Crystal Nikosey

RISE: Research & Insight Based Strategic Enablement

Advisor

Sales v̴s̴  and Enablement, The Podcast

Co-Host

Sales Enablement Society

Member

The Sales Collective

Vice President, Sales Transformation

WiSE - Women in Sales Enablement

Phoenix Chapter Lead

UserZoom

Director, Global Revenue Enablement

Second Nature

Customer Enablement Lead

Trust Enablement

Contributor to one of the 20 Best Sales Podcasts for 2021 named by Vendor Neutral.

Focused on helping sales enablement and revenue enablement practitioners and leaders succeed for themselves, the businesses they work for, and the profession overall.

Trustee

Cloud Academy, Inc.

Sales Enablement Manager

Tribyl, Inc.

Tribyl (pronounced tribal) is the industry’s first Digital Value Selling™ Platform.

Enterprises are learning that qualifying and closing deals over Zoom is here to stay for the foreseeable future. And that ‘value selling’ is no longer an optional buzzword in this economy.

Tectonic shifts define winners and losers. Driving Digital Value Selling™ is a career-defining move for CROs. Learn more about the 5 capabilities required for Digital Value Selling in the linked article.

Director, Customer Enablement

Crystal has been driving measurable impact in revenue enablement since 2012, designing data-backed programs that optimize sales team performance. 

Certified in Objective Management Group’s (OMG) sales competency-driven assessments, she combines a rigorous approach to sales processes across BDR, SDR, and AE roles to deliver consistent, scalable growth. 

Her expertise in improving key sales metrics—focusing on behaviors, process efficiency, and skill development—has directly contributed to increased deal velocity, win rates, and overall team productivity.

**Crystal’s Certifications and Expertise:**

- MEDDPICC Certified: Driving predictable revenue growth through disciplined sales process management

- Cross-Functional Optimization: Aligning goals across departments for measurable impact on sales outcomes

- Sales Training: Programs designed with a direct tie to business KPIs

- OMG Certified: Expertise in competency-based assessments to pinpoint growth opportunities

- GTM Strategy Development: Building go-to-market plans that deliver quantifiable results

- Change Management Leadership: Leading organizational shifts with a focus on data and results

- Motivational Styles: Leveraging intrinsic, extrinsic, and altruistic motivators to improve team performance

- Coaching/Leadership: "Coach the Coaches" approach to ensure sustained improvement across sales teams.

- AI: Intermediate proficiency, with a focus on applying AI for process improvement and predictive analytics

Senior Director, Sales Transformation

Jonathan M K.

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.

Google just quietly built the most comprehensive AI stack on the planet—and 90% of GTM teams are ignoring it.

Here’s what most people miss:

While everyone debates ChatGPT vs Claude, Google shipped 40+ AI products that already live inside the tools your team uses daily.

Gmail. Docs. Sheets. Meet. Drive. Search. Maps. YouTube.

All connected. All powered by Gemini. All learning from each other.

The math:

$19.99/month gets you:
→ Gemini 3.0 Pro (outperformed GPT-5 Pro on 19/20 benchmarks)
→ AI in every Workspace app
→ NotebookLM Plus for research
→ Image and video generation
→ 2TB storage

That’s less than most teams spend on a single AI tool.

Real GTM use cases delivering results right now:

Pipeline Research
NotebookLM + company 10-Ks + earnings calls + news articles = comprehensive account intelligence in 15 minutes vs 3 hours of manual research.

Meeting Leverage
“Take notes for me” in Meet auto-generates summaries with action items. “Send Gemini to meetings” attends calls you can’t make and reports back.

Content Velocity
Deep Research compiles multi-page reports from Gmail, Drive, and web sources. One prompt. One output. Ready for editing.

Outbound Personalization
Gemini processes prospect LinkedIn profiles, company news, and your CRM notes simultaneously. Personalized sequences at scale without the robotic feel.

Competitive Intel
NotebookLM Audio Overviews turn competitor documentation into 10-minute podcast briefings your team actually consumes during commutes.

Proposal Generation
Workspace Studio agents (just launched) automate the grunt work—pulling CRM data, generating first drafts, routing for approval. 20 million tasks executed in month one of alpha.

The strategic advantage nobody’s talking about:

Google’s AI isn’t just in your browser. It’s on your phone (Pixel), in your home (Nest), on your wrist (Watch), and in your car.

One ecosystem. One subscription. Context that follows you everywhere.

Your competitor is still copying and pasting between 6 different AI tools.

You can have one system that already knows your emails, calendar, documents, and workflow patterns.

The bottom line:

The best AI stack isn’t the one with the highest benchmarks.

It’s the one your team actually uses because it’s already embedded in their workflow.

Google understood the assignment.

Jonathan M Kvarfordt, MBA

Last call to get people into my  TEST course teaching AI using only... AI. Would love testers, anyone else want in?

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?

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.

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

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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.

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

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.

It is TIME for the GTM AI Podcast and newsletter, this week we got a lot of goodies including the amazing interview with Ken Roden around his research paper he is doing which is FASCINATING.

That and tons of research, news, trends, and more in the free GTM AI Newsletter with some AI goodies, let me know if you want it!

View newsletter: GTM AI Podcast & Newsletter

Once again it is TIME for the GTM AI Podcast and newsletter sponsored by the GTM AI Academy and AI Business Network. This week we have a lot to get in

Open article: 12/4/2025: Why 88% AI Adoption Actually Means You’re Already Behind by Jonathan M K. • 6 min read

12/4/2025: Why 88% AI Adoption Actually Means You’re Already Behind

Want a deep dive into AI agents and how to use AI in companies? Today's podcast guest Elliot Garreffa goes into how he does it with sharing screen and all the goodness.

Most AI projects fail because companies are asking the wrong question.

They ask: "How can AI make this process faster?"

They should ask: "If I had this capability from day one, what process would I design?"

Here's what stood out:
The Real Problem Isn't the Technology

Companies say "we tried ChatGPT for content and it wasn't good"—but that's like judging a car by only using first gear.

The breakthrough happens when you stop bolting AI onto broken processes and start reimagining workflows entirely.

-Why Most POCs Never Scale
Elliot's team spends zero time touching technology in phase one. They talk to the actual teams, map workflows, identify root causes (not symptoms), and build business cases with real projected ROI.
Result? Systems that teams actually use instead of another forgotten pilot program.

-The Autonomy Trap
Fully autonomous AI isn't there yet. The companies winning are building rigid workflows with strategic human checkpoints—not because it slows them down, but because it's the difference between content that converts and content that screams "AI-generated."

His live demo compressed months of SEO agency work into a chat window conversation. Same research depth. Same strategic recommendations. Minutes instead of months.

The episode drops insights on:
-Why your CRO's diagnosis is probably wrong
--The "proof of value" framework that gets executive buy-in
---When to use no-code tools vs. going technical
----How MCPs are changing the game for workflow automation
-----If you're tired of AI projects that look impressive in demos but die in production, this one's worth your time.

Once again it is TIME for the GTM AI Podcast and newsletter sponsored by the GTM AI Academy and AI Business Network. We have a lot to go through with 

Open article: 12/10/25: AI Adoption Splits: Enterprise Dollars Rise While Competition Implodes Everything by Jonathan M Kvarfordt, MBA • 4 min read

12/10/25: AI Adoption Splits: Enterprise Dollars Rise While Competition Implodes Everything

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.

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

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)

Your AI pilots aren't failing because of the technology.. take a wild guess why they fail? Wanna know? Let me send it to you...

It is time for the GTM AI Podcast and newsletter and I was fortunate to interview Ken Roden diving into his doctoral research at Temple University, and what he uncovered should fundamentally change how every GTM leader thinks about AI implementation in 2026.

Ken surveyed 200 professionals with statistically significant findings and the pattern he discovered explains why every headline is screaming about AI pilot failures. But it's not what MIT is telling you. It's not what the consultants are writing case studies about. And it's definitely not what you think.

The real blocker isn't employee resistance. It isn't inadequate technology. It isn't even change management.

I'm not going to spoil the actual finding here because you need to hear Ken walk through the data himself. But I will tell you this: If you're a GTM leader who thinks you understand how your team is using AI right now, you're almost certainly wrong. And that misunderstanding is costing you deals, talent, and competitive positioning every single quarter.

We also unpacked:
→ Why the people who think they're AI experts are often the least competent (and how to fix that) 
→ The "boring" use cases that are saving 20+ hours per week per rep (hint: it's not what's getting VC funding) 
→ Why your most confident AI users might be your biggest liability 
→ The AI Sandwich Model that's actually getting pilots to production 
→ What "AI fatigue" really means and why it's about to hit your team hard 
→ Why GPT-5's "Gronk problem" means you need to diversify your AI stack immediately

This conversation was one of those rare ones where I kept saying "wait, go back to that" because the implications kept cascading. The trust architecture piece alone will change how you think about rolling out AI across your org.

Not only that but I always deep dive into each weeks major AI releases that impact GTM leaders and professionals that you can read for free.. and I may give some other AI goodies in there too ;)

Want it? You know what to do... like
-Like this post
--Comment Your favorite Christmas song
---Repost cuz who doesn't wanna see lists of Christmas songs?

#GTM #ArtificialIntelligence #SalesStrategy #Leadership #GoToMarket

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!

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The Battle

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Jonathan M K.

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The Battle

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Jonathan M K.

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Engagements

Likes

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