---
title: "AI-Native GTM: 3 Agent Plays and the Layer That Makes Them True"
episode: 98
podcast: "The LeanScale Podcast"
publisher: "LeanScale"
guest: "Jake Toepel"
guest_title: "Chief Technology Officer"
date_published: 2026-08-12
date_modified: 2026-09-02
duration: 00:07:24
word_count: 1265
topics: ["ai-in-gtm", "revenue-operations", "gtm-strategy", "forecasting"]
canonical_url: https://www.leanscale.team/knowledge/podcast/jake-toepel-ai-native-gtm-context-graph/
source: "LeanScale Knowledge Hub — https://www.leanscale.team/knowledge"
license: "Free to quote and cite with attribution to The LeanScale Podcast."
---

# AI-Native GTM: 3 Agent Plays and the Layer That Makes Them True — Full Transcript

> Episode 98 of The LeanScale Podcast, with Jake Toepel.
> Published August 12, 2026 · 00:07:24 · 1265 words.
> Machine-transcribed and **not diarized** — speaker attribution is inferred, so verify
> attribution against the audio before quoting a specific person.
> Structured breakdown: https://www.leanscale.team/knowledge/podcast/jake-toepel-ai-native-gtm-context-graph/

## 00:00 — The promise: three plays, then the part everyone skips

**[0:00]** Right now, there's a good chance your CEO or your board has told you they want an AI-native go-to-market.

**[0:07]** And there's an even better chance nobody's actually told you what that means.

**[0:11]** So I'm going to show you.

**[0:13]** In the next 10 minutes, you will watch one AI agent run three of the highest leverage plays in go-to-market.

**[0:19]** Your ICP, your messaging, and a live pipeline diagnostic in less time than it takes most teams to book the meeting.

**[0:27]** And then I'm going to show you the part that everybody skips because the second you try this on your own data, it all falls apart.

**[0:34]** And the one thing that fixes it is a concept called the context graph.

**[0:38]** It is the single most important part of AI-native GTM, and almost nobody is talking about it.

**[0:44]** And we'll walk through how we're leveraging VASCO to build this.

**[0:48]** So watch the use cases first, but stay to the end because that's where I break down the context graph, and that is the whole game.

**[0:55]** I'm Jake, the CTO here at LeanScale, and we build AI-native revenue operations for some of the fastest-growing companies in B2B SaaS.

**[1:03]** Not slide decks about AI, the actual working systems.

## 01:07 — What AI-native GTM actually means

**[1:07]** So let me define the thing that everyone is chasing.

**[1:10]** AI-native GTM just means this, agents running the work that used to be non-humanly possible.

**[1:16]** The analysis nobody had time for, the answer that used to take your data team three sprints, running on-demand in plain English.

**[1:25]** That is it. So let me stop describing it and just show you.

**[1:29]** Three use cases. Here's the first.

## 01:31 — Play 1 — Who is actually your best customer?

**[1:31]** Use case one. Who is actually your best customer?

**[1:35]** Now, every company has an ICP slide.

**[1:37]** It was written 18 months ago by somebody who does not work here anymore.

**[1:41]** So I'm going to ask my agent the uncomfortable version of that question.

**[1:45]** Let's look at every account we closed in the last four quarters, cross-reference deal size, sales cycle, and six-month retention.

**[1:52]** Tell me which segments actually win and which ones we keep selling to that we should not.

**[1:57]** Now, watch what it does here.

**[1:59]** It's going to build itself a checklist, pull the accounts, segments them, and notice it's not just summarizing, it's hunting for the pattern.

**[2:08]** And here's the answer.

## 02:09 — The answer: your real ICP isn't the logos on your website

**[2:09]** Our real ICP is not the enterprise logos on the website.

**[2:13]** It is mid-market with a strong technical champion closing in half the time at twice their attention.

**[2:19]** That is a board level strategy conversation that used to take a quarter.

**[2:23]** We just had it in 90 seconds.

## 02:25 — Play 2 — Is your messaging actually landing?

**[2:25]** Use case number two. Is our messaging actually landing?

**[2:29]** Marketing has positioning. The market has opinions.

**[2:32]** Those are usually not the same document.

**[2:35]** So I will hand the agent our last 20 sales calls and our current messaging and ask,

**[2:40]** what are prospects actually responding to?

**[2:43]** What falls flat and where are we just saying it wrong?

## 02:47 — Keep this line, kill that one — with receipts

**[2:47]** And it comes back with receipts, real quotes from real calls, implementation in weeks, not months.

**[2:55]** Keep it. That line closes deals.

**[2:57]** One platform instead of five tools. Kill it.

**[3:01]** Prospects hear that as a jack of all trades, master of none.

**[3:04]** This is not a focus group you wait six weeks for.

**[3:07]** That is your real voice of customer on demand every single week if you want it.

## 03:12 — Play 3 — The live pipeline diagnostic

**[3:12]** Use case three. And this is the one that changes how you run the business, the live diagnostic.

**[3:18]** Now, picture your Monday forecast call.

**[3:22]** Pipeline is soft and nobody knows why.

**[3:24]** Now, normally that question, why is pipeline down?

**[3:28]** Goes to the data team and you get an answer three weeks later when half the quarter is already gone.

**[3:33]** Let's watch what happens when the answer is live.

**[3:35]** Pipeline is down quarter over quarter. Why is it concentrated in one region?

**[3:42]** OK, which channel? Outbound specifically, well, why outbound?

**[3:51]** Connect rates fell off a cliff six weeks ago, right when two reps ramped down.

## 03:57 — Five whys of root cause before the call ends

**[3:57]** Five wise, a root cause in the meeting, the thing that used to take three sprints and a dashboard request

**[4:04]** just happened before the call ended, and that is the real unlock speed.

**[4:09]** Speed is the new moat and go to market constant recalibration instead of finding out you were wrong a quarter too late.

## 04:16 — Now try it on your own CRM (it breaks)

**[4:16]** OK, if you have a Claude or a chat GPT license, you're probably thinking, just go do all this right now.

**[4:22]** So let me save you three months of headache.

**[4:25]** Watch what happens when you point raw A.I. at your real CRM and ask one simple question.

**[4:30]** What is my pipeline coverage ratio?

**[4:33]** Wow, it gave us a number instantly, confidently, and it's wrong.

**[4:38]** Here's why. And this is the entire reason A.I. native is harder than the demo makes it look.

## 04:43 — The four things missing: definitions, identity, plan, memory

**[4:43]** Four things are missing.

**[4:45]** Number one, your shared definitions.

**[4:47]** You have an expansion pipeline and a new business pipeline.

**[4:50]** The A.I. doesn't know that, so it's blending them and it measures them against nothing because it doesn't have your plan.

**[4:56]** Two is identity resolution.

**[4:59]** Your billing system says this account churned. Salesforce says it is wide open.

**[5:04]** Is Acme Inc, Acme Co, Acme 123 the same company?

**[5:08]** The A.I. has no idea.

**[5:10]** Three is your plan.

**[5:12]** The targets, the quota and the actual number you measure against.

**[5:16]** And four, memory.

**[5:19]** What an ICP means for you?

**[5:21]** What happened last quarter?

**[5:23]** The context that makes the answers yours instead of just generic.

**[5:27]** Without those four, every answer is a confident guess and a confident guess is worse than no answer because you're going to put that in front of the board.

**[5:36]** So here is what we actually built.

**[5:38]** This is the thing I told you to stay for at the start of this video.

**[5:41]** And this is the part that makes everything you just saw trustworthy.

## 05:46 — The context graph: the semantic layer underneath

**[5:46]** Underneath the agent sits what we call the context graph, a semantic layer that maps your raw data to what it actually means in your business.

**[5:55]** Your definitions, your motions, your plan and resolves every record to a single source of truth across your CRM, your billing, your product.

**[6:04]** This is what your go to market actually looks like underneath.

**[6:08]** So when the agent answers now, it's not just guessing, it's reading off a model of your business that you have already agreed is correct.

**[6:17]** That is the difference between a demo that wows you and a system you would bet the quarter on.

## 06:23 — Why buying everyone a Claude license doesn't work

**[6:23]** It is also why just buying Claude licenses for the whole team doesn't work without this layer in the middle.

**[6:29]** Everyone invents their own definition of pipeline.

**[6:31]** Now you have 50 versions of the truth.

**[6:34]** You build the foundation once and then everybody gets the self-serve answers they were promised in the first place.

**[6:40]** So that is a native GM.

**[6:43]** It's not a chatbot bolted onto your CRM.

**[6:46]** It's agents running real plays on a foundation that makes the answers true.

## 06:51 — Where to start, and what's in the next video

**[6:51]** If you're feeling the pressure to figure this out and most of you are, the place to start is not buying more tools.

**[6:57]** It's an honest look at whether your data can even support this yet.

**[7:01]** That's the assessment that we run.

**[7:03]** Link is below.

**[7:04]** We will show you exactly where you stand and what it takes to get to what you just watched.

**[7:08]** In the next video, I'm going to show you how we run this across dozens of companies at once, the agency version and everything we have built on top of this layer.

**[7:18]** I'm Jake from LeanScale and I'll see you there.

**[7:21]** [MUSIC PLAYING]