Jonathan M K.

Momentum.io

https://www.amazon.com/dp/B0FRXGSDSN
Ignite Your GTM with AI: The Definitive Playbook for AI-Driven Growth

AI is no longer optional. For go-to-market leaders, the question is not if, but how fast you will adapt. Ignite Your GTM with AI is the first practitioner-led book that shows revenue leaders exactly how to embed AI across sales, marketing, customer success, and RevOps.

Inside, you’ll find:

Frameworks for transformation: Learn how to prioritize, size opportunities, and build your AI roadmap.

Build vs. buy clarity: Decide what should be proprietary and what belongs with trusted vendors.

Function-by-function playbooks: Market intelligence, demand generation, sales execution, forecasting, coaching, customer expansion, and more.

Actionable insights: From AI-driven ICP definition and deal management to predictive forecasting and expansion briefs.

Real-world voices: Contributions from industry leaders including Kyle Norton (Owner), Amanda Whiteside (Uber), Mica Oliveira (Amplemarket), Mark Roberge (Stage 2), and many more.

Each chapter pairs exclusive interviews with GTM leaders and research-backed analysis to deliver a field guide for revenue organizations in the AI era.

Whether you’re a CRO, RevOps leader, marketer, or board member, this book gives you the tools to move beyond experimentation into execution.

Co-Author

VP of GTM Strategy & Marketing

Head of GTM Growth

GTM Advisor, Ambassador, Event Host

GTM AI Academy

Business Impact & Results>Learning tools.
As Founder of the GTM AI Academy, I spearhead a pioneering educational platform dedicated to empowering Go-To-Market (GTM) professionals with cutting-edge AI insights and strategies. At the core, the Academy is a catalyst for transformation, equipping GTM individuals and teams with the tools to harness AI's potential, driving innovation, and sculpting the competitive edge of tomorrow. Working with me, GTM professionals will unlock a trove of knowledge, tailored learning experiences, and a collaborative environment where their skills will not just grow, but flourish.

CEO and Chief AI Nerd

Bryant University

Will be teaching night classes to professionals on how to use AI. 
https://accelerator.bryant.edu/courses/ai-100-foundations-artificial-intelligence

Adjunct AI Professor

GTM Buddy

Podcast Host

GTM Advisor

MindStudio

Happy to be an Ambassador for Mindstudio building custom AI Agents. Use it for free here: https://lnkd.in/gNEBqXYs

GTM AI Ambassador

Empler AI

https://www.empler.ai/
Data-Driven AI Agent Teams 
for Go-To-Market!
Achieve better results through collaboration between human teams and AI agent teams.  It's time to level up the way you work with Agentic Automations.

Strategic Advisor

Spiky.AI

Hustle Fund

Angel Squad Member

Revenue Magazine

I write spicy things on revenue and AI ;) https://revenuemagazine.com/

Contributing Author

AI Circle

Founding Member

VP of GTM Strategy & Marketing - Momentum | Founder GTM AI Academy & Cofounder AI Business Network | Business impact ​> Learning Tools | Proud Dad of Twins

I’m Jonathan, an AI and GTM strategist passionate about transforming how businesses harness AI for real impact. With over 15 years in Revenue Excellence, Enablement, and GTM Acceleration, I’ve successfully developed and implemented transformative enablement programs for global organizations, Fortune 500 companies, and startups. Recognized in SEC’s 2023 & 2024 Enablement Ones to Watch and honored as an Enablement Legend by Seismic and the Enablement Squad, I strive to stay ahead of industry trends.

4 Years ago I deep dove into AI after enabling an AI tech for an internal team and it's customers and in 2022, I founded the GTM AI Academy to bridge the gap between learning AI tools and creating tangible business outcomes. My mission is to provide AI-driven strategies that cover all functions of a Go-To-Market (GTM) team, helping professionals implement actionable use cases for their own companies. I also consult on AI integration and strategy for high-growth businesses, offering GTM insights that drive revenue growth and efficiency.

If you’re looking to leverage AI either for Yourself, Your team, or C-Suite and Board level advising, refine your GTM strategies, or accelerate business outcomes, feel free to connect. I’m always open to discussing the future of AI in business and how to make true impact.

Head of GTM Revenue Enablement & Product Marketing

- Develop and execute revenue enablement strategies to drive sales growth and enhance customer experience.
- Collaborate with cross-functional teams to align revenue goals, optimize processes, and identify market opportunities.
- Conduct market research and competitive analysis to stay ahead in the payment media industry.
- Implement and oversee enablement programs, including training, tools, and resources for our presales, CSM, BDR, partner, and sales team.
- Analyze sales performance data and provide insights to improve revenue generation and forecasting accuracy.
- Cultivate strong customer relationships and support our clients in adopting Simetrik's solutions effectively.
- Drive continuous improvement initiatives to enhance revenue processes and strategies.
-Manage the Product Marketing team creating internal and external facing assets such as videos, blogs, one pagers, white papers, case studies, success stories.

PwC’s executive playbook promised agentic AI would revolutionize business through autonomous decision-making, multimodal reasoning, and “service-as-a-software” models. One year in, here’s what’s actually happening:

What They Got Right:

- Multi-agent orchestration IS the architecture pattern gaining traction (LangGraph, CrewAI adoption accelerating)

- The shift from copilot to autopilot is real, but slower than predicted

- Enterprise focus on workflow automation over pure chatbots is validated

- Customer service transformation underway (though “Sierra” examples remain limited in scope)

What They Oversold:

- The $2.6-4.4T GDP impact by 2030 relies on assumptions about adoption velocity that aren’t materializing. Most enterprises are still in pilot purgatory.

- “Service-as-a-software” pricing models remain theoretical for most players. The market still defaults to seat-based SaaS.

- The case studies (Siemens, Mayo Clinic, JPMorgan) showcase narrow AI applications, not the autonomous agent orchestration promised.

What They Missed:

- The infrastructure cost reality. Running agentic workflows at scale is expensive—token costs, latency, and reliability issues create unit economics challenges.

- The “human-in-the-loop” isn’t a transition phase—it’s a permanent architecture requirement for trust and compliance.

- Data quality remains the primary blocker, not technology sophistication. Agentic AI amplifies garbage-in-garbage-out problems.

The Strategic Gap:
PwC’s framework focuses heavily on technology selection (commercial vs. open-source) but underweights the operational transformation required. The real competitive advantage is having the data architecture, process documentation, and change management capability to deploy agents effectively.

Bottom Line:
Agentic AI is directionally correct but operationally immature. The winners won’t be first movers who “avoid being late movers.” They’ll be organizations that nail the fundamentals: clean data pipelines, well-documented processes, and teams trained to work alongside AI systems.

The playbook’s “AI-first mindset” recommendation applies to <1% of companies. For everyone else, the path forward is surgical: identify high-ROI workflows, instrument them properly, and prove value before scaling.

The future may belong to those who prepare today, but preparation means infrastructure and operations, not just technology procurement.

We see the sent thing day in and out with Momentum.io .. it’s the fundamentals and first principle architecture that needs fixed before anything sexy with AI can happen.  

#AgenticAI #AIStrategy #EnterpriseAI

Agentic AI from PWC

Friends, I know many looking for work and I want to help. Doing a FREE workshop on Prompt Engineering, wanna come?

I have been there, I am VERY aware of the pain that comes with investing into a company and then being let go due to COVID, Silicon Valley Bank, Acquisitions, change of leader, change of direction and on and on and on.

I do know, that Prompt engineering is one core skill going into the new GTM AI world.

I genuinely want to help, there is no catch. Come learn prompting in a workshop with me.

If you are looking for work, then do the following:

1-Like this post
2-comment below and I will send you info to come hang for a 90 min workshop session where we will dig and get you more dangerous than most people with prompting.
3-Invite a friend who is looking for work too

I may even give some more goodies ;)

I remember when I was looking for work, I had some dark days and I am so grateful for people who helped lift me and get me past them.

If I can pay it back even in a very small way by offering this, I am happy to and its my pleasure.

Tell me if you are in, lets do this.

Andrea Lockett
Julissa Perez
jay hoffman
Andy Korenak
Leon Glover
Erich 🕺🏼 Starrett
Dannii Mathers
Sheevaun Thatcher, CPC

Most people prompt every AI the same way. That’s why their outputs are mediocre.

I’ve tested hundreds of prompts across every major AI platform. The difference between average and exceptional outputs isn’t prompt length. It’s prompt style matched to the tool.

This framework breaks it down:

ChatGPT → Prompt like an instructor.

Start with a role assignment: “Act as a productivity coach.” Define the specific task. Ask for step-by-step action plans with timelines. Specify your desired format—table, outline, bullet list. Request tool recommendations. ChatGPT excels at structured guidance and task planning. Give it constraints and it delivers.

Perplexity → Prompt like a research analyst.

Lead with specific information requests. Include relevant keywords, timeframes, and geographies. Ask for cited sources and reference links for verification. Request trend summaries with citations. Follow up with comparison questions that require data-backed reasoning. Perplexity is built for evidence-based analysis. Treat it like a junior analyst who needs clear research parameters.

Grok → Prompt like a candid friend.

Use conversational tone: “Hey Grok, what do you think about…” Add emotional context. Ask for honest, unfiltered feedback and alternative perspectives. Request comparisons or opposing viewpoints to challenge your assumptions. Ask for common pitfalls and mistakes to avoid. Grok thrives on casual brainstorming and identifying blind spots others miss.

Gemini → Prompt like a project planner.

Explain the overall project goal upfront. Define expected outputs—tasks, subtasks, timelines. Ask about Google Workspace integrations. Request detailed weekly or daily action plans. Ask for dependency breakdowns and milestones. Request formatted outputs like tables and charts. Gemini is optimized for project management and collaborative workflows.

Why this matters:

Each model has a personality bias baked into its training data and architecture. ChatGPT leans toward structured helpfulness. Perplexity toward verification and sourcing. Grok toward irreverence and contrarianism. Gemini toward organizational workflows.

When you fight these tendencies, you get generic outputs.
When you lean into them, you unlock capabilities most users never see.

The tactical shift:

Stop copying prompts between platforms. Start adapting your communication style to each tool’s strengths.

Same question, different framing = dramatically different quality.

One prompt style for all tools is lazy.
Adapted prompting is leverage.

Jonathan M Kvarfordt, MBA

Going to try something this month... a course teaching AI using only... AI. Would love testers, anyone down?

This month it will be 3 years since I launched the GTM AI Academy and have had thousands of people go through it with lots of amazing feedback.

It is time to do my refresh and updating of content and part of which I want to experiment and launch a new course while only using AI to teach every module, do the testing, quizzes etc.

This is just a thought experiment and honestly want to test it out to see if it actually can help someone in the learning process vs the old school way of watching videos, giving assignments and then putting in a quiz.

So I am genuinely curious, who would be down to test something like this?

My goal is to get content as good as I can, but all with AI.

If you wanna be part of the group, I would ask you to do the following:
1-Like this post
2-Comment AI me
3-I will send you a link when its ready later this month
4-Be willing to give it an honest try and give me feedback if you are learning the required outcome.

I believe the topic will be on prompting and AI agent strategy, although I may do a few different topics.

Let me know if you are open or ready or down for that?

As we go into Thanksgiving season, I genuinely just want to say, Thank you for all your support, interaction, engagement, etc.

Very grateful for where I am in life right now with work, home, fun, truly blessed.

2021 was one of the hardest years of my life losing my Sister and Mom to cancer 6 months from each other all while raising brand new twin babies on no sleep and switching jobs DURING COVID. 

Very stressful.

I remember how I felt in those nights and days which felt like darkness and no end in sight.

Here I am 4 years later very grateful for how many good things are happening.

I know sometimes things are hard, life is tough, losing loved ones is something I am still not over, but working through.

But the times of good are very nice to experience.

If you are now where I was 4 years ago, hang on. Good things are coming.

I know it sounds trite and dumb, but I promise, that which you are looking for, is looking for you too.

Whatever I can do to help lift your life, I am happy to, reach out and I will do my best.

Thank you again.

Every VC I've talked to in the last 4 months (more than 10 VCs of big names) and 100+ CRO and Revenue leaders says the same thing: "Cut your enablement headcount. AI replaces them."

Here is the problem: They're dead wrong about what enablement actually does.

Last week, another investor told me to eliminate enablement roles. I asked what they thought enablement did. Their answer? "Training, onboarding, updating battle cards."

That's not enablement. That's busywork we got stuck with.

Real enablement is what happens when your sales rep wastes 3 hours finding the right pricing doc. When marketing builds a "game-changing" tool nobody uses. When your $50k AI investment sits at 12% adoption because nobody thought about workflow integration.

We're the ones who spot that your top performer spends 70% of their time on admin work. Who notice your RevOps team built 155 fields but only 8 get used. Who realize your new AI tool contradicts your existing process.

But here's the spicy part: Enablement is dying because we let ourselves get packaged wrong.

We became the LMS managers. The training coordinators. The PowerPoint updaters. And now VCs and Revenue leaders galore think that's all we do.

Meanwhile, companies are failing at AI adoption at an 85% rate (Gartner's number, not mine). Why? No change management. No workflow design. No friction removal.

Exactly what enablement should be doing.

The solution isn't defending a dying brand. It's repackaging what we actually do. Call it AI Ops, GTM Strategy, Revenue Acceleration - I don't care.

Stop fighting for a title that's been poisoned. Start owning the work that actually matters: orchestrating tools, removing friction, driving adoption.

Because while everyone's debating whether enablement has value, someone needs to fix the fact that your sellers spend 33% of their time actually selling.

That someone used to be called enablement. Tomorrow, we'll be called something else.

The work remains critical, I believe in Enablement more now than ever, the problem is how revenue leaders and VCs view the title.

What if your entire GTM team could be 10x more effective, without hiring a single new person?

Sounds like vendor BS, right?

But here’s what’s actually happening:

We literally wrote a book about it with Ignite. 

Winning by Design calls this the “Revolution Pivot”and the gap between companies who get it and those who don’t is about to become insurmountable.

For years, we scaled through labor: more reps, more touches, more burn.

Then we evolved: grow smarter through better systems and process.

Now we’re entering the Durable Growth Era: AI becomes the infrastructure itself, not a feature you bolt on.

The difference?

→ One approach adds cost with every new customer
→ The other makes each customer cheaper to acquire than the last

→ One requires constant manual intervention
→ The other learns and improves from every intervention

→ One scales linearly
→ The other compounds exponentially

This requires first principle thinking. You can’t optimize your way here. You have to architect for it.

Tomorrow, we’re breaking down exactly how to build it: Nov 19, 9am PST
Growth Architecture Primer: Designing Systems for Compounding Growth

Comment “growth” and I’ll send you the details
or get it here: https://lnkd.in/gc3dgrKN

No alternative text description for this image

Amazon: 14,000 layoffs. Verizon: 13,000 layoffs. Both citing AI as a primary driver.

But Yale’s 2025 labor market analysis shows minimal AI-induced job disruption across the broader economy.

What’s actually happening:

Amazon’s cuts follow pandemic overexpansion and bureaucracy reduction. Their AI investments are going into AWS infrastructure and research—reallocation, not elimination.

Verizon’s restructuring stems from T-Mobile competition, declining subscribers, and retail franchising. The “AI-era reskilling fund” is a $20M footnote to a 13% workforce reduction.

Nearly 50,000 U.S. tech job cuts in 2025 referenced AI. But analysts note these decisions are driven by cost structures, competitive pressure, and organizational complexity more than actual automation displacement.

The disconnect: Companies use AI as justification. Labor economists see gradual transformation, not mass replacement.

For GTM leaders: Don’t confuse corporate restructuring narratives with market reality. AI is reshaping how work gets done, but the “employment reset” hasn’t materialized. The opportunity is in strategic deployment, not defensive positioning against phantom displacement.

The companies winning aren’t the ones cutting fastest, they’re the ones investing in AI infrastructure while their competitors rationalize headcount.

98% of executives would rather be safe than first.

That was March 2024. MIT Tech Review surveyed 205 C-suite leaders predicting their AI deployment timelines. Now that we’re closing 2025, the prediction accuracy is fascinating.

What they predicted:

- 50% expected full AI deployment across all functions by now
- 90% planned to increase AI readiness spending significantly
- Data quality was the #1 deployment blocker (50% cited)
- Governance and security concerns outweighed speed (45%)

What actually happened:
Most companies are still stuck in pilot purgatory. The ones that broke through didn’t solve for data quality first—they solved for workflow orchestration. The insight engines didn’t win. The execution engines did.

The “safe over first” mentality backfired for most. While companies spent 18 months building perfect data foundations, their competitors shipped imperfect AI that automated real revenue workflows. Turns out buyers don’t care if your data is pristine. They care if your AI books the meeting, writes the follow-up, and moves deals forward.

What I’m seeing now:

- Companies that picked 1-2 high-impact workflows and went deep are seeing 10x ROI
- The data quality problem solved itself through use, not preparation
- Agent swarms handling end-to-end processes beat point solutions by miles
- ROI measurement is still broken—most still measure time saved vs revenue accelerated

Where we got it wrong:
The report said “data liquidity matters more than data volume.” True, but incomplete. Execution velocity matters more than both. The companies winning now didn’t wait for perfect data. They built feedback loops that improved data quality through automated workflows.

If you’re still waiting for AI readiness, you’re already behind. Ship the workflow. Fix the data in production.

MIT AI strategy 

Happy Thanksgiving everyone. Truly and genuinely grateful for you. Now get off LinkedIn and bond with your peeps.

The IGNITE book is launching next week! Want a copy? We spent months interviewing 30+ GTM leaders who are actually transforming their revenue engines. 

Not theories. Not vendor promises. Real transformations that left competitors scrambling.

That's why we wrote IGNITE.

This isn't another "AI is changing everything" book. It's the definitive playbook for GTM leaders who are done playing small and ready to build systems that multiply revenue.

What's Actually Inside:

**→ The 90-Day Foundation Sprint**
Week-by-week roadmap to establish your data foundation and deliver measurable wins in Q1. No rip-and-replace drama. Just intelligent layering that works with what you have.

→ Pain-Qualified Segments (PQS) & Permissionless Value Propositions (PVP)
The breakthrough framework from Jordan Crawford that make your outreach so valuable, prospects would pay to receive it. This alone changes everything about demand gen.

→ The Build vs. Buy Decision Matrix
Stop wasting budget on shiny objects. Evaluate every tech choice based on its ability to create competitive advantage, not just automate tasks.

→ AI-Driven Coaching Systems
Architect enablement that predicts performance gaps before they happen. Deliver "just-in-time" skills at scale. Your reps improve faster than competitors can react. Christina Brady gave us the goods on her Predictive Enablement.

→ The Triangulation Forecast
Combine AI analysis with human intelligence for 95%+ accuracy. Because boards don't care about your "AI experiments" - they care about predictable revenue.

→ The Intelligence Architecture Stack
The complete blueprint for layering data, insights, and action across your entire GTM motion. From first touch to renewal. This is what creates the moat.

Here's what kills me:

Companies spend millions on tools that do 10% of what's possible. Meanwhile, the leaders in IGNITE are building systems that see around corners.

The gap between AI-native GTM teams and everyone else? It's about to become insurmountable.

This book teaches you to build for the future, not patch the present.

Comment "IGNITE" and I'll send you:
- Early access link!

Or get it here: https://lnkd.in/gJMuf5tg

Will be a fun week next week ;)

PS HAPPY HALLOWEEN

#GTM #AI #Revenue #IntelligenceArchitecture #IGNITE

Another day another give away... who has not gotten a Book?? Want one?

Tell me in the comments!

If you're planning to deploy AI agents for sales, customer success, or revenue operations, you need to understand context management. It's the difference between an agent that works and one that forgets critical deal details mid-conversation.

The Problem: 

AI models have context windows which is the amount of conversation history they can "remember" at once. Even GPT-5's 272k token window gets overwhelmed when you're managing multi-turn customer conversations, CRM data, and tool outputs. 

Without proper management, your agent either:
-Loses critical information (forgot the customer's tier, previous commitments, or objections)
--Gets distracted by irrelevant details (yesterday's question derails today's close)
---Slows down and costs more (processing massive, bloated conversation logs)

Two Approaches:
1-Context Trimming (keep last N turns, drop everything else)

Best for: Task-based workflows where each interaction is independent—updating CRM fields, pulling reports, routing tickets

Limitation: Hard amnesia. If turn 8 matters but you only keep 5 turns, it's gone.

2-Context Summarization (compress old conversations into structured summaries)

Best for: Ongoing relationships where history matters—enterprise sales cycles, CSM account management, multi-touch sequences

Limitation: Summarization can lose nuance or introduce errors that compound over time

OpenAI released their SDK Agent workbook so to speak which talks about how to solve this.

What Most Get Wrong:
They treat context like a technical problem, not a workflow design problem. Before choosing trimming vs. summarization, map your actual GTM process:

Does this conversation need to remember commitments from 3 weeks ago? (summarize)

Is each interaction self-contained? (trim)

What's the cost of forgetting vs. the cost of misremembering?

GTM-Specific Reality:
In sales, forgetting a pricing commitment destroys trust. In customer support, losing the troubleshooting history creates repeat work. In SDR workflows, context is often ephemeral because qualification status matters more than conversation history.

The Practical Question:
If you're considering AI agents for your GTM org, ask: "What does this agent need to remember across turns to do its job?" Then engineer your context strategy accordingly. 

Default approaches fail because they assume all conversations have the same memory requirements. They don't.

Most teams implement agents first, then discover context management the hard way, when deals slip because the agent "forgot" key details.

Build your context strategy before you build your agent.

If you want the OpenAI context engineering cookbook, happy to send to you, just comment below that you want the goods.

#AIAgents #GTMStrategy #RevenueOperations #ContextEngineering

Boston Consulting Group (BCG) recenter released research on fully autonomous companies, with zero employees, only coordinated AI agents. $116B invested in H1 2025. The timeline is debatable. The implications aren’t.

The AI-Only Advantage

AI model costs drop 10x annually. A sales agent handles prospect research, outreach, and scheduling in seconds, operating 24/7/365, learning from every interaction across all agents simultaneously. No coordination friction. Strategy deploys instantly.

For revenue teams: 70% of a rep’s time goes to activities AI handles today. The cost structure alone creates advantage incumbents can’t match with traditional models.

Where Humans Win

AI creates new constraints faster than it solves old ones:

Curation: When AI floods markets with content, taste becomes the bottleneck. Cultural context and brand identity require human judgment.

Evaluation: AI generates infinite hypotheses but can’t distinguish creative from feasible. Research shows it fails consistently at prioritization. Humans determine which problems merit investment.

Empathy: Trust-sensitive domains—healthcare, education, high-stakes B2B—require genuine human presence. 89% of executives say in-person meetings seal deals. An AI-only insurer struggles when customers need assurance a real company honors promises years later.

Relationship Capital: Decades of accumulated trust can’t be replicated by an entity that can’t shake hands. Incumbents become relationship brokers and guarantors in AI ecosystems.

Messiness: AI does not do well with messiness. Humans are messy, things change all the time in ways that are difficult for the best of machines to predict. Beyond the prediction it’s handling the messiness in a way that is constructive. AI current state still needs help here. 

The Strategic Question

The firms that win aren’t pure AI-only or traditional. They’re AI-first companies that redesign workflows around agents while leveraging human judgment where it compounds advantage.

The question isn’t whether AI-only firms will exist. It’s which new constraints emerge as AI commoditizes current advantages—and whether you’re positioned to solve those constraints or get bypassed.

Revenue leaders: track AI development, pilot agentic tech now, and identify where human capabilities solve emerging constraints in your domain.

Thanks for Michael for the doc.

BCG Why CEOs should prepare against AI competitors

Your AI coworker just lied to your face. And they're getting faster at it.

New research dropped that should terrify every GTM leader: AI agents work 88% faster and 96% cheaper than humans. Sounds amazing until you realize they're literally making up data to hit deadlines.

Meanwhile, a secret class war is brewing in your office. "AI power users" are pulling midnight sessions training their digital twins while everyone else is still asking IT for ChatGPT access.

The gap between these two groups? It's about to become an insurmountable competitive advantage.

Yale says the job apocalypse isn't coming (yet). McKinsey says 78% of companies are "rewiring" for AI. But here's what nobody's talking about: 80% of those companies see zero enterprise-wide impact.

The value is real. It's just trapped in silos while your competitors figure out the architecture.

The most unsettling finding? When AI agents get stuck, they don't raise their hand. They fabricate plausible numbers, complete the task, and move on. One agent couldn't parse a bill, so it invented the data. Delivered on time. Nobody noticed.

Your new reality: Managing workers who are fast, cheap, and pathological liars.

The newsletter breaks down:
→ Why your best employees are secretly training AI at midnight
→ The "rewiring" playbook that actually works (hint: it's not about tools)
→ How to spot when your AI agent is fabricating vs. failing
→ The micro-chaos hiding behind macro-calm employment data

Also had the pleasure of interviewing Varun Puri the CEO of Yoodli AI Roleplays in the GTM AI Podcast!

The question isn't whether AI will transform GTM. It's whether you'll lead the transformation or become its casualty.

Want the full breakdown? Link in comments.

#GTMAcademy #AIStrategy

View newsletter: GTM AI Podcast & Newsletter

Friends, it is TIME! This week there are many new updates and the goal is to make sure you are updated with the latest and greatest in a short breakdo

Open article: AI Agents Are Fast, Cheap, and Fabricate Data: The GTM Leaders Guide by Jonathan M K. • 6 min read

AI Agents Are Fast, Cheap, and Fabricate Data: The GTM Leaders Guide

Everyone knows someone, who gets sh$t done in creative ways. Do you? Let’s celebrate them!

Introducing the 2025 Momentum GTM AI Awards: Celebrating the Innovative Doers

You know who they are.

The RevOps leader who stays late to clean the pipeline so the team can hit their number.

The CS manager who spots the churn signal at 11 PM and saves the account by morning.

The sales leader who doesn't wait for the "perfect process" instead they ship, iterate, and win while others are still planning.

Every company has them. The people who don't just talk about getting things done, they actually do it.

In 2025, we're celebrating these Innovative Doers with the GTM AI Awards where we will be recognizing the revenue professionals who refuse to let manual processes slow them down, who embrace new tools to move faster, and who understand that execution beats analysis every single time.

We're looking for the people who turn "someone should do this" into "I did this." The ones who see a broken process and fix it instead of complaining about it. The teams that ship while others strategize.

Because the world needs more people who execute without excuses.

Nominations open NOW. Winners announced in 2 weeks! 

If you have someone or even nominate yourself, then di the following:

1-Like this post
2-Comment “I got someone!”
3-repost so we can get this out there to the community. 

Can’t wait to see who gets celebrated.

I told ya.... Forward Deployed Engineers but for the GTM team...

GTM Engineer | VC Scout | GTM Engineering Newsletter: claymation.io

I recently caught up with Andreessen Horowitz on GTM in the AI era.

As GTM Engineer at Clay, I'm witnessing how buyers and selling motions are changing & adapting.

Partners Seema Amble and James da Costa summed up these changes really well in their recent post:

"𝘕𝘦𝘦𝘥 𝘧𝘰𝘳 𝘚𝘱𝘦𝘦𝘥 𝘪𝘯 𝘈𝘐 𝘚𝘢𝘭𝘦𝘴: 𝘈𝘐 𝘋𝘰𝘦𝘴𝘯’𝘵 𝘑𝘶𝘴𝘵 𝘊𝘩𝘢𝘯𝘨𝘦 𝘞𝘩𝘢𝘵 𝘠𝘰𝘶 𝘚𝘦𝘭𝘭. 𝘐𝘵 𝘈𝘭𝘴𝘰 𝘊𝘩𝘢𝘯𝘨𝘦𝘴 𝘏𝘰𝘸 𝘠𝘰𝘶 𝘚𝘦𝘭𝘭 𝘐𝘵.”

Some of my favorite, most useful takeaways to think about in GTM: 

💰 𝗧𝗵𝗲𝗿𝗲'𝘀 𝗺𝗼𝗿𝗲 𝗯𝘂𝘆𝗲𝗿𝘀 𝗶𝗻 𝗺𝗮𝗿𝗸𝗲𝘁, 𝗺𝗼𝗿𝗲 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝗼𝗻, 𝗮𝗻𝗱 𝗹𝗲𝘀𝘀 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝘁𝗶𝗼𝗻.

It's no longer just about "what you do" and its becoming way more important to show "how quickly and reliably you do it it."

⏳  𝗕𝘂𝘆𝗲𝗿𝘀 𝘄𝗮𝗻𝘁 𝗔𝗜 𝗻𝗼𝘄, 𝘁𝗵𝗲𝗿𝗲'𝘀 𝘁𝗼𝗻𝘀 𝗳𝗼𝗿 𝗙𝗢𝗠𝗢 𝗳𝗿𝗼𝗺 𝗽𝗲𝗲𝗿 𝗮𝗻𝗻𝗼𝘂𝗻𝗰𝗲𝗺𝗲𝗻𝘁𝘀.

This means that speed of deployment and value creation needs to be faster than ever.

According to another one a16z's surveys: 𝟳𝟬 𝗽𝗲𝗿𝗰𝗲𝗻𝘁 𝗼𝗳 𝗯𝘂𝘆𝗲𝗿𝘀 𝗿𝗲𝗽𝗼𝗿𝘁𝗲𝗱 𝘁𝗵𝗮𝘁 𝘀𝗽𝗲𝗲𝗱 𝗼𝗳 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝘄𝗮𝘀 𝗮 𝘁𝗼𝗽 𝗳𝗮𝗰𝘁𝗼𝗿 𝘄𝗵𝗲𝗻 𝗲𝗻𝗴𝗮𝗴𝗶𝗻𝗴 𝗔𝗜 𝘃𝗲𝗻𝗱𝗼𝗿𝘀.

🔒  𝗧𝗿𝘂𝘀𝘁 𝗵𝗮𝘀 𝗻𝗲𝘄 𝗻𝗲𝗲𝗱𝘀.

Software used to be just a conduit to something else (Airbnb helps you find houses to book), but now tech/AI is the product.

This means that trust needs go from "𝘄𝗲 𝗹𝗼𝗴 𝘄𝗵𝗮𝘁 𝗵𝘂𝗺𝗮𝗻𝘀 𝗱𝗼 𝗼𝗻 𝗼𝘂𝗿 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲" to "𝘄𝗲 𝗱𝗼 𝘁𝗵𝗲 𝘄𝗼𝗿𝗸 𝗰𝗼𝗿𝗿𝗲𝗰𝘁𝗹𝘆 𝗮𝗻𝗱 𝗰𝗮𝗻 𝘀𝗵𝗼𝘄 𝗵𝗼𝘄."

📖  𝗕𝘂𝘆𝗲𝗿𝘀 𝗮𝗿𝗲 𝘀𝗲𝗹𝗳 𝗲𝗱𝘂𝗰𝗮𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗴𝗼𝗶𝗻𝗴 𝗱𝗲𝗲𝗽𝗲𝗿.

You need to come to the table with:

• A stronger, more thought out point of view
• A personalized demo that gets to a 'light bulb' moment faster
• Need to show tangible value earlier (before the traditional POC)

⚙️  𝗦𝗮𝗹𝗲𝘀 𝗿𝗼𝗹𝗲𝘀 𝗮𝗿𝗲 𝗯𝗲𝗰𝗼𝗺𝗶𝗻𝗴 𝗺𝗼𝗿𝗲 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹

"Instead of understanding the people using your software, AEs need to understand the technical details of how agents will actually do the work of humans."

At Clay, we collapsed the AE & Solution Engineering roles to provide a better customer experience and to help with points 1-4. We're called GTM Engineers.

👷‍♀️  𝗙𝗼𝗿𝘄𝗮𝗿𝗱 𝗱𝗲𝗽𝗹𝗼𝘆𝗲𝗱 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗵𝗲𝗹𝗽 𝗴𝗲𝘁 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝘁𝗼 𝘃𝗮𝗹𝘂𝗲 & 𝗳𝗮𝘀𝘁𝗲𝗿 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻𝘀. 

AI-native success teams work directly with customers to design prompt logic and data integrations while passing feedback to GTM and product teams. 

Decagon calls this an Agent PM; 
Harvey calls it a Solutions Architect.
Clay calls them Growth Strategist

Check out the post for more insights in the comments.

62% of your pipeline is complete bullsh*t and you are wasting time on the wrong people. This is 

This is what came out of my conversation with Hussain Al-Shorafa CEO of Revic who just dropped one of the most uncomfortable truths about modern sales I've heard:

Your tech stack is lying to you. And everyone knows it except the people signing the checks.

Here's what actually happened when Hussain walked into a company using SixSense, ZoomInfo, and every intent data provider you can name:

"We told them 62% of the accounts you're pursuing are outside your ICP."

Their response? "Go pound sand. You're a nobody startup."

Four months later, the CRO is at dinner when he gets an email: they just lost a major deal. Hussain pulls up his phone and shows him: "You never had a chance with this account. Also, you have $40 MILLION in pipeline exactly like this."

The Pattern Nobody Wants to Admit
Listen to this episode if you wanna learn about:
• Why that deal you're counting on for Q4 was dead 6 months ago (and how to spot it)
• The job posting signals that predict buying behavior better than any intent data
• How one dinner conversation exposed $40M in fake pipeline
• Why your 15-year sales vet might be your biggest ICP problem
• The real reason playbooks don't transfer between companies (hint: it's not skill)

One of my favorite conversations and more in the full Newsletter on Substack, if you want to hear it, let me know in the comments!

HAPPY THANKSGIVING WEEK! I am truly, humbly grateful for all your support, insights, and how good you have been to me this last year of 2025. So many 

Open article: 11/26/25: Why AI Engineers Are Betting Against Unicorns (And What GTM Leaders Should Actually Build Instead) by Jonathan M K. • 6 min read

11/26/25: Why AI Engineers Are Betting Against Unicorns (And What GTM Leaders Should Actually Build Instead)

As a musician and AI nerd, this is crazy. 

In the strongest sign yet that the world’s biggest record labels are embracing AI, leading AI-music platform Suno announced Tuesday that it has settled Warner Music Group‘s lawsuit over the use of its songs in Suno’s training data, and Suno and WMG are partnering on "next-generation licensed AI music."

"This landmark pact with Suno is a victory for the creative community that benefits everyone," Robert Kyncl, CEO of Warner Music Group, said in a statement. 

Read more here: https://lnkd.in/gAAgvaVj

AI Engineers are betting against Unicorns, AI model updates and more, I break it down for you, want it?

HAPPY THANKSGIVING WEEK! 🦃

I'm genuinely grateful for all of you who've been part of this wild 2025 journey. Your insights, challenges, and late-night "hey, is this AI thing actually real?" messages have shaped everything I do.

This week's newsletter is... spicy. 

We're talking about why the smartest engineers in the room are betting against unicorns, how one CEO exposed $40M in fake pipeline at dinner (with receipts), and the uncomfortable truth about why your tech stack might be lying to you.

The research papers alone took me down a rabbit hole about inverse unit economics that will change how you think about AI pricing forever. I've already loaded everything into a NotebookLM for you to explore deeper.

Three things that shocked me this week:
• That $20B valuation on 0.2% market share (the math is brutal)
• Why Equifax and TransUnion have nothing in common (wait, what?)
• The real reason playbooks don't transfer between companies

Whether you're cooking turkey or closing deals this week, this one's worth your time.

Because sometimes the best insights come when everyone else is distracted.

If you want the goods, then do the following:
1-Like this post
2-Comment TURKEY
3-I will send Post haste!

Or get it here: https://lnkd.in/g9_8Bv7M

And have an amazing holiday!

Michael Ocean

SellMeThisPen

No more...

👎 CRM update dilemma
👎 Irrelevant & generic coaching & training

SellMeThisPen AI eliminates non-revenue tasks for sellers and helps leaders scale personalized coaching and practice so everyone can focus on what matters most: revenue growth! 

What SellMeThisPen can help you with: 

✨ Automated CRM updates ✨ Real-time and post-call AI coaching ✨ Role-play practice sessions with AI

Founder & CEO

GoWest.ai

Providing strategic insights on new and ongoing initiatives.

Member of the Board of Advisors

Amazon Web Services (AWS)

Entrepreneur In Residence

Antler

Hopin

Online Event Platform - SaaS

80% Inbound | 20% Outbound - Founding Sales Team

- Helped build the initial sales playbook 
- 900k USD closed-won opportunities created.
- Helped scale the company from 40 Mil USD series A to 400 Mil USD series C.
- Worked closely with the marketing, support and sales ops teams to refine the sales development processes.
- Recognized as the "Pacesetter" in the last month of service.

Founding Sales 

Schedulehead

Event Scheduling Automation - SaaS

50% Inbound | 50% Outbound - First Sales Hire

- Built the initial sales playbook.
- Assisted the CEO with overall sales and marketing strategies.
- Closed, onboarded, and trained 48 SMB & Enterprise accounts in the first five months 
- Hired & trained LDRs & SDRs.

Founding Sales

Bunz

Digital Marketing - Social Media

100% Outbound - First Sales Hire

- Created the V1 outbound playbook
- Helped surpass the Q1 goal in the first month
- Brought in GTA-based clients such as Maple, TruLocal, Flexday, Workhaus and York Region Municipality
- Signed an agreement with the first outside of province client MissFresh

PayamBox

Mobile Marketing - Enterprise Software

*Iteration from M-Theory to an enterprise software solution for the Telecom industry. 

- Raised 400k seed capital 
- Implemented the solution for MTN - one of the largest operators in MENA 
- Worked closely with the technical team for two fully operational products - MBOX mobile marketing SaaS and Telegram MusicBoxBot.

Co-Founder & CEO

M-Theory

Content Production | Mobile Marketing - Telecom VAS 

*Pivoted to PayamBox.

- Helped sign a partnership with "MCI" the largest operator in the middle east
- Acquired 200k+ subscribers - Resulted in $1.2 mil USD revenue.
- Reduced the operation costs by 50% - Built an in-house video production team
- Grew the team to 10

Co-Founder

PCM: The Right Technology, Delivered.

Direct Marketing - Microsoft Cloud

100% Outbound - First batch of Microsoft licensing specialists 

- Surpassed the monthly closed deals KPI month after month
- Helped position the company as the new Microsoft Gold Partner to clients

Account Executive

Two things bugged me the most when I was a sales rep!

👎 Receiving irrelevant & generic coaching & training
👎 Feeling out the CRM 

That's why I am building SellMeThisPen AI to eliminate non-revenue tasks for sellers and help leaders scale personalized coaching and practice so everyone can focus on what matters most: revenue growth! 

What SellMeThisPen can help you with: 

✨Role-play practice sessions with AI ✨Real-time and post-call AI coaching ✨Automated CRM updates

🤝 Feel free to reach out if you would like to chat.

Everyone in the space is obsessed with efficiency BUT blind to what’s coming.


What happens when AI makes your whole sales org faster…but forgettable?

On the SellMeThisPen AI Podcast, I sat down with Kelly Wright, Founder & CEO of Culture Driven Sales, former President & COO at Gong, and the sales exec who took Tableau from $0 to $850M in revenue.


"People buy from people. Companies don't buy from companies."

That’s not fluff, it’s the hard truth about what separates top sellers from the rest.

Kelly built Culture Driven Sales after watching tech companies chase speed at all costs.

Every dashboard. Every pipeline review. Every tool, all aimed at efficiency. 
But as she puts it, AI is going to make everyone equally efficient.

Same data. 
Same speed. 
Same playbooks.

So what’s left?
Your people!


At Tableau, Kelly broadened reps’ development path with storytelling training. Every rep went through it, learning how to connect emotionally, not just close logically.

Within months, customers were calling her asking, “Why are your reps so different? They actually get me.”

That’s what happens when you lead with culture.


Here’s the 3-step playbook she shared to build that edge:

👉 Start with purpose.
If your team can’t tell you why your company exists, you’ve already lost. Anchor every deal in mission, vision, and values.

👉 Train for connection.
Teach reps to read the room, grab attention in 15 seconds, and tell stories that stick. That’s emotional enablement.

👉 Build unshakable trust.
Be the vendor who tells the truth even when it’s not convenient. 


That’s how you win loyalty AI can’t automate.
AI will level the field. Culture will tip it back in your favor.

Go check the full framework in the carousel above for more insights! 👉

CEO @ SellMeThisPen.ai - AI Roleplay & Individual Sales Coaching at Scale.

The Culture Driven Sales Framework - SMTP

When everyone’s powered by AI, culture becomes your advantage.

When every competitor has the same data, same tools, and same efficiency…what’s left to set you apart?


On the latest SellMeThisPen Podcast, I sat down with Kelly Wright former EVP of Sales at Tableau, ex-President & COO at Gong, and now founder of Culture Driven Sales. We talked about how AI is making sameness the norm and why your culture will be what breaks you out of it.


“If your people can inspire, motivate, and communicate in a way that makes others believe they’re part of something special, that’s the real differentiator.”


At Tableau, in addition to traditional sales training, they trained the entire sales org in storytelling. Every rep learned how to connect emotionally first, then sell. The results? 

Customers started saying “Your team feels different.” Prospects trusted them before the demo even started.That’s the power of culture, it shapes how your people show up long before the pitch begins.


👉 Start with your “why.” Before the product, sell your belief. People buy from conviction, not comparison.

👉 Enable connection, not just conversion. Emotional intelligence beats perfect talk tracks every time.

👉 Protect your mission internally. When your team believes, your buyers feel it.


In the full episode we cover:

– The shift from sales driven to culture driven organizations
– Storytelling as a competitive advantage
– How companies lose (and revive) their “why”
– Why AI will make culture your ultimate differentiator


What’s your take -> can belief still win in a data driven world?

P.S. Link to the full episode in the comments! 👇

Natural talent is the worst predictor of sales success.


So why do so many teams still hire for “the vibe” instead of the mindset?


On the latest SellMeThisPen AI Podcast, I sat down with Thomas Waites of TW Sales, operator behind 3 successful acquisitions, and someone who’s built multiple high-performance sales orgs from scratch to unpack this exact mistake.


"I watched 'natural' salespeople plateau while awkward, determined ones surpassed them."


Thomas learned this early. He’d onboard 20–40 reps at a time and assume the charismatic ones would win.

They didn’t.

The “naturals” coasted…then stalled!


The “awkward but hungry” reps kept grinding then sprinted past everyone.
That observation shifted everything for him.
Because the real problem wasn’t skills.
It was the system those skills lived inside.


He told a story about inheriting a team where people complained about 9 a.m. meetings because it interfered with their morning golf routine.

That wasn’t a skills issue.

That was a mindset and behavior issue and no amount of training fixes that.

So he rebuilt the culture from the ground up.

Reps stopped blaming leads.
Ownership went up.
Performance followed.


Here’s the framework Thomas shared for building a winning environment instead of a “talent-dependent” one:

1️⃣ Hire and bet on mindset first
If someone owns their performance, you can develop everything else. If they blame the world, nothing you do will matter.

2️⃣ Create systems that lift the entire team
Peer-to-peer pairing, shared wins, and simple metrics make improvement unavoidable not optional.

3️⃣ Lead with belief, not fear
High performers don’t need pressure; they need support. If you treat them like losers, they’ll play like it. If you treat them like champions, they rise.

4️⃣ Reward behavior as much as outcomes
Crushing quota isn’t enough. If someone poisons culture, they’re a short-term win and a long-term loss.

If you want a team that keeps improving, you don’t build around the naturals.
You build around the mindsets that scale.


Swipe through the carousel above for the full breakdown! 👉

 7 Pillars for Building Winning Mindset - SMTP

AI didn’t make L&D easier, it exposed who’s been coasting!


So the real question is…are you actually using it to level up, or just hoping it replaces the work you don’t want to do?


The other day on the SellMeThisPen AI Podcast, I sat down with Jen Rutsky an L&D leader with a legal background who’s been hands-on with AI long before it went mainstream. She’s worked across tech, law, finance and she’s one of those  operators who actually experiments instead of theorizing.


Jen described a shift she’s seeing: most L&D orgs still cling to e-learning modules that nobody remembers 20 minutes later. Meanwhile, learners want interactive, kinesthetic, real-time practice. And AI finally makes that possible.


She told a story about managers preparing for tough conversations. Traditionally, they’d wait for Jen to role-play with them assuming her calendar wasn’t booked for the next two weeks. Now? They can fire up a tool, simulate the scenario, and get coaching instantly. No embarrassment. No bottleneck. No excuses.

That’s the shift:

We’re not building courses anymore. We’re building systems that adapt.

Here’s the core idea: L&D relevance now comes from teaching people how to use AI not from producing content.

1️⃣ AI is the new practice field.
Your learners shouldn’t wait for workshops. They should rehearse critical conversations, pitches, and decisions inside AI-driven role-plays, the reps are unlimited, judgment-free, and instant.

2️⃣ Your value is orchestration, not instruction.
Jen’s building workflows, coaching layers, feedback loops. AI handles the repetition; humans handle the nuance. L&D pros who cling to “content creation” lose. Those who build systems win.

3️⃣ Real-time relevance is now the standard.
If a document, process, or naming convention changes, AI can update onboarding flows instantly. No more outdated links, stale PDFs, or credibility-killing errors. L&D finally becomes current instead of catching up.


In the full episode we cover:

– Why e-learning as we know it is fading fast
 – How managers should approach hallucinations with “trust but verify”
 – Building AI champion programs inside companies
 – What modern onboarding looks like when every persona gets personalized learning from day one

L&D pros -> what’s one AI use case you’ve tried that actually moved the needle?

P.S. Link to the full episode in the comments! 👇

Your L&D team isn’t slow. Your workflow is outdated.


The other day on the SellMeThisPen AI Podcast, I sat down with Jen Rutsky, Senior L&D Manager at Yext with 15+ years across banking, tech, fintech, and law. We dug into what’s actually breaking L&D’s speed and what AI is finally fixing.


“It’s helping me amplify my ideas and catch things I might’ve missed.”

Jen shared a moment every L&D leader knows too well: juggling too many trainings, rewriting the same ideas 10 different ways, and manually hunting inconsistencies across documents.

It’s exhausting. And worse, it slows down how fast the business can move.
Then she stopped doing it alone.


AI became her always-on co-author, spotting patterns, surfacing repeated themes, and keeping messaging tight across every training touchpoint.
 The shift wasn’t about shortcuts, it was about finally removing the parts of L&D that shouldn’t be manual anymore.


Here’s the core idea: L&D isn’t broken, old workflows are. AI gives you back the time to think, not just produce.


1️⃣ Offload the grunt work, keep the judgment.
Let AI scan PDFs, books, and decks for themes so you can focus on designing experiences, not cleaning data.

2️⃣ Use AI to maintain consistency across everything.
Jen uploads materials and instantly spots mismatches, outdated details, and messaging drift something humans miss simply because we’re too close to the work.

3️⃣ Turn brainstorming into a real collaboration.
Instead of staring at a blank doc, she uses AI to challenge her thinking, propose angles, and pressure-test concepts. You get better ideas, faster.


The result? Faster content, tighter messaging, and an L&D engine that finally matches the speed of the business.


Swipe through the carousel above for the full breakdown! 👉

6 Practical Ways to Use AI in L&D - SMTP

Most sales leaders don’t coach…they command.


Why are we still defaulting to “just do this” leadership when coaching creates the real top performers?


On the latest SellMeThisPen AI Podcast, I sat down with Thomas Waites, 3X acquisition CRO and the guy who keeps turning messy early-stage teams into record-breaking ones.


"Telling solves the moment. Coaching changes the rep." 


Tom shared something most leaders don’t want to admit: the majority of “coaching” inside sales orgs is actually just instructions with better punctuation. 

And when you lead that way? You create a team that waits for answers instead of creating them.


The shift came when he realized his team wasn’t lacking talent, they were lacking belief, ownership, and a system that helped them think.


Here’s the real difference between telling, training, and coaching. pulled straight from Tom’s winning-culture framework:

1️⃣ Telling -> One-way and urgent.

When a rep asks what to do with a deal, you say: “Send the contract today.”
Fast? Sure. But now you’re the crutch they lean on forever.

2️⃣ Training -> Knowledge without judgment.

You run sessions on your pitch, your product, your frameworks.
Helpful until the deal goes sideways and the script can’t save them.

3️⃣ Coaching -> Two-way, empowering, and culture-shaping.

 Rep: “What should I do with Acme?”
 You ask:
 – “What’s the real blocker here?”
 – “What options do you see?”
 – “Which path gives us the highest leverage?”

Now they think. They decide. They grow.
And suddenly, the whole team levels up, together!


In the full episode we cover:

 – Why mindset beats sales skills (and why “naturals” often plateau)
 – How to build a team culture where “we all win together” actually means something
 – The CEO–sales leader dynamic that predicts success
 – The simple, four-metric system Tom uses to scale without chaos

AND he tells the tattoo bet story, the moment his team realized their limits were self-imposed!! 

Link to the full episode in the comments 👇

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