue to solve, don’t book the meeting. Open with a “because” that names a problem peers in their industry face, never their own performance, and let them choose the one that resonates. * Audience-First Beats GTM-Engineering-First: The discipline is a means; the audience is the end. FullEnrich serves three distinct audiences (GTM teams, lead-gen and talent agencies, product builders embedding the API). Each one has different acquisition motion, product needs, contract structure. Build squads around the audience, not the tooling — and let GTM-engineering capacity serve the squads where it actually moves the metric. * Stop Building 25-Slide Decks: The bar to execute has dropped; the bar to convince has stayed high. That asymmetry is the lever. If you’re a VP with an idea, hire someone to ship the zero-to-one in days, demo the result, then politick. Pitching internally before you’ve proven anything is the slow path that closes your learning window. Enjoying this episode so far? Subscribe for free to new posts. Top Quotes “I don’t know anyone that is really happy with their data providers, even if they multiply them.” “If you don’t know who you want to talk to, just don’t even think about it, don’t start, because you will get rejected, it will be hard.” “I never start with the tools or with the skills. I always start from my audience or end users.” “Having people that know how great look like is very important because the danger of AI is just very well articulated MBA type of intern that know how to write down very articulated way. But when you go into details, you need to be picky.” Referenced Tools and Resources * Data and enrichment: FullEnrich [https://fullenrich.com/] (aggregating 20+ vendors) * CRM and data infrastructure: Salesforce, Snowflake * Workflow automation: Clay [https://www.clay.com/], n8n, Zapier * AI and agents: Claude Code, MCP server (FullEnrich), HubSpot MCP * Movement origins: “Forward-deployed engineer” (Palantir), GTM engineer (Clay) Timestamps * (02:37) Welcome to S2E6 — the data infrastructure layer of GTM engineering, Ben’s bio (Sales Ramp, Jellyfish, FullEnrich) * (04:13) Ben’s intro — FullEnrich origin, 20+ data vendors, usage-based model, integrations everywhere * (07:13) What’s changed in GTM engineering — the Palantir comparison, why Clay launched the movement * (09:12) Beyond GTM — recruiter and talent acquisition use cases, Snowflake as system of record * (12:07) Where the movement is being oversold — ex-spray-and-prey agencies rebranding as engineers * (14:50) Does GTM engineering 10x the rest of the sales org? The hire profile question * (16:22) Claude Code hype — siloed adoption, FullEnrich’s MCP server, the chat-as-blank-page problem * (20:36) Why one data provider isn’t enough — coverage gaps, the benchmarking pain * (23:08) The orchestration layer — managed waterfall by industry, region, segment * (26:02) Cold calling as a growth lever — your list is the strategy * (28:36) Tone of voice on the call — don’t push, don’t sound salesy, ask permission * (29:51) Have a reason to call — the “because” frame that earns attention * (30:37) Don’t touch the prospect’s ego — name the problems peers face, let them pick * (31:50) What’s next for the enrichment industry — global coverage, verification, decision layer * (34:28) Hiring for GTM in the AI era — what separates good from great * (42:47) AI as the well-articulated MBA intern — polish hides shallow work * (44:20) How FullEnrich structures its GTM org — three audiences, three squads * (50:00) Agencies vs in-house — main motion in-house, $20–50K budget for new motions * (53:41) Stop-doing for VPs — demo the zero-to-one before building the deck * (55:56) Closing — audience first, list is strategy, AI with growth mindset Where to Find Benjamin * LinkedIn [https://www.linkedin.com/in/benjamin-douablin/] * FullEnrich [https://fullenrich.com/] Where to Connect with Jared & Matteo * Matteo Tittarelli, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/matteo-titta/], X [https://x.com/matteo_titta], Website [https://genesysgrowth.com/], Newsletter [https://newsletter.genesysgrowth.com/] * Jared Waxman, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/jwaxman/] Thanks for reading GTM Engineer School! Subscribe for free to receive new posts and support my work. 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 [https://gtmengineerschool.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

S2E5: "Foundations Before Automation" | Mario Moscatiello

Listen now | The VP of Marketing at Airbyte unpacks why every company is now a go-to-market company, the warm outbound playbook that doubled pipeline, and what separates the operators worth hiring in 2026. Brought to you by This could be your logo! Reach out to Jared [https://cal.com/jaredwax] to sponsor the next episode of this podcast and reach 5000+ modern GTM operator and founders. About our guest — Mario Moscatiello Mario Moscatiello is the VP of Marketing at Airbyte, the open source data integration platform with 500+ connectors that moves data between sources and warehouses, CRMs, or activation tools. If you are syncing product signals, stitching together enrichment sources, or moving data between systems at scale, Airbyte is probably already somewhere in your stack. Mario came up the developer-tools path: growth at Pusher in London, then GitBook, then a stint as Principal at Flex Capital and board observer at Strapi, then Head of Growth at FluteStack. He had been advising Airbyte since 2020, four years before joining full-time, so when he stepped into the VP role he already knew the product, the community, and the motion cold. Since joining, Mario has built what he calls a warm-outbound motion that triangulates GitHub signals, product usage, and pricing-page intent through Common Room, Octave, and Clay. That approach doubled Airbyte’s pipeline growth rate. Core Takeaways * Foundations Before Automation Is The Real Step Change: GTM engineering is a step change only when product market fit is in place and revops data is clean. AI is a multiplier of whatever foundation exists. Bad data equals bad signal equals bad results, and AI in the mix is a multiplier effect. Pre-PMF teams hacking GTM with AI just create more damage faster. The two foundations are the PMM hat (personas, competitor, market, what works) and the revops hat (clean fields, clean enrichments, clean attribution). Without those two, more activity equals more noise. * Owning Workflows End-To-End Is The Leverage Unlock: Every team member can now own a workflow from idea to live. Paid SEO goes from idea to keyword research to blog post with assets and published in an hour. The SDR manager goes from prospect list to email copy to launched campaign in the same hour. AI compresses the wait between specialists. The right framing is force multiplier per role, not headcount replacement. Anthropic and OpenAI are hiring engineers AND account executives at the same time they ship tools that supposedly replace both. Five strong people doing the work of fifteen, not one star doing the work of ten — because that one star carries unrepeatable key-man risk. * Warm Outbound Is Signal Triangulation, Not Message Volume: The doubling of Airbyte’s pipeline growth rate did not come from blasting cold sequences. Two specific plays. First, events: dump the post-event lead list into Common Room, rank by who has signed up for the product or used the open source repo, and let SDRs only call the warm subset. Second, PLG signups: when an engineer signs up, outreach to them, AND prospect for decision-makers in the same org, AND warm those decision-makers with ads BEFORE the SDR call. The Twilio “Ask Your Developer” campaign at scale. Even when a motion has to be cold, the question is how to warm it up. ABM at Series B is now defensible if you know your audience. * Hire Barrels, Not Ammunition. Then Outsource The Deep Expertise: Mario hires generalists who can take a project end-to-end without a playbook over narrow specialists. The best SDR he ever hired was selling pest control door to door. Four traits to look for. Agency: just do the thing, do not tell me you will plan to do the thing. Curiosity: the playbooks that worked five years ago do not work now. Taste: AI brings the cost of writing copy and code to zero, and taste is what differentiates. Chip on the shoulder: something to prove. Then complement the in-house team with agencies for deliverability, paid media, and scaled outbound, so the team focuses on managing agents and workflows rather than becoming a CPM expert. Enjoying this episode so far? Subscribe for free to new posts. Top Quotes “Bad data equals bad signal equals bad results... When AI is in the mix, that’s a multiplier effect.” “For me, it’s really about drive over experience, agency over experience. I don’t care if you’ve never done this job. The best SDRs I hired was a person that was selling pest control products like door to door.” “AI brings the cost of writing copy, writing code, and everything to zero. What is going to differentiate is your taste and deep understanding of who you’re selling to.” “The biggest thing you should stop doing is just doom scrolling social media and sending your team everything that other people are doing... Just start listening to what your customers are saying.” Referenced Tools and Resources * Data infrastructure: Airbyte [https://airbyte.com/], Salesforce, Supabase * Signal hub: Common Room [https://www.commonroom.io/] * Outbound orchestration and messaging: Octave [https://www.octavehq.com/], Clay [https://www.clay.com/], Instantly [https://instantly.ai/], Outreach [https://www.outreach.io/] * Audience sync and ads: Vector * Sales intelligence: Gong * AI assistants and dev: Claude Code [https://www.anthropic.com/], Claude, Cursor, ChatGPT, Lovable * Documentation and written culture: GitBook, GitHub * Frameworks and references: Barrels vs Ammunition (Keith Rabois, Founders Fund and Vinod Khosla), Twilio “Ask Your Developer” campaign Timestamps * (05:11) Welcome to S2E5 — Matteo’s intro on data infrastructure, Mario’s bio, the warm-outbound motion that doubled pipeline at Airbyte * (08:18) Investor to operator return — every company is a go-to-market company when software costs go to zero * (09:55) Workflow ownership end-to-end — paid SEO, SDR manager going idea to live in an hour, technology no longer the blocker * (11:28) Dev tools historical context — Auth0, Pusher, segment plus APIs, GTM engineering not new for dev tools * (13:33) Step change vs oversold — PMM and revops as the two foundations, AI as multiplier of garbage too * (16:50) The brand and product marketing comeback in the AI slop era * (17:48) Force multiplier vs headcount replacement — Anthropic and OpenAI hiring engineers AND AEs, key-man risk * (19:30) Markdown files in a GitHub repo vs notebooks on laptops — knowledge that survives the people * (23:14) Build vs buy and stitching — Vercel and Ramp can build, most teams should stitch via MCP * (25:00) MCP server unlock — making any tool talk to any tool, free from vendor integration roadmaps * (28:02) Mario’s overnight cron job that cleans his daily notes plus a CLAUDE.md file knowing his priorities * (28:43) Stack walkthrough — Common Room, Octave, Clay, Instantly, Vector, Gong, Outreach * (32:32) Warm outbound play one — events leads ranked through Common Room before any SDR call * (33:30) Warm outbound play two — PLG signups plus decision-maker prospecting plus warming via ads (Twilio at scale) * (35:33) ABM at Series B is now defensible if you know your audience * (36:41) Barrels vs ammunition (Keith Rabois) — drive over experience, the door-to-door pest-control SDR * (41:57) Outsourcing the deep expertise — deliverability agency, paid media agency, the team focuses on agents and workflows * (47:18) Four traits for great GTM engineers — agency, curiosity, taste, chip on the shoulder * (49:33) Stop doom scrolling, start listening — the Gong digest workflow as the one habit to start Where to Find Mario * LinkedIn [https://www.linkedin.com/in/mmoscatiello] * Airbyte [https://airbyte.com/] Where to Connect with Jared & Matteo * Matteo Tittarelli, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/matteo-titta/], X [https://x.com/matteo_titta], Website [https://genesysgrowth.com/], Newsletter [https://newsletter.genesysgrowth.com/] * Jared Waxman, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/jwaxman/] Thanks for reading GTM Engineer School! Subscribe for free to receive new posts and support my work. 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 [https://gtmengineerschool.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

"Earning the Right to Automate" | Eoin Clancy

About our guest — Eoin Clancy Eoin Clancy is the VP of Growth at AirOps, the AI search and content engineering platform powering content workflows at companies like Webflow, Ramp, and Notion. He came up through the same GTM engineering path our audience is on — six years at Telnyx going from growth engineer to head of growth, then founded Build AI First in late 2023. At AirOps, Eoin scaled the company from $2M to $15M ARR in 11 months and runs the AirOps content engineering cohort that's become one of the most concrete training programs in AI search. Core takeaways Polarization Is Accelerating, Not Closing: The spectrum between top operators and the median has never been wider. Laggards are still figuring out Zapier; the top 10% are spending days in Claude Code and shipping at a different rate. AI doesn't replace people — it replaces the ones who don't use it well. Eoin's call to action: if you're actively learning today, you're already in the top 10%, and the only job is to stay there. Information Gain Is The Whole Game In AI Search: Search engines and the LLMs powering them reward unique context that isn't in the training data. Where that context lives — in your customer calls, support tickets, internal Slack threads, expert heads — is now reachable through MCPs and agents. The competitive moat is the proprietary substrate, not the publishing pipeline. Cosine similarity is your enemy: undifferentiated content reads as gray, replicated, and the algorithm penalizes it. AI/Human Collaboration Is A Modulator, Not A Switch: The "either let the AI do everything or do it all yourself" frame is broken. The right question per workflow: which steps reduce human involvement (legal review codified into an agent over time), which steps increase it (subject-matter-expert capture from your engineers and salespeople), and what's the hybrid that gets to 10 out of 10 quality. The pure ends get to 6 or 7. Earn The Right To Automate: High-velocity experimentation comes before infrastructure. AirOps ran 5–10 manual webinars before codifying anything; Ramp ran years of trigger experiments before building internal sales tooling. Premature automation locks in process before learnings exist. Take 10 shots, learn from the misses, codify only what's repeatedly worked. Top quotes > "I'd much rather take 10 shots on goal, five of them hit. Two of them are failings that you learn more about your audience or the market on, and then you develop from there." > "If you actually don't know what works and what doesn't, you're, you haven't earned the right to go automate it yet." > "Internally, I'm known as the guy who drinks our own champagne. So drinking your own champagne is my preferred method." > "If you're actively learning today, you're probably in the top 10%. And that's just where you want to make sure that you stay." Referenced tools and resources AI assistants & dev: Claude Code [https://www.anthropic.com/], Claude, ChatGPT, Cursor AI search & content engineering: AirOps [https://www.airops.com/], Perplexity, Google AI Overviews, MCP GTM & ops infrastructure: Salesforce, Clay [https://www.clay.com/], Slack, Gong, Intercom Image generation: Nano Banana Analytics: GSC, GA4 Workflow automation: Zapier Timestamps (04:23) Welcome to S2E4 — the SEO to AEO shift, Eoin's path from growth engineer to VP Growth at AirOps (07:06) What's actually changed in GTM, content, and context engineering in the last year (09:53) The polarization of skills — top operators racing ahead, the median falling behind (12:00) AI won't replace people, it should empower them — Ross Simmons quote, anti-doom framing (13:49) Hype vs reality in AI-powered content — where information gain actually lives (17:25) Don't let your agent fan out a thousand pages — it does more harm than good (17:55) Cosine similarity and the gray middle — why undifferentiated content loses in AI search (20:18) Build vs buy plus bundling and unbundling cycles — the TV subscription analogy (22:30) Bundling is the next move — tool consolidation with MCP and Claude Code orchestration on top (24:33) The maintenance burden of vibe-coded apps — late-night pings and product-owner drift (25:30) Pick your battles — the nano banana lesson on waiting out the better tool (27:14) What Eoin's team optimizes for — high-velocity experimentation over single-bet projects (30:31) Switching to AI search — why no acronym (AEO, GEO, LLMO) has won yet (32:56) Top operator misconceptions — "AI content is bad" and "we have nothing unique to say" (35:00) The hybrid is the answer — modulating AI and human involvement per workflow step (41:07) What you can do this week — sales calls plus GSC plus Slack into Claude or ChatGPT (46:49) Where content engineering sits at AirOps vs Webflow vs Ramp — and why it sits under growth (48:42) True north metric for AI search — mention and citation rate, branded search as correlation (50:34) Drinking your own champagne — AirOps runs its full GTM motion through AirOps (52:13) Hiring the next GTM engineer — sit between sales and marketing, build infra plus boost team efficiency (56:55) Closing — the gap is widening, keep the human in the loop, where to find Eoin Where to Find Eoin LinkedIn [https://www.linkedin.com/in/eoinclancy/] AirOps [https://www.airops.com/] Where to Connect with Jared & Matteo Jared Waxman, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/jwaxman/] Matteo Tittarelli, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/matteo-titta/], X [https://x.com/matteo_titta], Website [https://genesysgrowth.com/], Newsletter [https://newsletter.genesysgrowth.com/] 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 [https://gtmengineerschool.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

S2E3: "Building for Machines, Not Humans" | Kevin White

About our guest — Kevin White Kevin White is the head of marketing at Scrunch AI, where he's building visibility infrastructure for the post-LLM web — analytics and optimisation that show brands how they're being represented inside ChatGPT, Perplexity, Claude, and Google AI Overviews. Before Scrunch, Kevin spent a decade marketing for the companies that defined the modern operator stack — Common Room, Retool, and Segment — and has advised teams at Ashby and Deepnote. He's one of the most pragmatic operators in the AEO space, with a working hypothesis that "there are no experts in this market yet" and a habit of running controlled experiments instead of taking anyone's word for it. Core takeaways Bots Are Your New VIP Visitor: Retrieval bots from ChatGPT, Perplexity, Claude, and Gemini are now hitting sites at meaningful volume — on Scrunch's own site, bot traffic exceeds human visits. Each retrieval call has a real human with commercial intent behind it. The work for marketers and engineers is shifting toward making sites cheap to crawl in tokens (Markdown and JSON over heavy JavaScript), so retrieval bots get more useful information and your brand surfaces in more answers. Wave 1 GTM-E Was Enrichment. Wave 2 Is Bespoke Trigger Hunting: The first wave of go-to-market engineering consolidated firmographic enrichment for SDRs. That layer is mature. The alpha now lives one step upstream — in identifying the specific sequence of triggers that puts a buyer in commercial-intent mode (a product action, a competitive event, a regulatory shift) and building the workflow to catch it at scale. Tools like Cloud Code have collapsed the build cost from a 6-figure software contract to a $20/month subscription. Hire The Vibe Coder Over The Content Writer: Vibe-coded interactive tools — site graders, prompt generators, real-time domain audits — are now more compelling outbound offers than gated PDFs. The same build gets reused as outbound asset, programmatic SEO play, sales enablement surface, and self-serve qualification interface. Kevin would hire a vibe coder over a content writer 100 times out of 100. Elena Verna at Lovable just hired one full-time. The move is no longer fringe. Reddit Citations Are TOFU. Lower-Funnel Intent Lives In The Long Tail: Most "win at AEO" advice fixates on Reddit and Wikipedia. Kevin's data says those surfaces cover top-of-funnel referential prompts — "what is X" — not the comparison and evaluation prompts that drive commercial intent. The prompts you actually want to win for are answered by long-tail niche publications. Optimise where your buyer's lower-funnel question lives, not where the volume looks biggest on a leaderboard. Top quotes > "We have more bot traffic now than we have human visits to our site." > "If I had the choice between hiring a vibe coder to build really cool tools and someone on the content side of things who's going to write a bunch of like white papers, I'm definitely going to hire the vibe coding person 100 times out of 100." > "There's not really an expert in the space. I would say instead of listening to me or others, go out there, create controlled experiments, see if those experiments yield the right kind of results that you're looking for." > "As marketers, you would typically dismiss in the past — bot traffic, this is not going to give me any information on the user experience. But now, it's like, I want that bot traffic, because there's a person with intent behind that bot." Referenced tools and resources AI assistants & dev: Cloud Code [https://www.anthropic.com/], Cursor [https://cursor.sh/], Claude [https://www.anthropic.com/], ChatGPT GTM & enrichment: Common Room [https://www.commonroom.io/], Clay [https://www.clay.com/], Clearbit, Apollo, Outreach, Artisan, 11x AI search visibility: Scrunch AI [https://www.scrunchai.com/], Perplexity, Google AI Overviews Citation surfaces: Reddit, G2, Trustpilot, Wikipedia Web infra & CDN: Cloudflare, Akamai, Vercel [https://vercel.com/] Analytics: GA4, PostHog, Similar Web Timestamps (00:04) Welcome to S2E3 — Kevin's path from Segment to Retool to Common Room to Scrunch AI (03:00) What's actually changed in GTM engineering — Wave 1 enrichment vs. Wave 2 trigger reverse-engineering (04:55) Reverse-engineering signals back from buyer commercial intent (09:25) The biggest failure mode — list-building beats message-coaching, every time (12:00) SDRs as multipliers, not dispensable headcount (14:00) Stack the plays as patterns emerge — and don't stop hiring once it works (16:25) Where GTM engineering is winning — and the untapped industries with greenfield opportunity (18:15) Cloud Code as today's tool of choice — and why Kevin won't be loyal next quarter (20:40) Worked example: paid spend × declining organic = Scrunch ICP (23:05) Who maintains the sprawl of vibe-coded tools? Enter the AI architect (24:43) The vibe coder vs. content writer hiring decision — 100 out of 100 times (27:30) One vibe-coded tool, four surface areas — outbound, SEO, enablement, self-serve (30:30) AEO, GEO, AI search — and why Kevin stays acronym-agnostic (33:14) There are no AEO experts yet — run controlled experiments instead (36:00) Reddit and Wikipedia cover top-of-funnel. Long-tail niche pubs cover lower funnel. (39:00) Two Scrunch personas — marketing (CMO/SEO) and engineering (CTO/CIO) (42:30) Bots are now your VIP visitor — Scrunch's own traffic data (44:00) Three categories of bots: traditional search, training, and retrieval (44:48) The token economy of crawlability — Markdown and JSON over JavaScript (48:46) The mental shift from "filter bot traffic" to "want bot traffic" (53:12) Hire deep IC experts and let them stack AI on top — the new shape of marketing teams Where to Find Kevin LinkedIn [https://www.linkedin.com/in/kevbosaurus/] Scrunch AI [https://www.scrunchai.com/] Where to Connect with Jared & Matteo Jared Waxman, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/jwaxman/] Matteo Tittarelli, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/matteo-titta/], X [https://x.com/matteo_titta], Website [https://genesysgrowth.com/], Newsletter [https://newsletter.genesysgrowth.com/] 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 [https://gtmengineerschool.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

S2E2: "Context Is the Moat" | Zach Vidibor

About our guest — Zach Vidibor Zach Vidibor is the co-founder and CEO of Octave, the first context engine built specifically for GTM teams. Think of Octave as a GitHub for your go-to-market context — a structured home for your ICP, your value props, your competitive opinions, and every piece of institutional knowledge that should shape how AI and humans represent your company in market. Before founding Octave, Zach spent a decade as an operator inside companies that defined how modern GTM is done — LinkedIn, DocuSign, and Dropbox — seeing from the inside how strategy leaks and compresses by the time it reaches the frontline. Octave is his answer to that problem: a shared repo so every agent, workflow, and person on the team represents the company consistently. Core takeaways Context is the moat, AI is the commodity: Every team now has Claude, GPT, and Gemini. Using AI is table stakes. The alpha has to sit one layer up — in your first-party context: your codified ICP, your competitive opinions, the customers you know you don't serve and why. The lens you put between your company and the market is the defensible thing; the model behind it is not. Wave 1 was filling fields. Wave 2 is codifying opinions: The first year of GTM engineering was dominated by enrichment — "we can now look up 30 DevOps engineers and drop them into an email." Problem solved. The next wave is interpreting what 30 DevOps engineers mean for how you act on that account — and the best teams aren't optimizing yesterday's assembly line. They're 3D-printing new motions from scratch with context as the starting input. If you skip ICP, you will regret it: LLMs are sycophantic optimists. Without your opinions baked in as constraints, they iterate plausibly against any problem indefinitely — "GPT splits atoms until infinity." ICP isn't a static deliverable; it's a testable hypothesis the system grades itself against. Teams that skip this foundation end up producing AI-slop at scale. Retire the set-and-forget mindset: The market's resting heart rate has gone from 60 to 120 beats a minute. VPs who still expect high conviction before every decision will lose to the ones who shift on a dime. Ten new competitors arrive per quarter. Category-defining tools appear on one-month cycles. The mindset for 2026 isn't "decide once"; it's "decide fast, shift faster, keep your context repo clean enough that changing direction is cheap." Top quotes > "Using AI, that's not a differentiator, right? You have to put alpha on top." > "What about, instead of an assembly line, we 3D print this thing?" > "The resting heart rate of the market has gone from 60 to 120 beats a minute." > "Don't just expect the models to know what you know." Referenced tools and resources Context & Messaging: Octave [https://www.octave.ai/] (GitHub for your GTM context) Data & Prospecting: Clay [https://www.clay.com/], Salesforce, HubSpot AI & Agents: Claude [https://www.anthropic.com/], Claude Code, Claude Co-work, OpenAI [https://openai.com/] (GPT), Google Gemini Past operator context: LinkedIn, DocuSign, Dropbox (Zach's prior career) Timestamps (03:10) Welcome to season 2, and why the season shifts from hype to operating system (04:00) Meet Zach Vidibor — co-founder and CEO of Octave, the context engine for GTM teams (06:20) Why context is the lens between your company and your markets (08:00) How GTM engineering has evolved in the last year — Wave 1 to Wave 2 (09:50) Using AI isn't a differentiator — you have to put alpha on top (10:20) Why LLMs are sycophantic optimists and what that means for GTM work (13:10) Where GTM engineering is real vs. where it's oversold (18:30) The "3D print this thing" reframe — beyond assembly-line optimization (19:30) Claude Code hype and what it means for solo operators vs. the enterprise (22:10) The coordination problem Claude Code creates in scaled sales orgs (25:00) Cut vs. grow — why you need to pick the goal before deploying AI (26:00) "Slice the world into 50 subverticals" — what different goals actually look like (28:00) Defining context engineering, and why ownership is still TBD (30:00) Institutional knowledge: the "we don't sell to higher ed" problem (34:30) The infrastructure monitoring case study — developer outbound at scale (36:00) Brownfield vs. greenfield routing and persona-specific context (39:40) Why the goal is positive interactions, not just demos (41:00) Matteo on the PMM perspective — teams that skip ICP (42:30) "If you skip, you will regret" (43:30) How Octave structures its GTM team — forward-deployed engineers reporting to sales (47:00) Hiring bar for great GTM engineers — taste plus systems thinking (50:40) "Go-to-market is super quantum" (52:30) What VPs should stop doing immediately (53:40) The resting heart rate of the market — 60 to 120 beats a minute Where to Find Zach LinkedIn [https://www.linkedin.com/in/yashtekriwal/] Clay [https://www.clay.com/] Where to Connect with Jared & Matteo Jared Waxman, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/jwaxman/] Matteo Tittarelli, GTM Engineer School Co-founder: LinkedIn [https://www.linkedin.com/in/matteo-titta/], X [https://x.com/matteo_titta], Website [https://genesysgrowth.com/], Newsletter [https://newsletter.genesysgrowth.com/] This is a public episode. 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