Dale Zwizinski

🤝 Chief GTM Officer | YOUR GTM Special Ops Team | Founder enabled GTM Strategy -> Data vs. Gut | Give > Receive | Recovering Coder | Extending Runways for Founders | Must haves 💪 Grind 🧠 Integrity 🎯 Coachability

An energetic, top performing sales professional, leader, and coach who is passionate about the Cloud based technologies.  More than 20 yrs experience with enterprise sales and known for my ability to grow and enhance businesses.   Working with innovative technologies and platforms to make customer successful wakes me up in the morning!
 
A self-starter who is happiest when helping customers enhance their business with innovative technologies.  It is important to stay ahead of trends and looking for ways to help a customer grow their business and improve their products/services.  The sales environment has changed dramatically over the last 5 years, the next 5 years will be a monumental shift --> Sales, Marketing and Service are on a collision course.

The pursuit of sales and maintaining customer satisfaction has taken me around the globe.  Establishing contacts and a track record of success in the financial service market throughout China, Asia, Mexico, and the United Kingdom, just to name a few.  Every sales person should be well versed in cultural differences and knows that paying attention to such details can make or break a sale.

SALES is changing and utilizing every available channel is important - if you are reading this you know what I am talking about!  To understand more about the sales evolution come read and listen to content here: www.thesaleschangeagent.com
 
Entrepreneurship and education is a deeply ingrained with a MBA from the Olin Graduate School of Business at Babson College.  and an undergraduate degree (with a double major in Management and Finance) at Merrimack College. Living in Lakewood Ranch, Florida (outside of Tampa), with my wife and 2 children.   For fun I enjoy traveling with his family, play/coach soccer, workout, ski, and golf.

Dale Zwizinski
Mobile: 401.952.9231
Email: dzwizinski@gmail.com

Strategic Sales Advisor

Collaborating with the CEO on all thing revenue, including:
✅ Go to Market
✅ Aligning to the Buyers Journey
✅ Pricing Strategies
✅ Sales Pipeline Growth

Our mission is to empower Customer Success teams to build great relationships with their customers.

We work with early and growth stage B2B SaaS companies to help them scale Customer Success outcomes.  Everything we do is devoted to removing the overwhelm of back-to-back customer meetings so that CSMs can focus on the bigger picture: building relationships.

UpdateAI is the first meeting assistant built specifically for CS.

I partnered with Revenue Creator to bring a 5-part series to the community on one topic:

AI in Go-To-Market is no longer optional.

This is not theory. It is not hype. It is not experimentation.

The market is already splitting between companies building AI into their GTM strategy and those who are quietly falling behind.

Early data shows:
• 26 to 50 percent higher win rates
• Up to 78 percent higher conversion rates
• 62 percent shorter sales cycles

But those are just early signals.

The real disruption is this: revenue is being decoupled from headcount.

Look at Midjourney. Millions of users. Eleven employees.
That is not an anomaly. It is leverage redefined.

Over this 5-part series, we break down:

1️⃣ Why AI-native GTM is a strategic imperative
2️⃣ The 4-stage maturity model from automation to autonomy
3️⃣ The ROI progression from tactical gains to exponential returns
4️⃣ The C-suite mandate and the leadership actions required
5️⃣ The assessment and governance framework that makes it sustainable

Here is the hard truth:
73 percent of companies are still stuck at basic task automation.
82 percent of AI initiatives fail because of leadership, not technology.

The roadmap is clear.
The returns are real.
The leadership moment is now.

Your board is not asking whether AI will transform your market.
They are asking whether you will lead that transformation.

Read the full series and decide where you stand.

Your next 90 days will define the next decade.

I partnered with Revenue Creator to bring this 5-part series to the community. Part 1: The Strategic Imperative: Why This Is No Longer Optional Let's 

Open article: Your 5-Part Strategic Roadmap to AI-Native Transformation by Dale Zwizinski • 4 min read

Your 5-Part Strategic Roadmap to AI-Native Transformation

73% of AI startups are stuck automating emails.

Meanwhile, their competitors are building Autonomous GTM Engines.

The trap? 

Founders skip GTM Foundations and jump straight to "scale."

Here is what the 4 stages actually look like:

Stage 1: Task automation (emails, summaries)
Stage 2: Process augmentation (CRM updates, reporting)
Stage 3: System orchestration (connecting data silos, proactive alerts)
Stage 4: AI as a teammate closing complex workflows

Most never escape 

Stage 1. Not because the tech is not ready. Because leadership is not ready.

What is your:
1. Value Proposition 
2. Ideal Customer Profile
3. Buying Persona

Where is your team right now?

undefined undefined

the-sales-change-agent

revenue-in-a-box

AI isn’t magic. It’s infrastructure.

But too many companies are treating it like magic anyway.

They’re piling on tools. 
Automating fragments. 
Naming “Heads of AI” without ever asking: Are we actually ready to transform?

Leaders want outcomes from AI, but skip the foundation it depends on:

🧭 Strategy
Do you have a clear roadmap tied to outcomes; or are you experimenting without direction?

📊 Data + System Integration
Is your GTM data clean and unified; or is each department running its own playbook?

🧠 Talent + Culture
Have you built AI literacy across the org; or is your team quietly resisting new workflows?

🛡️ Governance
Are you tracking performance, bias, and compliance; or hoping those problems don’t show up?

🚧 Companies stumble when they skip this maturity assessment.
🏗️ Companies scale when they build it in.

If you’re not getting ROI from AI, it’s not your model.

It’s the system you’re putting it into.

📈 The path to AI-native GTM starts with clear diagnostics, real alignment, and foundational execution.

Your Current Position: The Maturity Assessment Before investing in transformation, you need an honest assessment of your current capabilities across f

Open article: The Blind Spot That's Sabotaging Your AI Transformation by Dale Zwizinski • 3 min read

The Blind Spot That's Sabotaging Your AI Transformation

Stop blaming your sales team for a "growth problem" when you actually have a fragmented systems problem.

I see it every single week. Leadership teams get in a room, draw up a beautiful strategy, pat themselves on the back, and then hand it off to a team that is fundamentally misaligned at the ground level.

On the latest episode of Bridge the Gap, Nicole Brownell  (Managing Director at Novo Advisors) joined Adam and me to pull back the curtain on why execution fails even the best strategies.

Here is the cold, hard truth:
Alignment isn’t a feeling. It’s a shared scorecard.

Nicole dropped some serious gems that every C-suite leader and RevOps pro needs to hear:

1. Revenue isn't just a Sales KPI.

If you are only holding Sales accountable for revenue while Marketing is chasing "brand awareness" and "MQLs," you’ve already lost. If the departments aren't speaking the same language or sharing the same metrics (like OKRs that roll up to a single goal), you don't have a team—you have silos.

2. The Product/Sales Gap is killing your retention.

This one hit home. Nicole pointed out that sales teams often sell a version of the product that doesn't actually exist in reality. When the "value delivered" doesn't match the "value promised," you don't have a sales problem—you have a retention crisis waiting to happen 30 days after the contract is signed.

3. RevOps is your Playbook.

Strategy is the "where" and "how" of winning. RevOps is the actual playbook that dictates how you play the game. Without RevOps holding the line, your systems stay fragmented, your data stays dirty, and your execution stays sloppy.

We spend so much time talking about strategy because it’s the "fun" part. Execution is the hard part. It’s the daily grind of making sure the front-line narrative matches the back-end delivery.

If your GTM motion feels like it’s grinding gears, stop looking for more leads. Start looking at your alignment.

Are your teams actually aiming at the same target, or are they just sitting in the same meetings?

Check out the full episode for more on how to bridge this gap.

https://lnkd.in/eZ-8EADf

Most teams do not have a strategy problem.

They have a handoff problem.

This week I watched a solid plan lose 10 days in execution.

Not because people were lazy.

Because ownership got fuzzy after kickoff.

Here is the operator fix:

The 3 line handoff

1) Owner: one name, not a team
2) Outcome: what done looks like in plain English
3) Clock: next checkpoint date, on calendar before the meeting ends

That is it.

If you cannot write those 3 lines, the project is not ready.

Actionable takeaway:
Before your next launch, run every workstream through the 3 line handoff.

You will spot drift before it becomes delay.

What is your most common handoff failure right now?

Most founders hire their first sales leader too late.

Then they hire the wrong one.

Here is what actually happens:

You scale to $1M ARR on founder-led sales. 
You think you need a VP of Sales to take it from there.

So you hire someone who has scaled from $10M to $50M. 

They walk in expecting a repeatable process, a trained team, and clean data.

They find none of that.

Within 90 days they are frustrated. 

Within 6 months they are gone. And you are back to square one, except now you are $300K lighter and 6 months behind.

The hire was not wrong. The timing was.

Your first sales leader should be a builder, not a scaler. 

Someone who can create the process from scratch, not someone who needs one handed to them.

Conversely you can also look at Operating Partners to ensure that you  have everything stabilized and foundation built before bringing a VPS sales hire, and ensure that they have all of the right things in place for success.

Get the stage right before you get the person.

Personalization Beats Automation

Buyers don’t need more email; they need relevance.

High-performing GTM teams are using intent data, deal stage, and buyer behavior to create true personalization at scale.

Most companies think they're doing AI because they have a chatbot. 

That's Stage 1 maturity
-> Task automation. It's the equivalent of a faster typewriter.

The real competitive advantage is the jump from Stage 2 to Stage 3. 
-> System Orchestration.

Stage 2 is process augmentation. 
-> You've added AI to existing workflows. It's better, but it's still siloed.

Stage 3 is where the magic happens. 
-> This is where AI isn't just a tool in the workflow. It is the workflow. 

Data flows from marketing to sales to customer success without human intervention. 

The system identifies a lead, qualifies it based on real-time intent data, assigns it to the right rep, and drafts the personalized outreach.

If your team is still manually moving data between tools, you're stuck in the past. 

Stage 3 isn't about working harder. 
It's about building a system that works for you. 

The jump to Stage 3 is where the 7x conversion rates live. 

Stop automating tasks. 
Start orchestrating systems.

Everyone needs a board or advisors to help you, try this:

"You are building a high-fidelity AI advisor for Dale Zwizinski’s Personal Board of Directors. This advisor must operate as a Chief of Staff-level strategist, not a generic assistant and a team of advisors.

Use the following structure to define their core logic. 

Do not write a 'personality description.' Write a 'Reasoning Engine.'"

────────────────────

1. The Core Identity
[ADVISOR NAME] – [ROLE, e.g., Chief Revenue Officer]
Lane of Genius: [One paragraph. What is the specific territory this person owns? What problems do they see that others miss?]

2. Core Frameworks & Mental Models
List 5–8 named frameworks this person uses to process reality. These are the "rules of the game" for this advisor.
• [Framework 1]: [Brief description of how it works]
• [Framework 2]: [Brief description of how it works]
• [Framework 3]: [Brief description of how it works]

3. Non-Negotiables (The "Edge")
What are the hard constraints this advisor would never compromise on? What makes them push back? This section prevents the AI from becoming "too nice."
• Constraint 1: [e.g., Never accepts incremental 5% growth; only 10x shifts.]
• Constraint 2: [e.g., Allergic to 'consulting-speak'; demands direct, plain English.]

4. The Decision Filter
When Dale presents a problem, what is the exact sequence this advisor uses to analyze it?
1. Filter 1: [What is the first question they ask?]
2. Filter 2: [What framework do they apply next?]
3. Filter 3: [What is their final stress test?]

5. Voice & Delivery
Describe the tone and format. 
• Constraint: No fluff, no "I hope this helps," no summaries. Direct insights only.
• Style: [e.g., Blunt, visionary, sardonic, or data-driven.]

This is a start to how your can incease your effectiveness and efficiencies!

Let’s Build Your 2026 GTM Engine

AI is changing how GTM is executed.
But without a system and strategy;it’s just noise.

At Revenue Reimagined, we help CEOs and revenue leaders:
✅ Diagnose their GTM gap
✅ Design a hybrid GTM model
✅ Deploy AI + human workflows that scale

We don’t do playbooks. 
We build operating systems.

📥 Want a GTM Foundations Report?
Get yours here:

Open article: Bridge Your GTM Gap™: Diagnose & Redefine Your Go-to-Market Strategy | Revenue Reimagined by revenue-reimagined.com

Bridge Your GTM Gap™: Diagnose & Redefine Your Go-to-Market Strategy | Revenue Reimagined

My research into 2026 GTM trends shows three massive, concrete shifts that revenue leaders are failing to navigate.

Here is the first one!

The Agentic Chasm
You don't have a talent problem. 
You have an orchestration problem.

Most revenue leaders think "AI Maturity" means giving their sales team a better prospecting tool. 

That's Stage 1 thinking, it just helps you fail faster.

The real gap in 2026 is the Agentic Chasm.
It’s when you hire AI agents to do the work, but your GTM process is still built for humans from 2019.

If your AI agent is just "automating the spam," you’re destroying your brand at scale.

The shift isn't from human to AI. 

It’s from Task Execution to System Orchestration.

Stop hiring tools. Start building the engine.

The "SaaSpocalypse" is the trending topic for a reason.

Marc Benioff and the Databricks CEO are both signaling the same thing: The old SaaS model of "seats and screens" is under massive pressure.

Why? 
Because AI agents don't need a UI. 
They need an API.

If your GTM strategy is still based on selling "more seats," you are fighting a losing battle against efficiency.

The new GTM foundation:
1. Outcomes over activities.
2. Systems over seats.
3. Autonomous engines over manual workflows.

The GTM Gap is no longer just about sales and marketing alignment. It is about the gap between your legacy software and the autonomous future.

We are moving from a world of "software you use" to "software that does the work for you."

If you are a founder or revenue leader, your job is no longer to manage people using tools. It is to orchestrate systems that deliver results.

The SaaSpocalypse isn't an ending. 

It is the beginning of the Autonomous GTM Engine.

**The Pivot Point.**

Most people think a breakthrough is a loud, celebratory moment.

It isn't.

It's usually a quiet, terrifying realization in the middle of the night that everything you've been building... might be pointing in the wrong direction.

That's the pivot point.

Not the press release. 
Not the rebrand. 
Not the announcement post.

The pivot point is the moment *before* all of that, when you're alone with the truth, and you have to decide what to do with it.

We aren't selling a podcast. 
We're selling a transformation.

And transformation always starts in the dark, before anyone else sees it coming.

Technical debt kills your product. Revenue debt kills your company.

Most founders are unknowingly accumulating massive revenue debt. It happens when you scale sales before you've stabilized the GTM Gap.

You hire three reps because you have a little traction. 
You haven't defined the ICP beyond "anyone with a budget." 
You haven't nailed the value prop. You just want volume.

Now you have:
1. Inconsistent messaging that confuses the market.
2. High churn because you closed the wrong customers.
3. A sales team that's guessing instead of executing.

This is revenue debt. 

And like technical debt, the interest rate is compounding. 

You can't hire your way out of it. 

You have to go back and fix the foundation. 

Stabilize. Foundation. Repeatability. Scalability. 

Don't skip the sequence. 

The debt will always come due.

80% of your buyer's journey is happening while you're asleep.
And they aren't filling out your forms.

The "MQL" is dead.

In 2026, if you're waiting for a "lead" to hit your CRM, you've already lost the deal to someone who was orchestrating the account months ago.

GTM leaders are still obsessed with activity metrics.
- How many calls?
- How many emails?
- How many LinkedIn touches?

The market doesn't care about your activity. It cares about its own problems.
The winners in this cycle aren't the ones with the loudest outbound.
They are the ones with the most intelligent Intent Orchestration.

Move your focus from "The Lead" to "The Signal."

That's how you close the GTM Gap.

Jonathan Moss

Turning GTM into a revenue factory through recurring impact & helping GTM leaders do the same | GTM Executive leveraging AI ✨ | Keynote Speaker & Advisor | Podcast 🎙️ Host |

I created the Revenue Nervous System™ a framework for building intelligent, self-improving growth engines that learn, adapt, and scale. The IMPACT+ Framework™ is how you implement it: a structured approach for embedding AI across the revenue lifecycle and turning strategy into execution.

I help Founders, Business Executives and Go-to-Market leaders transition to AI-native GTM and architect Agentic Growth Systems that eliminate friction and turn AI into measurable performance outcomes across their business.

At Experity, I serve as EVP & GM for Patient Engagement and Care Agent, the industry's first AI-native clinical intelligence platform. We're transforming how urgent care connects with patients through a multi-agent system that automates communication, personalizes engagement, and unifies clinical + commercial workflows across 3,000+ clinics.

Think of it as the Orchestration and Routing Layer for Healthcare: where data, context, and intelligence finally work together.

Beyond Experity, I work with founders, executive teams, and AI-native startups on growth architecture, GTM execution, and multi-agent system design.

Quick professional stats:
→ 87% median growth rate across all of my roles
→ $1B+ capital raised across portfolios
→ Scaled revenue $0 → $15B
→ Backed by Sequoia, Lightspeed, GTCR, Warburg Pincus, SoftBank

Core expertise: Revenue Nervous System™ | IMPACT+ Framework™ | Agentic AI Growth Strategy | AI-Native GTM | Patient Experience & Healthcare AI

Executive Member

Sprouts.ai named some amazing people and somehow I was included in the top 20 GTM Leaders to Watch in 2026.
 
Grateful. Also a little on the hook now.
 
Because if there's one thing I'm convinced of heading into this year, it's that the GTM leaders worth watching won't be the ones with the most tools, the most initiatives, or the loudest voices.
 
They'll be the ones who figured out how to build systems that actually compound.
 
Here's what I keep seeing: teams stall out not because they lack effort, but because they're running on architecture that was never designed for how buying actually works today.
 
Buyers are more informed. Cycles are less predictable. AI is raising the output bar for everyone.
 
In that environment, staying busy is easy. Knowing what matters is hard.
 
What I've found is that most GTM breakdowns trace back to the same root cause: the system doesn't remember, doesn't learn, and doesn't coordinate in real time.
 
You fix ICP in January. By March, the signal has shifted and nobody updated the model.
 
You run a feedback loop between sales and marketing. But nothing gets captured, so the same mistakes repeat six months later.
 
You add an AI tool. But it's bolted onto a broken process, so you get faster noise instead of better decisions.
 
The teams winning in 2026 aren't just using AI differently. 

They're building differently, around layers of intelligence that compound over time instead of resetting every quarter.
 
Clear context. Institutional memory. Coordinated execution. AI that amplifies judgment instead of replacing it.
 
That's the work. And honestly, it's still early enough that the teams who start now will have a gap that's very hard to close later.
 
Grateful to be in a community of operators who are helping make sense of the GTM foundations, what is working on the "field" and how to manage this transition into the AI-era. 

Some of my good friends Elizabeth McCalley.eth 🦋, Koen Stam 🐰 Jen Igartua, Stephanie Valenti, Steph Reck ⚓, Dale Zwizinski, Sophie Buonassisi ,Sarah Allen-Short, Kiva Kolstein 
 
Strong company to be in.
 
If you're building GTM for 2026, make sure you to follow these great leaders and tell us what is on your mind.

EVP @ Experity | AI-Native GTM Architect | Revenue Nervous System™ | Care Agent | Healthcare AI

Anthropic published new research last week that should change how every GTM leader thinks about their headcount plan.
 
Not "AI might affect jobs someday." Right now. Today.
 
The paper introduces something called "Observed Exposure" 

Combining what LLMs can actually do with how Claude is being used in real work, weighted toward tasks that can be automated. 

Then mapping that against what specific jobs require people to do all day.
 
The GTM numbers:
 
→ Customer service reps: 70.1% AI exposure 
→ Market research analysts: 64.8% 
→ Sales reps: 62.8%
 
That's not theoretical capability. 

That's real-world deployment, mapped against what sales reps actually do all day. Today.
 
But here's the part nobody's talking about.
 
For computer and math roles, AI theoretically can handle 94% of tasks. 

Real-world observed deployment? 33%. That's a 61-point gap sitting there, untapped.
 
That 61-point gap belongs to someone. 

The question is whether you're the one closing it or the one getting closed on.
 
There's another finding buried in the BLS data overlay: for every 10 percentage point increase in AI exposure, employment in that occupation is projected to grow 0.6 points less through 2034.
 
Sounds small. Run it across your entire revenue org and it isn't.
 
But here's what actually surprised me: companies aren't doing layoffs. 

They're doing something quieter. Not backfilling roles. Not approving the next SDR class. 

Running the same RevOps team for three years instead of growing it. 

Letting attrition do the work that announcements would make public.
 
That's how structural labor market shifts actually happen. Not with a headline. With a headcount plan that never gets approved.
  
The GTM leaders getting ahead of this aren't asking "can AI help my team be more productive?" 

They're asking: "What does this role need to look like if AI handles [X] at scale?"
 
Different question. Different answer.

Most GTM awards celebrate the big number.
 
The quarter you 3x'd pipeline. The campaign that went viral. The deal that saved the year.
 
But here's the thing nobody talks about — big numbers built on shaky systems don't compound. They collapse.
 
I've watched it happen more times than I can count across 21+ years of scaling companies. A team absolutely crushes a quarter, leadership throws a party, and six months later they're trying to figure out why the machine stopped working. 

Turns out there was no machine. Just a bunch of really talented people grinding really hard.
 
That's exactly why I'm proud to be on the judging panel for the Winning by Design Growth Awards at Impact Summit 2026.
 
Because this isn't that kind of award.
 
Three categories. Each one matters.
 
→ 𝗕𝗼𝘄𝘁𝗶𝗲 𝗳𝗼𝗿 𝗚𝗿𝗼𝘄𝘁𝗵 𝗠𝗼𝗺𝗲𝗻𝘁𝘂𝗺 — recognizes leaders who've built across the full customer journey. Acquisition, onboarding, retention, expansion. Not optimized one piece while the rest leaks.
 
→ 𝗦𝗣𝗜𝗖𝗘𝗗 𝗳𝗼𝗿 𝗚𝗿𝗼𝘄𝘁𝗵 𝗔𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗶𝗼𝗻 — for operators who've made their teams faster 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 making them sloppier. Velocity from alignment, not from pressure.
 
→ 𝗔𝗜 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗼𝗿 — this one's close to my heart. Not for teams that "use AI." For leaders who've embedded it into the operating logic of how they grow. AI with intent, not AI as a checkbox.
 
The judges? Jacco van der Kooij. Kyle Norton. Sydney Sloan. Jared Brickman. And me somehow.

Leaders who've actually built and scaled systems at this level.
 
We're not looking for a good story. We want evidence. Before-and-after benchmarks. Real metrics. What actually changed and why it held.
 
𝗡𝗼𝗺𝗶𝗻𝗮𝘁𝗶𝗼𝗻𝘀 𝗰𝗹𝗼𝘀𝗲 𝗠𝗮𝗿𝗰𝗵 𝟭𝟴𝘁𝗵.
 
If you're a GTM leader who's done the hard, quiet, unsexy work of building growth infrastructure that compounds — or you know someone who has — this is for you.
 
Not for the headline. For the system behind it.
 
👉 Link in the comments to nominate.
 
Who in your network has built growth the 𝘳𝘪𝘨𝘩𝘵 way this year? Tag them below — they deserve the recognition.

Google's VP of Startups just said the quiet part out loud.

LLM wrappers and AI aggregators have their "check engine light" on.

I've been saying this for months. But hearing Darren Mowry from Google Cloud put it that bluntly? That hits different.

Here's what he means: if your entire AI startup is a nice UI sitting on top of GPT or Claude, you're toast. 

The model providers are coming for your lunch. They always were.

The startups that survive? They have vertical depth. 

Cursor doesn't just "use" AI—it understands how developers actually write code. 

Harvey AI doesn't just "chat"—it knows how law firms think about case research.

I've spent the last year building AI-native GTM systems. Not wrappers. Not aggregators. Systems where AI agents run actual operations—prospecting, content, competitive intelligence, pipeline management.

And the difference is night and day.

A wrapper adds a step. An operations-native system removes twelve.

The moat was never the model. It was never the prompt engineering. It's the workflow. 

It's understanding—really understanding—how a specific type of work actually gets done, and then building intelligence into that process.

After 21+ years of scaling operations, I can tell you: this is the same pattern every technology wave follows. The shiny demo phase dies. The "actually runs my business" phase lives.

We're entering that second phase right now.

If you're building on AI, ask yourself: would your product survive if the underlying model got 10x better and the provider launched their own version of your feature?

If the answer is no, that check engine light is for you.

The opportunity is massive for the builders of agents in back office, GTM and may other places in business. 

Gonna be a fun next couple of years! 

Let’s cook! 👨‍🍳

A common question I get: "what is the difference between a Skill and an Agent?" 

I have built 80+ AI agents for Business across GTM, Product, Engineering, etc. 

I built a guide to help - comment and I will send it to you.. ok back to the program..
 
Agents are like employees in departments: Sales, Marketing, CS. 

Vertical. Domain-specific. They own a function and make decisions.
 
Skills are like apps those employees use: horizontal, reusable across departments, any agent can pick them up.
 
Tools let agents act. 

Skills provide the knowledge of how and when to act: including your company-specific context.
 
That last part is the whole game.
 
Because raw capability is not competence.
 
Your AI can call APIs, analyze data, generate content, and orchestrate workflows. 

That's capability. 

But does it know your team's specific 8-step deal qualification process? 

Does it know anything over $50K hits Deal Desk? 

Does it know the naming conventions, the approval chains, the compliance requirements?
 
That's competence. And that's what skills provide.
 
The architecture is elegant:
 
• Agents carry full context constantly (expensive, bloated)
• Skills load progressively — metadata at startup (~100 tokens), full instructions when activated, resources only when needed
• One skill serves many agents
• Agents call skills. Skills can invoke agents. Bidirectional.
 
No single agent carries all that procedural knowledge. They just know what skills exist and call them when needed.
 
If you're building simple bots, tools are enough. 

If you're building digital employees, you need skills. 

The bottleneck is never whether the agent can perform an action. 

It's whether the agent knows YOUR specific process for performing it correctly.
 
Agents are the who. Skills are the how.
 
Stop building capable agents. Start building competent ones.
 
What's the biggest gap between what your AI agents can do and what they actually do well? Drop it below.

I am finding it pretty easy these days to keep up with everything changing in AI, Business and GTM....

HAY? (How About You - Not sure if that is a shorthand or not, but that's all my kids talk in these days)..

What Cassie Young said! 

When she talks you should 👂! 👇

Partner at Primary Venture Partners, Seasoned Enterprise CRO/CCO

🌶️🌶️ CROs, there's a GTM reckoning coming for the board room. Your board members are done rewarding your AI experimentation efforts.🌶️🌶️

The efficiency gains of the last two years were a half-truth. Sure, you trimmed the fat, but the GTM engine has been atrophying for most companies.
Here's the cold hard truth: GTM inefficiencies used to hide behind 80% SaaS margins but in the age of AI, there is nowhere left to hide. As AI compute costs eat into gross margins, you can no longer afford higher operating expenses.

In 2026 Boards will stop rewarding AI experimentation and start demanding P&L impact through the PRIME framework:
⚙️ Productivity: Is ARR/revenue per GTM head actually climbing?
📈 Retention: Are AI investments moving the needle on GRR/NRR?
💲 Investment Efficiency: Why is CAC payback still stuck at ~16 months?
🪴 Momentum: Is growth predictable and coming from a healthy mix of new and existing?
⬇️ Expense Reduction: Have you actually eliminated labor or software costs?

Most CROs use AI for "marginal gains"—better meeting summaries or slightly faster cycle times. That won't save your P&L. The winners are thinking transformationally:

🟢 Jeanne DeWitt Grosser's team at Vercel replaced a 10-person inbound SDR team with one "Lead Agent"
🟢 Kyle Norton's team at Owner.com 2x'ed productivity per rep with their AI operating system
🟢 Matt Braley’s team at EliseAI had three AEs close $50M in new ARR by supercharging their talent with AI infrastructure
🟢 Amanda Kahlow and the 1mind team use the same AI Superhumans they sell to fuel their own growth, comfortably surpassing the age-old T2D3 growth thresholds with a <6-month CAC payback

PRIME has become our non-negotiable for GTM investing, and it needs to be yours for GTM operating. Are you ready to be held accountable for the P&L? 👀👀

This is a great group of GTM leaders to follow! 

Do it and you won’t regret all the knowledge that is dropped 👇

GTM Leaders to Follow in 2026 🌟

Go-To-Market today is more than a playbook; it’s coordination, clarity, and constant iteration.

The leaders on this list are the ones building adaptive systems that align product, sales, marketing, and success around revenue momentum. They think in experiments, customer segments, and long-term, compounding motions.

Swipe through to explore the list, and follow these operators for grounded insights on winning in competitive, noisy markets.

Check them out 👇

Dale Zwizinski, Sophie Buonassisi, Sarah Allen-Short, Andrew Ettinger, Steph Reck, Joshua Bruton, Alice Wyatt, Sonali S., Stephanie Valenti, Beau Brooks, Matt Schalsey, Jessica Kao, Joon Choi, Alex Richards, Kiva Kolstein, Jonathan Moss, Jen Igartua, Koen Stam, Marcus Bening, Elizabeth McCalley.eth

GTM Leaders to Follow

What would you attempt to do if you knew you would not fail?

Important question to ask yourself especially with all the opportunity right now. 

State your goal, go achieve it. 

Regardless of the outcome you have succeeded. 

The outcome is always learning, experience, connections, and many things you would have never accomplished without going for it.

Enterprise AI adoption just jumped 7x in a single quarter.
 
Not 7%. Seven times.
 
JPMorgan Chase is producing investment banking decks with AI agents in 30 seconds. 

BMW is running multi-agent systems across manufacturing plants—not as a pilot. In production.
 
The chatbot era is over. Most people just haven't noticed yet.
 
Multi-agent setups handling competitive intel, content, pipeline research, and prospect analysis—coordinated, not siloed. 

And here's the thing nobody talks about in the breathless coverage:
 
The hardest part has never been the technology.
 
It's always the humans.
 
A YC startup called Trace just raised $3M on exactly this insight. Their data shows 2-3x higher agent utilization when teams design the human-AI handoff intentionally.
 
I've seen this same movie. CRM. Marketing automation. Cloud. Analytics. 

The tech always works. The org is always the bottleneck.
 
Three things I've learned the hard way building these systems:
 
→ Start with the workflow, not the tool. Map the actual process step-by-step. Find where a human adds the least value. That's where your agent goes.
 
→ Graduated autonomy is mandatory. Draft before publish. Recommend before decide. Flag before act. The leash gets longer as trust builds. Skip this step and you break things. (Ask me how I know.)
 
→ The real metric isn't task completion. It's time-to-decision. My agent system doesn't replace strategic analysis—it eliminates the 4-6 hours of research that used to happen before the analysis. The human still decides. Just faster, with better inputs.
 
Gartner says 40% of enterprise apps will have embedded AI agents by end of 2026. 

In September 2025, that number was 5%.
 
The companies that spent 2025 experimenting are now operationalizing. 

The companies that spent 2025 watching are now scrambling.
 
That gap compounds every quarter.
 
What's your first workflow you'd hand to an agent?

Your org chart is about to become irrelevant.
 
Not because AI is "replacing jobs." Because it's dissolving the reason departments exist in the first place.
 
Anthropic just launched Agent Teams—multiple AI agents that coordinate autonomously, share context, and divide complex work without a human managing every handoff.
 
Everyone's covering it as an engineering story. They're missing the bigger picture.
 
This is a GTM story. And it changes how revenue organizations get built.
 
For 100 years, we've organized companies around functional expertise. 
 
But that structure was designed for a world where humans were the only source of specialized execution. 

When the only way to get competitive analysis done was to hire someone who does competitive analysis.
 
That world ended last week.
 
What agent teams actually enable is a shift from organizing around WHO has the skills to organizing around WHAT work needs to happen.
 
Microsoft calls it the shift from "org charts" to "work charts."
 
I call it the jobs-to-be-done model for organizational design.
 
Here's how the work actually splits:
 
𝗝𝗼𝗯𝘀 𝗮𝗴𝗲𝗻𝘁𝘀 𝗳𝗶𝗹𝗹 → Data assembly and enrichment. Pattern recognition across thousands of interactions. First-draft content creation. Coordination and handoff management. Continuous competitive monitoring.
 
The execution layer. The coordination layer. The stuff humans are slow and inconsistent at doing across scale.
 
𝗝𝗼𝗯𝘀 𝗵𝘂𝗺𝗮𝗻𝘀 𝗼𝘄𝗻 → Strategic judgment calls. Relationship architecture. Creative vision. Ethical guardrails and edge cases. And the meta-job—deciding which work goes to agents and which stays human.
 
The judgment layer. The trust layer. The stuff that requires experience, intuition, and the ability to read a room.
 
That's not "humans vs. AI."
 
That's a work chart. Jobs to be done, assigned to whoever—or whatever—does them best.
 
The pattern is consistent. Companies reorganizing around agent-augmented work are collapsing departments that existed primarily to manage coordination overhead.
 
Think about your GTM org today. How much of your headcount exists to coordinate between functions rather than create value?
 
Agent teams don't need alignment meetings. They share context natively. 

They don't lose the thread between marketing's campaign intent and sales' first outreach. 

They don't need a three-week runway to align five departments on a product launch.
 
The companies that win in 2026 won't just "use AI tools."
 
They'll have structurally different organizations. Fewer silos. More outcome-oriented teams. Agents handling execution and coordination. Humans concentrated where judgment, creativity, and relationships drive outcomes.
 
The question isn't "should we adopt AI agents?"
 
It's "which boxes on our org chart exist because the work demands them—and which exist because that's just how we've always organized?"
 
That's the uncomfortable one.

Experity

Forum Member

Winning by Design

Pavilion

Advisory Council Member

Let's go!! This could be a once in a lifetime opportunity for someone to help us disrupt healthcare and the way patients engage it today. You don't want to miss the opportunity!

We’re #hiring.

#Healthcare has lived too long with patient experiences that feel dated and transactional. We’re building something different, a modern, AI-native Care Agent that helps clinics respond faster, communicate better, and reduce friction for patients. It’s already live in 2,000+ clinics, handling nearly a million patient conversations each month, so this is real-world impact at real scale.

We’re looking for a Software Engineer - Technical Lead for our Care Agent solution to help take the next leap in transformation. You’ll drive technical delivery and raise the bar on quality, reliability, and speed of learning, while working in a modern stack (Node.js, TypeScript, Next.js, AWS Bedrock AgentCore).

Direct hire only, no agencies.
Apply here: https://lnkd.in/eq5Pm2PX

Want to be considered?
* Apply (link above)
* Please do not message me directly

Ask someone we both know to send me an intro with your resume

Be ready for: Why this problem, how are you using AI today, what impact can you make here

#Engineering #HealthcareAI #SaaS #TechLeadership #Innovation

Know anyone who might be interested?

AI has changed from a chat back and forth to a coworker.. catch up on everything that happened this week 👇

Open article: The Week AI Became Your Coworker by open.substack.com

View newsletter: GTM AI Podcast & Newsletter

Open article: 3/6/26: This Founder Tried Every AI SDR. They All Failed. What He Built Instead Converts at 90% Open Rates. by Jonathan M Kvarfordt, MBA • 4 min read

3/6/26: This Founder Tried Every AI SDR. They All Failed. What He Built Instead Converts at 90% Open Rates.

IYKYK - you just need a microphone and this new keyboard.

taplio

The Battle

Dale Zwizinski

Jonathan Moss

Followers

Posts

Engagements

Likes

Performance ScoreDale Zwizinski's LinkedIn Performance

Performance ScoreJonathan Moss's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Dale Zwizinski

Jonathan Moss

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Dale Zwizinski's LinkedIn Performance

Performance ScoreJonathan Moss's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreDale Zwizinski's LinkedIn Performance