GTM Vault

Context Is GTM Infrastructure, Not a Tool Connector | Alex Bilmes, Endgame

Someone gave every rep a Claude license. Every team built its own ChatGPT project. Now the same question gets two different answers depending on who you ask. One customer had a rep pitch a product line that did not exist because ChatGPT made up SKUs the company had never sold. The model was not the problem. The agent was not the problem. The architecture underneath was. Alex Bilmes built Endgame to fix that architecture. He has raised over $47M for Endgame, with customers including Braze, Scale AI, BetterUp, and Monte Carlo. Monte Carlo reached 80% AI adoption across its GTM team running on the platform. In GTM 46, Alex breaks down why revenue is the GTM function furthest behind on AI despite being the function that makes the money, why connecting Claude directly to a stack of MCP servers produces inconsistent answers at scale, and the new function that controls how every rep sells. He explains why agentic hellscape is the default state of most enterprises right now, why revenue per employee is the metric every CRO is laddering to, and why the best leaders are the ones spending nights and weekends building with AI on their own accounts. This is not a conversation about better AI tools. It is a conversation about the architecture that determines whether every tool you bought produces leverage or sprawl. Read the full write-up: https://www.gtmvault.co/p/gtm-46-context-is-gtm-infrastructure [https://www.gtmvault.co/p/gtm-46-context-is-gtm-infrastructure]

The Feedback Loop Is the Missing Layer in Performance Marketing | George Howes, Canva

The ad shipped. The creative looked great. The campaign went live. Performance stalled anyway. Not because targeting failed, not because the budget was wrong. The team scaled ad volume faster than its ability to learn. Most performance marketing failures are not media problems. They are feedback loop failures between creativity, data, and iteration. Most companies have not absorbed this yet. In this episode of GTM Vault, Rick Koleta sits down with George Howes, Head of Canva Grow and founder of Magicbrief (acquired by Canva), to break down why creative and media are not separate disciplines, why the feedback loop between them is the missing layer in modern GTM, and what changes when creative production runs on the same infrastructure as performance data. George founded Magicbrief, a creative intelligence platform that Canva acquired, after years inside top creative agencies watching the same failure repeat at every brand. Teams launched ads, collected results, moved on. Learning never compounded. He now leads Canva Grow, the product Canva is building to ingest ad performance from every platform, tie it back to the specific creative assets that produced the outcome, and push those learnings into the next round of creative before the next round is made. He explains why most performance marketing failures are feedback loop failures and not media failures, why creative teams and data teams sit at opposite ends of a broken handoff, why scaling ad volume faster than learning is the silent constraint at every growth stage, why AI is a multiplier for teams that already have the loop closed and a noise amplifier for teams that do not, why click-through rate lies more often than any other metric in the stack, why creative and media are the same system measured at different time scales, why small teams with all context in one place consistently outperform large teams with fragmented tooling, why one great static compounds into a video ad, a YouTube pre-roll, an email hero, and a paid social carousel when the loop is live, and why learning velocity is the new spend. This episode is for founders, CMOs, and performance leaders building in categories where ad volume is cheap, channels are saturated, and differentiation lives in how fast the team learns from what they ship. Performance marketing is not a media problem. It is a feedback loop problem. Structure match to GTM 44 exactly. Paragraph one is the setup with the short declarative cadence and the "Most companies have not absorbed this yet" closing beat. Paragraph two is the "In this episode of GTM Vault, Rick Koleta sits down with..." intro with a three-clause thesis statement. Paragraph three is the guest stats paragraph with the career arc that set up the product. Paragraph four is the long "He explains why..." list with nine structural threads from the conversation. Paragraph five is the who-it's-for paragraph ending on the short thesis reframe, matching the "The demo is not a sales artifact. It is the unit of the sale." pattern with "Performance marketing is not a media problem. It is a feedback loop problem." One note on guest stats. I do not have specific revenue or growth numbers for Magicbrief (pre-acquisition ARR, funding history, headcount, etc.) the way we had them for Supademo. If you want that paragraph to carry more empirical weight like the GTM 44 version did, send me any numbers you have and I will wire them in.

The Demo Layer Is Core GTM Infrastructure | Joseph Lee, Supademo

Most demo experiences are still screenshots in a slide deck or a 45 minute call where the prospect watches someone else click. Both are artifacts of an era where the sales motion carried the product. Neither survives in a market where buyers self-serve, shortlist in private, and decide before a human ever enters the loop. The demo stopped being a sales meeting. Most companies have not absorbed this yet. In this episode of GTM Vault, Rick Koleta sits down with Joseph Lee, founder of Supademo, to break down why the demo layer is becoming core GTM infrastructure, why most product-led companies lose conversion at the exact moment they should be proving value, and what changes when the demo stops being a one-time artifact and becomes a composable asset that runs across every stage of the funnel. Joseph built Freshline to $3M in revenue and made Forbes 30 under 30 at 22. Then COVID wiped out 90% of the revenue overnight. The insight from that collapse became the foundation for Supademo. 150,000 professionals across 100 countries. 2,000 paying customers. G2's number five fastest growing product. 8x growth in 2024. 3x in 2025. Profitable. He explains why market readiness is an architectural property of the business and not a creative choice, why the $1M ARR motion was almost entirely things that do not scale (programmatic SEO at every funnel layer, SEO-ranked product demos of competitor tools, white-glove responses on Reddit and changelogs), why defensibility lives in three places that code cannot compress (team adaptability, distribution as a flywheel, brand eminence), why capital efficiency is an optionality decision and not a virtue signal, why PMF has a short shelf life and why he runs his own version of the Cursor all-hands, why change management is the invisible cost of every software purchase, and why taste is the new moat. This episode is for founders and operators building in product-led categories where anyone can ship software in a weekend and differentiation lives in how the product gets distributed, adopted, and embedded into the way a company does business. The demo is not a sales artifact. It is the unit of the sale.

The Semantic Layer Is the Missing GTM Architecture with Danylo Borodchuk (Lopus AI)

Most analytics fail before the first query runs. Not because the data is bad. Because the definitions underneath it never agreed. The CRM says one thing. Billing says another. Product analytics says a third. Every dashboard built on top inherits the divergence. The founder picks the number that matches their intuition and calls it a decision. In this episode of GTM Vault, Rick Koleta sits down with Danylo Borodchuk, founder of Lopus AI and Y Combinator W25, to break down why 12 tools produce 12 definitions of customer and zero agreement on what revenue means, and what a governed semantic layer changes about every metric downstream. Danylo dropped out of Dartmouth with a CS background, DALI Lab, and DARPA research. Before Lopus was an analytics platform, it was a generative UI tool that got Twitter hype and zero traction. YC forced the question that killed the first idea: who actually wants this? Nobody had an answer. The pivot tells you everything about where the real pain lives. He explains why every company's CRM is a mess in the same predictable ways, why marketing and sales will never agree on "qualified" without a governed definition layer, why the most dangerous analytics tool is the one that always gives you an answer, how a self-healing definition layer regenerates its own SQL when underlying schemas change, why a 1,000-view blog post outperformed a 10,000-view one when you connect content to revenue instead of attention, and why the forward deployed data engineer model compounds at seed stage in the same way Palantir's did at enterprise scale. This episode is for founders and operators running a GTM stack where every tool defines the business differently and nobody has reconciled the definitions into a single governed layer. The fix is not a better dashboard. It is the architectural layer between raw data and every query the business runs against it.

When Dashboards Divorce the P&L - GTM Metrics vs Financial Reality with Rowan Tonkin (Planful)

Most go-to-market teams track metrics that were never designed to produce financial truth. The CRM was built for sales activity, not financial outcomes. Every metric stacked on top of it, from pipeline coverage to weighted forecast, inherits that original misalignment. Marketing reports MQLs trending up. Sales reports meetings booked ahead of target. Finance reports revenue is flat. Four functions, four green dashboards, one missed quarter. In this episode of GTM Vault, Rick Koleta sits down with Rowan Tonkin, CMO at Planful, to break down why GTM metrics drift from financial reality as companies scale, and what the structural reconciliation between go-to-market and the P&L must look like. Rowan spent nearly a decade in presales and implementation at financial planning companies before becoming a CMO. He operates where finance, planning, and go-to-market are forced to reconcile inside the same system. He explains why finance builds shadow models when it loses trust in dashboards, why pipeline coverage is the most trusted and least reliable metric in B2B, why growth masks the unit economics that determine durability, why precision is not accuracy in forecasting, and why AI on a system already corrupted by incentives produces confident noise, not better signal. This episode is for founders and operators who feel the gap between what their dashboard says and what their P&L shows and want to understand why the fix is not better reporting but a three-layer metric architecture where operational, commercial, and financial metrics are formally defined and structurally connected. Build the reconciliation layer first. Everything else follows.