Ryan Staley

Whale Boss

A New Era of Revenue Leadership with AI 

Our mission is to empower 1 million Go-To-Market Executives to achieve superhuman potential through AI transformation. We help revenue leaders escape the operational grind, multiply team capacity, and accelerate revenue—all while working less and achieving more.  This can be done in less than 2 months with AI education activation, innovation and automation. 

🚀 AI as “Liberating Intelligence”
AI isn’t just a tool; it’s “liberating intelligence.” This shift redefines productivity, ambition, and control, enabling leaders and teams to reach impact levels once unimaginable—all without expanding headcount. This approach resonates with executives who seek freedom in both business and life, making AI a true transformational ally.

🔹 From Productivity to “Capacity Multiplication”
Today’s leaders don’t need mere productivity boosts; they need to multiply team capacity. AI agents, workflows, and assistants go beyond task completion, amplifying output so teams perform at peak levels without constant oversight—giving leaders time for moves that truly matter.

🌄 Liberating Leaders to Live the Dream, Not Chase It
With AI, revenue leaders can grow without the endless grind. Freed from perpetual hiring and micromanagement, you gain the power to step back, letting a self-sustaining revenue engine deliver results while you live the life you envision.

💡 AI for “Decision Density”: Minimize Decisions, Maximize Impact
AI reduces the mental load by taking on real-time tactical choices, freeing leaders to focus on fewer, high-impact decisions. It turns decision-making from a draining process into strategic momentum.

I’m passionate about helping revenue leaders not just transform their teams but redefine growth itself. 

Together, we’re building a future where AI isn’t just helpful—it’s liberating.

Founder and CEO

The Scale Up Show

I deconstruct how the top SAAS CEOs in the world grow their companies repeatedly and predictably.  

This show has featured Startup and Billion Dollar Founders, Best Selling Authors, and the World’s Top Sales and Marketing Experts like Terry Jones (Founder of Travelocity and Chairman of Kayak),  Andrew Gazdecki (Founder of Microacquire), Harpaul Sambhi (Founder of Magical with a previous exit to Linkedin) and many more.

Podcast Host

Gartner

Gartner Peer Community is Gartner's new, next-generation online destination designed to increase value through timely answers and meaningful peer connections.

Ryan Staley has been invited as a Founding Peer Community Ambassador to contribute insights on B2B sales, sales leadership, and enterprise go-to-market among other topics. Gartner Peer Community is Gartner's new, next-generation online destination designed to increase value through timely answers and meaningful peer connections. 

Ryan Staley has been invited as a Founding Peer Community Ambassador to contribute insights on B2B sales, AI for Sales, sales leadership, and enterprise go-to-market among other topics.

Peer Ambassador: B2B Sales, Sales Leadership & Enterprise GTM

Pavilion

As an instructor, I have taught over 800 VPs of Sales and CROs my proprietary methods for Enterprise Sales and Enterprise GTM.  

Pavilion is a private, invitation-only community of sales and marketing executives at growth-focused companies.

Executive Member,  Former CRO & Enterprise Sales GTM School Lecturer

RevGenius

RevGenius is a think tank networking group of revenue-generating sales and marketing professionals brought together to learn, share, support, and grow with each other. You can consider us your alt work family!

Founding Member

Sales Hacker, Inc.

Flex Technology Group

Specific examples of value delivered for net new customers listed below;

-Leading Retail Company ($15 billion in annual revenue)-$3.6 Million in expense reduction over the life of contract, 15 FTE's freed up for core IT initiatives and 300% improvement in SLA's

-High Growth Manufacturer ($9 Billion in annual revenue)-$1.8 Million in expense reduction over the life of contract, 300% improvement in SLA's and 15 vendors consolidated into 1.

-Leading National Healthcare Provider ($2.5 Billion in annual revenue)- $3.6 Million in expense reduction over the life of contract, SLA improvement of 400% and  Co-authored enhanced asset management strategy

-Top Professional Services Organization ($3 Billion in annual revenue)- 60% expense reduction, SLA improvement of 300% and asset management visibility provided across 900 locations

Vice President of Strategic Accounts

Director of Strategic Accounts

Director of Sales, Midwest Region

Regional Sales Manager

Pitney Bowes (Managed Services)

Managed Print Services Enterprise Sales (Midwest Region) for Fortune 500 and Fortune 1000 organizations.

Senior Sales Consultant

Antenna Software

Antenna is a high growth early stage Software company that provides a SaaS based applications and mobility platforms that allow Fortune 500 companies to mobilize their enterprise applications.

• Responsible for Direct and Channel Sales for the Region
• Developed new Partner/Customer relationships for an
   undeveloped territory

Director of Sales Midwest Region

Sold customized Managed Print Services and software solutions to Fortune 500 and Fortune 1000 C-level executives. 

• President's Club Winner 2004, 2005, 2006, and 2007
• Grew a new market that had no customers into the one of
   the most profitable sales markets.

I help Chief Revenue Officers & Sales Professionals Leverage AI to work 10 hours less weekly and 2x performance. Follow for cutting-edge cheat codes, prompts, and workflows🎙Scale Up Show Host🔥$0→$30M ARR in 5.5 yrs

Over the last decade, I’ve grown a division from 0-$30M ARR with 4 Sales People and have upskilled over 1,600 GTM executives on AI, Enterprise Sales and GTM Strategy  .

My mission is to inspire 1 million Go To Market Executives to work less and sell more through becoming Superhuman with Artificial Intelligence.

I help revenue leaders transform their teams by acquiring AI skills to escape the operational grind, and accelerate topline revenue.

I’m the founder of Whale Boss and The Scale Up Show.

My portfolio:

→ I’m the Founder of Whale Boss, an AI Sales & Marketing consulting and skill transformation company
→ I’m the Founder of the Scale Up Show, Top 1% Global Podcast
→ I teach Executives, Sales & Marketing teams to implement tools like ChatGPT, Copilot, Claude, etc.   
→ I provide Chief AI Officer Advisory services for human capital.  


My results:

→0-$30M without funding, marketing or SDRs with only 4 Sales people
→Identified and implemented over 500 AI use cases (internally and externally)
→Taught over 800 CROs proprietary selling strategy and tactical execution
→Consulted over 40 Technology companies on custom revenue growth strategies.  
→Voted as a TOP global AI thought leader, Gartner Ambassador & Sales Assembly thought leader. 


If you want to learn more on how to become Superhuman, you can join my newsletter.
⇒ https://superhumanrevenue.beehiiv.com/


If you want to explore AI skill transformation for your organization or Team, apply for an AI Consult.  
=> https://calendly.com/ryanstaleywss/introductory-call-with-ryan-staley-from-whale-boss


Youtube- https://www.youtube.com/channel/UCFGndSHN4KkE89kUP74U7Qg

Podcast-https://ryanstaley.io/podcast/

X-https://x.com/Ryan_Staley1

Just wrapped another CRO roundtable last week in Chicago.
Stellar group. 

The conversation was unfiltered, insightful, and honestly pretty intense.


Here's what's actually keeping revenue leaders up at night:
1. Misaligned Expectations with the Board

Targets keep rising while market conditions keep deteriorating.
The fear isn't about working harder—it's about being held to numbers that completely ignore reality. How do you prove success when the metrics everyone's watching don't actually reflect what's happening in the business?




2. The AI Shock + Everything Changing at Once

Technology, GTM motions, buyer behavior, AI capabilities, org structure—all shifting simultaneously.

Without a clear framework, every change feels like risk instead of opportunity.

The real issue? Separating AI hype from actual impact before you waste time and credibility chasing vaporware.



3. Tech Stack Evolution vs. Human Adoption

The stack evolves faster than behavior, process, and culture ever will.
You've got increasingly sophisticated tools and data while revenue outcomes lag miles behind. The gap isn't closing—it's widening.



4. Margin and Pricing Pressure
Competitors are cutting price aggressively, creating massive pressure to follow.

Leaders are stuck protecting brand value and economics while discount pressure builds every single quarter. Race to the bottom or hold the line?



5. Comp Plans, Metrics, and Governance

Designing effective comp plans is brutal when GTM motions shift and turnover stays high.

Which metrics actually matter versus which ones just look good in board decks? How do you create incentive alignment when ownership across GTM is still fuzzy?


6. Cross-Functional GTM at Scale

Scaling Sales, CS, Product, and Marketing requires a unified operating model.

At hyper-scale, collaboration collapses into silos. Everyone wants a single customer journey—until it requires giving up their kingdom.



7. Talent and Ramp Reality
Ramping and retaining top reps in this environment is harder than ever.
The challenge? Distinguishing true high performers from strong interviewers. And balancing L&D investment against the reality of high turnover.



8. CRO Role Clarity and Org Design

When do you actually need a CRO versus a Head of Sales?

The difference is structural and political, not just a title change. Position the role wrong in the leadership architecture and it becomes friction instead of leverage.

Which of these 8 is hitting hardest for you right now?

Huge thank you to Warren Zenna to hosting

Also it was an amazing group and great to see Daniel Frailey Guy Rubin Greg Leos Howard Diamond Elio Narciso Marc Sabatini Jason A Wankovsky  James Kaikis

Founder & CEO, Whale Boss | Demystifying AI Agents | Helping revenue leaders 2x team results through AI Led GTM | Trusted by PE-backed SaaS | Transform your team in 60 days

I've learned more about life than I ever had this year, so I wrote down 20 things I know at 48 that I wish I knew at 28.

This is straight from the heart.



1. Working as an employee trains you to ask for permission. Working as a founder trains you to take action because your life depends on it.

2. Every 10 years, there was a technology evolution that I ignored because I was too busy. I missed the internet explosion (in early 2000), Mobile and Social (2008-2011), and Bitcoin (2015 at $230 vs. $100K+ now). I am not doing the same with AI.

3. I used to be massively afraid of failing; things had to be perfect. However, my most painful failures pushed me to do things that I never would have dreamed of.

4. Without some separation of work from relationships, health, and fun, life can seem empty when work doesn’t meet your expectations.

5. The biggest risk to an achiever with a hard work ethic is burnout. Recovery (in whatever form you need) is sometimes better than working an extra 5-10 hours weekly.

6. It’s better to have 2-3 amazingly loyal friends you can count on rather than 15 that are mediocre.

7. Lack of focus on your own can be just as paralyzing as a job you hate.

8. You can learn anything, but you don’t have time to learn everything.

9. Nobody has all the answers, and the fastest way to evolve is to do rather than passively watching LinkedIn, YouTube, taking courses, reading books, etc.

10. If you don’t make a plan for your life, you will live within the confines of someone else’s plan.

11. I appreciate my parents way more now because I have to parent and realize how hard they worked to give me an amazing life.

12. If you help others unselfishly, it always comes back to you, whether it be a day, a month, or years later.

13. God, the universe, or whatever you believe in will often guide you in simple ways if you just ask for it and allow for grace.

14. Daily focus on gratitude will transform who you are and your view of the world if you make space for it.

15. Alcohol doesn’t need to be a big part of your life to fit into social situations.

16. Your biggest breakthroughs will happen unexpectedly after you relentlessly work to improve through massive action.

17. Every person on this earth has a unique path that no one else has ever had. Take that experience and do the best you can with your unique gifts.

18. Focus is the biggest barrier you will face when AI makes custom knowledge free.

19. Your children will bring you joy that you can’t comprehend at 28.

20. If you take care of yourself physically, mentally and psychologically you won’t feel old.

That's all for now! I am sure more will come to me for a post 2 on this:)

Every company says they're "doing AI." Few are actually seeing results.

Why? They're treating AI like a 2-year R&D project when it should be a 60-day transformation.

━━━━━━━━━━━━━━━━━

THE TYPICAL APPROACH (That Fails):

Months 1-6: Form committees, evaluate vendors
Months 7-12: Run pilots, "gather learnings"
Months 13-24: More pilots, maybe deploy something

Result: $500K spent, 2 years wasted, no impact

━━━━━━━━━━━━━━━━━

THE 60-DAY APPROACH (That Works):

Weeks 1-2: Pick ONE process, automate it, show immediate results
Weeks 3-4: Expand to 3 more processes, train team
Weeks 5-6: Connect to existing systems, measure everything
Weeks 7-8: Deploy revenue-generating applications

Result: $35K investment, 60 days, measurable ROI

━━━━━━━━━━━━━━━━━

WHY MOST FAIL:

- Analysis paralysis: Studying instead of using
 Boiling the ocean: Too many initiatives at once
 No quick wins: Team loses interest

━━━━━━━━━━━━━━━━━

THE ANTI-HYPE RULES:

1. Ship to production in Week 1 (not pilots)
2. One process at a time
3. Measure hours saved, not AI maturity
4. If it takes >60 days, you're doing it wrong

━━━━━━━━━━━━━━━━━

REAL EXAMPLE: $300M ARR Company

Day 1: Identified pain point (meeting prep), trained 30 reps
Day 14: 4.5 hrs/rep/week saved
Day 30: Expanded to email, research, CRM
Day 60: 300 hrs/week saved, pipeline up 20%, win rate up 6%

Investment: $35K | ROI: 400%+ in 90 days

━━━━━━━━━━━━━━━━━

THE BOTTOM LINE:

Stop planning AI. Start shipping AI.

60 days. Not 2 years.

━━━━━━━━━━━━━━━━━

Is your AI transformation taking too long?

whale-boss

li_at

JSESSIONID

Talks about #gtm, #sales, #chatgpt, #entrepreneurship, and #artificialintelligence

95% of executives are missing GPT-5's true potential.


WHEN I see people using GPT-5 like ChatGPT 4o...

WHAT I really see is millions in missed opportunities.

I just cracked GPT-5's three game-changing features that separate winners from wannabes:

Feature #1: 

The "Rival Intelligence" Framework ⚡ → Single prompt = 5 expert perspectives instantly → Customer + Shareholder + Employee + Competitor + Regulator analysis → I fed it Shopify's leaked AI memo - got strategic recommendations in 30 seconds


Feature #2: 

Your Data = Your Competitive Moat 🎯 → Connect HubSpot, Google Drive, Box directly to GPT-5 → Extract client dreams, fears, frustrations from 90 days of data → Generate personalized scripts + strategies from YOUR actual conversations


Feature #3: 

Agentic Workflow Mastery 🚀 → "Single-pass" prompting = no more back-and-forth → Deep market recon + strategy + execution in ONE prompt → Think strategic consulting team, not search engine


HOW to implement today:

Challenge Current Thinking: Use rival perspectives on your biggest decision

Mine Your Gold: Connect your CRM and ask for pattern analysis

Go Agentic: Create workflows that think 5 steps ahead

I'VE tested this with 2,500+ executives.

The results? Superhuman decision-making in seconds.

Most leaders are playing checkers with AI.

Smart ones are playing 4D chess.

Which game are you playing? 👇

Download The Ultimate GPT-5 Go-To-Market Prompting Toolkit: 
Profile link

Gpt 5 not Gpt 4

4 hours of GTM work → 15 minutes. Same outcome. ~2x quality.
Here’s what one AI workflow did for me last week:


The workflow (all in a single thread):

-Follow-up email with clear actions for the prospect.
-Deal coaching on how qualified it was through MEDDICC-style criteria.
-Next best actions based on my notes and pipeline context.
-Full proposal in my branding, with all the details tightened up.


🔥 Total time: ~15 minutes.

Old way: 3–4 hours of deep work.

Quality: better structure, cleaner narrative, stronger visuals than if I white-knuckled it myself.


This is why I think we need a new standard for AI ROI.

Not “I paid $100 for licenses, where’s my $40K?”


But:
Hours collapsed per workflow
Quality lift vs manual
Capacity unlocked per rep per week


The beautiful thing about it was that it wasn’t a complex Agent build.

It was a stacked workflow of 2 tools.


Those are the leading indicators that create the compounding ROI later.


Question for you: Where in your GTM motion would a “4 hours → 15 minutes” shift change the quarter?

$1.5 Trillion invested in AI in 2025.

90% of enterprises see ZERO impact on EBIT.

Let me say that again:

90% see no bottom-line impact.

Despite trillions invested.

Here's why (and what to do differently):

━━━━━━━━━━━━━━━━━

**THE PARADOX:**

What's happening:
→ 92% plan to increase AI investment
→ 70%+ have integrated AI into at least one function
→ AI is everywhere in the enterprise

What's NOT happening:
→ Revenue growth from AI
→ Profit margin improvement
→ Bottom-line impact

The question everyone's avoiding:

Where's the ROI?

━━━━━━━━━━━━━━━━━

THE 3 FAILURE MODES:

1. Pilot Purgatory

Companies run 47 AI pilots.

None reach production.

Why? They're always "testing."

2. The Integration Gap

AI tools purchased.

Can't access company data.

Sit unused. Money wasted.

3. Time to Value Problem

Implementation takes 6+ months.

People lose interest.

Tools abandoned before impact.

━━━━━━━━━━━━━━━━━

REAL DATA FROM MY CLIENTS:

Companies that SEE ROI:
→ Implementation in <60 days
→ Focus on 2-3 use cases max
→ Measure impact weekly
→ Result: 2x productivity, 10-20% revenue lift

Companies that DON'T see ROI:
→ Implementation in 6+ months
→ Try to boil the ocean (10+ use cases)
→ Measure impact quarterly (or never)
→ Result: Wasted investment, team burnout

━━━━━━━━━━━━━━━━━

THE "TIME TO VALUE" FRAMEWORK:

If people don't see results in 2 weeks, they quit.

Here's how to beat that:

Week 1:
→ Pick ONE painful process
→ Implement ONE AI solution
→ Show immediate time savings

**Week 2:**
→ Quantify the impact
→ Share wins widely
→ Build momentum

**Week 3-4:**
→ Scale what worked
→ Add ONE more use case
→ Repeat

**Result:**
→ Fast wins compound
→ Adoption spreads organically
→ Bottom-line impact in 90 days (not never)

━━━━━━━━━━━━━━━━━

**THE BOTTOM LINE:**

The $1.5 Trillion AI investment paradox isn't about bad technology.

It's about bad implementation.

**Fix these 3 things:**

1. Get out of pilot purgatory (ship to production)
2. Solve integration FIRST (data access is everything)
3. Deliver value in weeks, not quarters

Do that?

You'll be in the 10% that actually sees ROI.

━━━━━━━━━━━━━━━━━

Are you seeing AI ROI at your company?

Or are you stuck in pilot purgatory?

Comment below. 👇

It took me 10 years to learn how to qualify deals effectively.

AI can do it in 3 questions.

With 95% accuracy.

Here's how:

━━━━━━━━━━━━━━━━━

THE OLD WAY:

Years 1-3: Learn your product inside out
Years 4-6: Understand your market deeply
Years 7-10: Master pattern recognition

Result: Expert intuition about which deals will close

Time investment: 10 years

━━━━━━━━━━━━━━━━━

THE NEW WAY:

3 Questions to AI:

Question 1:
"Based on our last 100 won deals, what are the top 5 characteristics that predict a win?"

Question 2:
"Analyze this new opportunity: [paste deal details]. How does it compare to our ideal customer profile based on actual wins?"

Question 3:
"What are the 3 biggest red flags from our lost deals that appear in this opportunity?"

Result: Data-driven qualification in 5 minutes

Accuracy: 95%+ (tested against actual outcomes)

━━━━━━━━━━━━━━━━━

WHY THIS WORKS:

Human intuition:
→ Based on maybe 50-100 deals you remember
→ Influenced by recency bias
→ Misses subtle patterns

AI analysis:
→ Based on ALL your historical deals
→ No bias, just patterns
→ Sees correlations humans miss

━━━━━━━━━━━━━━━━━

REAL EXAMPLE:

Sales rep brought me a "perfect" opportunity:

Human intuition said:
→ Great fit company
→ Budget approved
→ Timeline makes sense
→ "This is closing for sure"

AI analysis revealed:
→ Company size matches lost deals (not won deals)
→ Title of decision maker is different than usual champions
→ Deal velocity is 2x slower than typical wins
→ Missing 3 key buying triggers from successful deals

Recommendation: Deprioritize

Outcome: Deal stalled at 120 days, never closed

AI was right. Human intuition was wrong.

Every company says they're "doing AI." Few are actually seeing results.

Why? They're treating AI like a 2-year R&D project when it should be a 60-day transformation.

━━━━━━━━━━━━━━━━━

THE TYPICAL APPROACH (That Fails):

Months 1-6: Form committees, evaluate vendors
Months 7-12: Run pilots, "gather learnings"
Months 13-24: More pilots, maybe deploy something

Result: $500K spent, 2 years wasted, no impact

━━━━━━━━━━━━━━━━━

THE 60-DAY APPROACH (That Works):

Weeks 1-2: Pick ONE process, automate it, show immediate results
Weeks 3-4: Expand to 3 more processes, train team
Weeks 5-6: Connect to existing systems, measure everything
Weeks 7-8: Deploy revenue-generating applications

Result: $35K investment, 60 days, measurable ROI
━━━━━━━━━━━━━━━━━

WHY MOST FAIL:

- Analysis paralysis: Studying instead of using
 Boiling the ocean: Too many initiatives at once
 No quick wins: Team loses interest
━━━━━━━━━━━━━━━━━

THE ANTI-HYPE RULES:
1. Ship to production in Week 1 (not pilots)
2. One process at a time
3. Measure hours saved, not AI maturity
4. If it takes >60 days, you're doing it wrong
━━━━━━━━━━━━━━━━━

It-took-me-10-years-to-learn-how-to-qualify-deals-effectively.pdf

Google Just Opened a 90-Day Competitive Window
Most businesses will miss it entirely.


I've watched this pattern for 3 years across 2,500+ executives:


Early movers capture 12-18 months of market advantage. Hesitators spend years catching up.


It's happening again. Right now.


The Tests That Matter
I spent 48 hours stress-testing Gemini 3 on real business scenarios:
Sales Prep: 

3 hours → 10 minutes (same quality, better output) 

Website Build: 3 weeks → 63 seconds (921 lines of functional code) 
Analytics Dashboard: 2 weeks → minutes (production-ready)

Zero exaggeration. I recorded everything.


The Business Math

Your team of 50 can now perform like 60-75. 
Your content velocity increases 5-10×. 
Your decision speed accelerates 10-20×.


Same headcount. Same budget. Different results.


Your 3-Stage Play
Days 1-30: Individual team members test on daily tasks (10-20% time savings) 
Days 31-60: Scale across departments (30-40% capacity increase) 
Days 61-90: AI-first workflows deployed (50%+ multiplication)

NOTE: After 90 days, this becomes table stakes. The advantage window closes.

The Split Happening Now
Group A: Testing this week, implementing next week, scaling by month-end Group B: "Monitoring the situation"
Group A dominates their markets by Q2 2025. Group B explains market share losses to their boards.


Your 7-Day Action Plan


Day 1-2: Identify your highest-value, most time-intensive process 
Day 3-4: Assign your best operator to test Gemini 3 
Day 5: Document time/capacity savings Day 6-7: Scale or course-correct

The Question


You won't get disrupted by AI.

You'll get disrupted by competitors using AI better than you.

Are you testing this week, or "waiting for more information"?

The 90-day clock is ticking ⏰

The GPT-5.1 rumors have my full attention.

What I’m hearing from people who actually know:

→ Not an update. A transformation.
→ Reasoning that makes current models look broken.
→ Speed + pricing that changes everything.


Here’s what happens if this is real:
The gap between AI-first and AI-last companies becomes uncrossable.
Workflows we teach today become obsolete next week.


6-month “AI strategies” get rewritten in 48 hours.


What I’m telling clients:

Don’t wait to “see what happens.”
Build the muscle of rapid AI adoption NOW.


Because if these rumors are accurate, you’ll need it in 3 weeks.


Bottom line:
The curve is about to bend.
Teams ready to move fast will capture 18 months of advantage in 60 days.


Teams still “evaluating” will be explaining to their board why they’re behind.



Which side will you be on?

BREAKING-CLAUDE 4.5 OPUS RELEASE (here's what it actually means)
I've spent 3 years implementing AI for go-to-market teams.   
Here's what I've learned about benchmarks:


Nobody cares about the scores.
They care about what the scores MEAN for their Monday morning.


So let me translate the latest Claude Opus 4.5 results into plain English:


WHAT THE NUMBERS SAY:

Agentic Coding: 80.9% (fixes 4 out of 5 real software bugs)
Tool Use: 98.1% (completes multi-tool tasks reliably)
Scaled Tool Use: 62.3% (orchestrates many tools simultaneously)
Novel Problem Solving: 37.6% (still struggles with truly creative thinking)


WHAT THIS MEANS FOR YOUR TEAM:

🔹 For CROs: Your SDRs spend hours on research before every call. AI can now do that research in 10 minutes with 80%+ accuracy. That's 2-3 extra meetings per AE per week.
🔹 For CMOs: Campaign execution bottlenecks disappear when AI handles reporting, repurposing, and distribution simultaneously. 2X output. Same team.
🔹 For RevOps: Manual CRM updates, forecast modeling, pipeline analysis—AI handles 50%+ of this autonomously now. Your analysts focus on insights, not data entry.


WHAT THIS DOESN'T MEAN:

AI isn't replacing your closers.

The novel problem solving score (37.6%) tells you where humans win: complex negotiations, relationship building, creative strategy.

That number was near 0% two years ago—so the frontier is moving.
But TODAY, the play is clear:


AI handles the mechanics. Humans handle the moments.

The companies I work with aren't debating this anymore.
They're racing to reorganize around it.


How are you thinking about deploying agentic AI this quarter? Drop your use case below—I'll share what's working.

The "Pilot Purgatory" Problem
The traditional software playbook is KILLING your AI ROI.

Here's what I mean:
I've seen dozens of Public, VC, PE-backed companies spend 6-9 months "validating" AI pilots.

By the time they're ready to scale? The technology has already evolved 3 generations.

OpenAI just released data showing they've shipped a new feature every ~3 days this year.


Your quarterly validation cycle can't keep pace with weekly capability improvements.


Here's the uncomfortable truth most consultants won't tell you:
The companies stuck in pilots aren't failing because of technology.


They're failing because they're applying OLD playbooks to NEW capabilities.
🔹 Traditional software: Start small → Test a specific use case → Scale once proven 

🔹 AI implementation: Build learning systems → Iterate in weeks → Scale while improving


The difference?
AI systems don't follow fixed rules. 
They generate outputs based on patterns, data, and context.


Success changes with new inputs.

That means quality and reliability require CONTINUOUS evaluation, feedback, and iteration.


NOT a 6-month pilot program that measures last quarter's metrics.


Here's what I've seen work in 60-day transformations:

Shorter loops (weekly, not quarterly reviews)

Decentralized learning (champions across every team)

Immediate measurement against business outcomes


NOTE: The companies reaching production consistently share one trait—they balance speed with structure and evolve as fast as the technology.



Is your AI strategy moving at the speed of ChatGPT's feature releases, or the speed of your annual planning cycle?

Gemini 3.0 in 3 Minutes: Live website & Dashboard build (INSANE RESULTS)

This one blew me away.  

After playing with this all weekend Google really knocked the cover off the ball.

Turning cold leads into warm leads.

This was a combo of Gemini 🍌and @grok 

The ability to generate an insane scene and then animate it can be done for $60 per month of what would have taken $10,000 in the past in addition.



It can be done from your phone in literally 5 minutes vs a multi-week process.



Insane that this is possible.  And opens up creativity to so many people.

40% of enterprises say they lack internal AI expertise.

This number is about to get worse.

Here's why (and what to do):

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THE SKILLS GAP DATA:

What enterprises need:
→ AI strategy development
→ Prompt engineering expertise
→ AI workflow design
→ Integration architecture
→ Change management for AI

What they have:
→ Traditional IT skills
→ Legacy system knowledge
→ Pre-AI processes
→ No AI-native talent

The gap is widening.

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WHY THE GAP IS GROWING:

Reason 1: AI Skills Are Brand New
→ These roles didn't exist 2 years ago
→ No traditional education path
→ Learn by doing, not by degree

Reason 2: Competition for AI Talent Is Brutal
→ Startups offering $300K+ for AI roles
→ Enterprises can't compete on salary
→ Best talent going to AI-first companies

Reason 3: Skills Evolve Monthly
→ What was cutting-edge 6 months ago is basic now
→ Constant learning required
→ Traditional training programs too slow

━━━━━━━━━━━━━━━━━

THE 3 TYPES OF AI SKILLS NEEDED:

Type 1: Foundational (Everyone needs)
→ AI tool usage (ChatGPT, Claude, etc.)
→ Basic prompting
→ Understanding AI capabilities/limitations

Current gap: 60% of employees lack this

Type 2: Applied (Power users need)
→ Advanced prompting techniques
→ Custom GPT creation
→ Workflow automation
→ AI + existing tools integration

Current gap: 80% of employees lack this

Type 3: Strategic (Leadership needs)
→ AI strategy development
→ ROI calculation
→ Risk assessment
→ Change management

Current gap: 90% of leaders lack this

Does your company have the AI skills it needs?

Or are you in the 40%?

The-Skills-Crisis-A-dollar500K-Problem-With-a-dollar35K-Solution.pdf

A CRO of a Publicly Company told me he'd trade his worst performing salesperson to fund AI transformation.

Not fire a large part of his team because of AI.

Trade the lowest performing person FOR AI.

That conversation revealed something I've now confirmed across hundreds of executive conversations:

The leaders who will win in 2026 aren't thinking about AI as a technology decision.


They're thinking about it as a RESOURCE ALLOCATION decision.

After 3 years and 2,500+ executive AI implementations, here are the 7 beliefs driving their 2026 AI strategies:

1. AI is strategically non-optional—but must be grounded in execution 
🔹 Not a side experiment. Not a pilot. 
🔹 They want AI hardwired into campaigns, daily activities, and systems.


2. Willing to fund AI by reallocating headcount, not adding spend 
🔹 One mid-performing rep = one AI transformation budget. 
🔹 They're in reallocation mode, not expansion mode.


3. Training must be the most relevant enablement they've ever had 
🔹 No theory. No hype. 
🔹 People must leave sessions doing specific things differently TOMORROW.


4. Transformation must be phased and resilient to changing priorities 
🔹 They're notorious for changing direction. 
🔹 Crawl-walk-run beats big-bang every time.


5. Time and change-capacity are the scarcest resources 
🔹 AI work must be time-neutral or time-accretive. 
🔹 It can't feel like "another initiative."


6. AI must compensate for structural underinvestment 
🔹 No dedicated data analysts. Underfunded marketing. 
🔹 AI is the force multiplier that covers the gaps.


7. The AI story must be consistent across sales + marketing + leadership 
🔹 One storyline. One SOW. 
🔹 CFO and CMO must see their words in the program.


NOTE: The bar has changed. Executives will trade headcount for AI—IF it clearly drives daily behavior change and revenue outcomes.


Which of these 7 beliefs resonates most with what you're hearing from leadership?


Struggling to figure this out? 

DM me to see how your peers are tackling this for 26 and beyond.

Save Hours Every Week With This Simple Trick!

I used to spend 10+ hours every week writing marketing content. It was a time sink.


Then I leveraged AI, and my content workflow exploded:

Generated 30 LinkedIn posts in 15 minutes.

Created 12 YouTube video outlines (including SEO/AEO research, thumbnail designs, and full scripts) in the same time.


The best part? Same quality, 95% less time.


This isn't just about speed; it's about shifting your focus from creation to strategy.

The secret is knowing exactly what’s possible with Claude Code (outside of traditional coding). It’s a game-changer for Marketing, Sales, and general Go-to-Market functions.

#AI #ContentMarketing #LinkedInStrategy #Productivity #GoToMarket

Sometimes I think we overcomplicate AI in sales.

Everyone wants the perfect playbook, the secret sauce, the one tool that will magically double revenue.

But the truth is, most of the wins I’ve seen come from small, gritty experiments.

A team tries a new AI-powered lead scoring model. It flops. They tweak it, try again. Suddenly, they’re booking 30% more meetings.

Or a manager uses AI to analyze call recordings. Finds out the top reps ask twice as many questions as everyone else. Next week, the whole team is trying it. Win rates jump.

It’s not glamorous. It’s not always scalable. But it works.

AI isn’t a silver bullet. It’s a thousand little adjustments, stacked up over time.

The teams that win aren’t the ones with the biggest budgets. They’re the ones willing to get their hands dirty, fail fast, and learn faster.

So if your AI project feels messy, you’re probably on the right track.

What’s the smallest experiment that made the biggest impact for your team?

Mixing models? 

 There’s been a lot of different opinions in terms of mixing models however, I’m absolutely blown away that I could create a video like this in five minutes by using nano banana pro 🍌with Grok 4.1 imagine.

I get for standardization purposes of ONLY ONE LLM in large organizations has huge value however, a lot of the large language models are like superheroes that each have their own special superpower.

taplio