Most VP of RevOps searches go wrong before anyone looks at a resume. The CRO decides they need one person who can manage every tool in the stack, architect the entire go-to-market engine, analyze the data, build AI solutions, and somehow drive revenue while responding to every Slack request that comes in. That person doesn't exist. And the searches that start with a hundred-item wish list almost always end in a hire that spends their time updating Salesforce fields that don't move the needle on anything.

In this episode, Eddie Reynolds and Rachael Bueckert break down how to actually approach this hire. The conversation covers the three distinct roles hiding inside the VP of RevOps job description, what a CRO needs to figure out before writing a single line of a job posting, the interview question Eddie uses to separate the tools people from the architects, how to keep a new hire focused on what matters instead of drowning in ad hoc requests, and why hiring fractional ops alongside a full-time VP often produces better results than either alone.

Resources Mentioned in This Episode:

GTM Ops Frameworks

01:30 - Why most VP of RevOps searches fail

02:13 - Three roles hiding in one job description

06:55 - The analytics role nobody has time for

08:33 - The AI unicorn problem

14:24 - What to figure out before writing the job posting

15:39 - The one question every CRO should answer first

16:25 - The interview question that separates architects from tool updaters

18:37 - Using benchmarks to find the biggest revenue opportunity

21:18 - Where AI fits in the hiring decision

23:49 - Keeping a new hire focused with a RevOps roadmap

26:45 - How random Slack requests derail strategic work

28:32 - The deal desk and commissions trap

38:01 - Qualifying by motion expertise, not tool expertise

48:57 - When fractional RevOps alongside a full-time VP makes sense

52:25 - How to staff the three RevOps roles

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Jeremy Von Halle joined Abridge when they had two sellers and less than $5 million in ARR. Now the company has over $200 million in revenue, a $5.3 billion valuation, and a 200-person commercial organization selling into a total market of just 300 large health systems. With only 300 potential enterprise accounts, every customer interaction has to be the best version of itself. So Jeremy built an AI-powered rev ops engine that preps sellers before every call, captures and routes insights from every conversation, completes RFPs in under an hour, monitors all 300 accounts for news every morning, and surfaces deal risks that managers would otherwise miss.

In this episode, Eddie Reynolds sits down with Jeremy Von Halle, VP of Revenue Operations and Chief of Staff to the Chief Commercial Officer at Abridge, for a deep dive into the specific AI tools, agents, and architecture behind their enterprise sales engine. The conversation covers the foundational data layer that makes any of it possible, their internal AI agent "Archie" that lives in Salesforce and Slack, how they use Attention and Tray to capture golden and rotten deal signals, why centralized AI builds beat reps vibe coding their own solutions, and the save time, save money, make money framework for proving ROI when your sales cycle is 18 months.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:23 - Intro to Jeremy Von Halle and Abridge

02:48 - Why AI in enterprise sales is about depth, not breadth

06:36 - 200-person commercial org selling into only 300 accounts

09:33 - Save time, save money, make money: the ROI arc

11:26 - When and how do you prove ROI with an 18-month sales cycle?

15:39 - The QA layer: flagging calls that don't meet the rubric

16:33 - Centralized AI build vs. reps vibe coding their own solutions

25:08 - How many iterations before you get it right?

28:19 - The foundational data layer that makes all of it work

30:59 - Capturing call transcripts and updating Salesforce with Attention

32:10 - Golden events and rotten events: sentiment signals from every interaction

36:55 - "Archie": the AI agent embedded in Salesforce and Slack

40:28 - Daily news monitoring across all 300 accounts

40:58 - RFP completion from days to under an hour

43:23 - AI-powered forecast prep for frontline managers

44:48 - Deal risk scoring from conversational and stage progression data

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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A meme went viral on LinkedIn: "Hey, this is Gigi from GG's Pizza calling. You ordered last week. We have a pepperoni pizza ready and can deliver in ten minutes. Are you hungry?" It's absurd. Nobody does outbound for pizza. But Eddie looked at it and realized Gigi is actually running better outbound than most B2B teams. She knows who bought before, what they ordered, that they're probably hungry right now, and she can deliver in ten minutes. Most SaaS companies can't say any of that about their own outbound motion.

In this episode, Eddie Reynolds and Rachael Bueckert use the pizza analogy to break down the six problems killing outbound right now: no shared definition of what outbound even means, targeting people with zero buying intent, confusing personalization with relevance, lack of segmentation that forces reps to context-switch across industries all day, ignoring CAC payback economics, and messy systems that make it impossible to figure out what's actually working.

Resources Mentioned in This Episode:

Outbound Efficiency Framework

GTM Ops Frameworks

The First 90 Program

01:00 - The pizza meme that explains everything wrong with outbound

03:20 - Problem 1: nobody agrees on what outbound actually means

09:21 - Problem 2: targeting people with zero buying intent

11:16 - The biggest fallacy in sales: trying to change hearts and minds

17:08 - What the pizza place gets right about intent that most B2B teams miss

27:31 - Problem 3: relevance vs. personalization (they're not the same thing)

28:40 - The pitch to Rachael that would have taken her money on the spot

33:46 - Problem 4: lack of segmentation and why reps can't context-switch

37:06 - How Gigi segments better than your SDR team

42:37 - What the whole thing looks like when every layer is dialed in

49:18 - Problem 5 and 6: messy systems and CAC payback economics

55:55 - Gigi's systems are cleaner than yours

57:24 - CAC payback: would Gigi even be profitable doing this?

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Britni Borrelli was brought into Mitratech, a $600 million PE-backed company built from roughly 24 acquisitions, to implement AI across the entire go-to-market organization. What she found was seven Salesforce instances, $5 million in overlapping software that nobody had quantified, legacy systems that leaders had emotional attachment to, and data scattered across so many tools that the chief product officer was told to just go listen to Gong calls if he wanted to know what customers were saying.

In this episode, Rachael Bueckert sits down with Britni Borrelli, VP of Global Sales Strategy and Chief of Staff to the President at Mitratech, for a conversation on how she assessed 24 acquisitions worth of tech debt before touching AI, why she started with data and relationships instead of tools, how she navigated the politics of replacing systems that leaders had built and still owned, the $5 million in software waste she uncovered from an Excel spreadsheet nobody had looked at, and why ripping the Band-Aid on consolidation beats trying to make everyone happy.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:23 - Intro to Britni Borrelli and Mitratech

01:12 - What "implement AI" actually meant when she walked in

02:10 - Buying software with AI in the name vs. actually implementing AI

03:12 - Starting with data: garbage in, garbage out

05:29 - Observing first: building relationships before changing anything

07:12 - Seven Salesforce instances and the consolidation decision

09:44 - Software that could replace 12 tools at once

11:43 - Managing pushback when you're overhauling everything

13:21 - The current tech stack and why contracts make consolidation slow

16:07 - Acquisition integration: what went wrong and the better process

21:32 - A decade at Tableau and how it changed her relationship with data

25:05 - Surfacing customer voice to product without Gong call listening

30:30 - How do you trust the data once AI is producing it?

35:38 - The 85% vs. 15% close rate problem

46:00 - The $5 million in software overlap nobody had quantified

48:15 - 25-30% more selling time from reducing admin

53:38 - What boards should be asking but aren't

01:08:34 - What a good AI ecosystem actually looks like

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Almost every revenue leader will tell you their number one priority is generating more pipeline. But if the pipeline you already have is leaking, more volume just means you lose more deals, only faster. Reps are chasing deals they will never win, sandbagging deals they could close, and pushing close dates quarter after quarter because nobody trusts what's in Salesforce. Meanwhile, the CRO is spending hours going rep by rep, deal by deal, just trying to get a read on the forecast.

In this episode, Eddie Reynolds and Rachael Bueckert walk through the updated v3.0 of USC's Pipeline Management Framework layer by layer. The conversation covers how to identify whether pipeline management or lead generation is actually the problem, the ICP qualification criteria most companies skip, how to define sales stages and exit criteria that make sandbagging and ghost pipeline impossible, the pipeline inspection process that turns one-on-ones from interrogation into coaching, and why AI is the last layer to add and what breaks when it's the first.

Resources Mentioned in This Episode:

The Pipeline Management Framework v3.0

GTM Ops Frameworks

The First 90 Program

01:09 - More pipeline won't fix a leaking funnel

04:21 - Telltale signs the problem is pipeline management, not lead gen

07:38 - The pyramid: why fundamentals, adoption, optimization, amplification in that order

09:03 - What sales methodology actually means and why most teams stop too early

15:42 - ICP for pipeline management: who should even be in your pipeline?

19:25 - The fuzzy data points that make or break qualification

25:24 - Sales stages, exit criteria, and when to walk away from a deal

32:49 - Adoption: how to get reps to actually follow the process

37:44 - Pipeline inspection that turns one-on-ones into coaching

41:23 - Optimization: using stage conversion data to coach rep by rep

44:02 - The Salesforce SDR handoff tweak that doubled conversion overnight

46:36 - The Go-to-Market Council

51:08 - Amplification: where AI fits and where it doesn't

56:01 - The fastest win: clean your pipeline in one day

This episode is a guest appearance by Eddie Reynolds, CEO of Union Square Consulting, on the Epic Events by vFairs podcast with Muhammad Younas. You can find the original episode on Spotify and Apple Podcasts.

Eddie breaks down how events fit into a GTM strategy and why most companies waste their event budget by skipping the foundational work. The conversation covers why ICP and buyer personas have to come before any event investment, how Eddie stacked an entire conference with pre-arranged meetings and generated millions in pipeline from small events, the step-by-step process most companies miss between the event itself and actual revenue, why intimate dinners where customers sell to your prospects are more effective than booths with badge scanners, and how to evaluate whether your event spend is outperforming what you could get from another channel.

Resources Mentioned in This Episode:

GTM Ops Frameworks

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Salesforce co-founder Parker Harris stood on stage and asked the same question every sales rep has been thinking for 20 years: why should you ever have to log into Salesforce again? Then Salesforce went headless, opening up the MCP so that AI tools like Claude and ChatGPT can read from and write to Salesforce directly. Eddie has been telling customers to force their reps to update Salesforce while simultaneously having his own executive assistant do 99% of his updates for years. That contradiction is about to go away.

In this episode, Eddie Reynolds sits down with Gerry Marletta, SVP of Delivery at Union Square Consulting, for a conversation on what Salesforce Headless 360 actually means for go-to-market teams, why your Salesforce doesn't need to be clean for AI to start delivering value, the difference between reading data and writing data and where the guardrails need to be, why they built their own analytics tool on SOQL queries instead of trusting the MCP for hard numbers, and how six months of CRM cleanup can shrink to six weeks when AI does the heavy lifting.

Resources Mentioned in This Episode:

GTM Ops Frameworks

01:13 - Do we ever need to log into Salesforce again?

03:56 - Depends on who you are and what you do

05:07 - No rep in history has ever wanted to update Salesforce

07:17 - The Wall Street team that refused to log in

09:19 - The 35-field mutiny that got everyone fired

12:03 - What is Salesforce Headless 360 and MCP?

16:45 - Does your Salesforce need to be clean for this to work?

22:00 - Reading data vs. writing data: where to take the training wheels off

25:07 - Automating call prep from calendar events

27:16 - Your data can live in 25 different sources now

31:56 - Updating opportunities from call recordings

39:09 - Why rigid tools kill creative selling

44:38 - The dinner party metaphor: stop cleaning rooms nobody visits

50:07 - SOQL queries vs. MCP: why hard numbers need zero interpretation

56:12 - Hallucination risk: where it's zero and where it's not

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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John Barrows has trained sales teams at Salesforce, LinkedIn, Google, and Amazon. He's watched every wave of outbound innovation since before predictable revenue was a playbook. And right now, he has a challenge for anyone claiming AI has tripled their results: show me the numbers. Because what he's seeing across hundreds of companies is that we're still in the efficiency phase of AI, not the results phase. Reps are sending faster, but they're not selling better. And 14 out of 20 reps who booked a call with him couldn't even tell him what he does for a living.

In this episode, Eddie Reynolds sits down with John Barrows, CEO and founder of JB Sales, for a candid conversation on what's actually working in outbound right now and what isn't. The conversation covers the "give a shit" factor that separates reps who get responses from reps who don't, why the SDR model was never really profitable and where it goes from here, how to run sales hackathons that get your whole GTM team building AI solutions together, why email might be about to become the most valuable outbound channel again, and the ICP and segmentation foundation that has to exist before any of it matters.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:23 - AI and outbound: separating signal from noise

03:56 - Still in the efficiency phase, not the results phase

06:51 - Why top-down AI adoption fails

10:04 - Turn your sales org into a sales hackathon

22:01 - The SDR model was never really profitable

27:12 - The "give a shit" factor and the Morgan story

32:16 - 14 out of 20 reps couldn't tell John what he does

33:43 - Why email is about to become the most valuable channel again

36:41 - The foundation: ICP, personas, and segmentation before AI

40:50 - Eddie's reps switched to templates and the meetings dried up

41:50 - Why hiring outside tech might be the answer

52:33 - Happiness, core values, and the unsexy path to winning

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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For ten years, the partner channel has been the single largest source of revenue for Union Square Consulting. Not marketing, not outbound, not referrals from happy customers. Partners. And for most of those ten years, Eddie was reaching out to the wrong ones. Thousands of conversations with partners who looked right on paper but never sent a single deal. It took years of trial and error to land on the three criteria that actually predict whether a partner will deliver. And if any one of those is missing, it's a waste of everyone's time.

In this episode, Eddie Reynolds and Rachael Bueckert break down how to define your ideal partner profile with the same rigor you'd put into your ICP. The conversation covers the three criteria that separate partners who send deals from partners who send pleasantries, how to think about partner benefit when there's no revenue share in the equation, why even internal partners at companies like Salesforce and Wells Fargo compete for mindshare the same way external ones do, and how to operationalize your IPP into a continuously improving system that actually drives revenue.

Resources Mentioned in This Episode:

GTM Ops Frameworks

01:25 - Why we don't talk about the partner channel enough

02:38 - The three criteria for an ideal partner

06:28 - Why direct benefit matters more than revenue share

09:24 - Wells Fargo: 186 lines of business, 35 business cards, zero mindshare

10:11 - Salesforce: internal partners competing for attention

11:31 - Why $500 in quota relief doesn't move the needle

14:37 - Where people go wrong defining their partner profile

21:21 - What enablement for partners actually looks like

22:14 - The La Bernardine dinner story

31:37 - AI for keeping your ideal partner profile current

37:15 - How to measure whether your partner program is worth it

45:24 - Turning the IPP into a continuous improvement system

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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Jeff Perry joined Carta in late 2018 when it was a 275-person startup selling cap tables to founders. Eight years later, it's a $650 million private markets platform with 50,000 companies on the platform, a fund administration business for venture and PE firms, a total compensation product, tax advisory, and a recently acquired law firm. The cap table business is still healthy, but it has a ceiling. Every dollar of growth beyond that core product came from building or buying entirely new revenue lines for entirely new types of customers.

In this episode, Rachael Bueckert sits down with Jeff Perry, CRO of Carta, for a conversation on how to keep growing when your core TAM runs out, the specialization mistake that taught them to simplify instead of overengineer, and how a $50K customer becomes a $1M customer over time through multi-product cross-sell.

Resources Mentioned in This Episode:

GTM Ops Frameworks

00:26 - Intro to Jeff Perry and the Carta growth story

01:13 - What Carta looked like at $20M and 275 people

05:06 - Why the cap table TAM ran out and what came next

07:39 - Build vs. buy: what's harder, new products or acquisitions?

09:50 - The Manhattan takeover and guerrilla marketing for PE firms

13:40 - How customer conversations drive the product roadmap

17:53 - One-call closes and two-year enterprise cycles in the same company

21:18 - The customer symposium where the CPO built features before dinner

23:28 - Enabling reps to sell across a widening product portfolio

32:50 - Territory and capacity planning across multiple business lines

34:55 - The separate sales team mistake and why they simplified

40:09 - Comp plan evolution: product-specific quotas vs. one quota

46:13 - Expansion: how a $50K customer becomes $1M

50:09 - Advice for CROs hitting a TAM ceiling

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GTM STRATEGY & AI ENGINEERING FOR B2B TECH

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