I have over 15 years of experience in digital marketing. Throughout my career, I’ve transformed data into actionable insights that drive real business results. My journey has taken me from being a hands-on Digital Marketing Associate to leading teams as a Digital Marketing Manager. Along the way, I’ve developed and executed strategies that consistently improve ROI and foster customer engagement.

At ADvance Media, I spearheaded multi-channel campaigns that increased ROI by 25% and reduced acquisition costs by 10% for enterprise clients. At WHEREHOUSE BEVERAGE CO, I scaled the digital ad budget from $20K to $250K in just six months, delivering a consistent 3x ROI by using advanced targeting techniques and rigorous A/B testing.

Currently, I collaborate with clients as a freelancer to design and execute data-driven marketing strategies. My focus is on performance marketing, e-commerce growth, and customer acquisition. One notable project led to a 35% increase in organic traffic by implementing targeted content strategies and SEO improvements.

Beyond work, I stay ahead of industry trends by attending webinars and participating in local marketing meetups. I believe in continuous learning and sharing knowledge with peers in the field.

Let’s connect! If you’re interested in working together on your next digital marketing project or want to exchange ideas about industry trends, feel free to connect via LinkedIn or contact me directly at hello@itsrachael.com.

Skills:
Digital Marketing Strategy | Performance Marketing | Data Analysis | E-Commerce Growth | Multi-Channel Campaign Management | Predictive Analytics | CRM Automation | SEO Optimization

Rachael Mahaffey

Ryan Staley

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 2,500 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

Podcast Host

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.

I fired a $150K prospect a few weeks ago.

Not because the deal fell apart.

Because the person on the other side couldn't move at the speed needed — or delegate to the people trying to help him.

Here's what happened:

I'd been bending over backwards to accommodate a complex enterprise deal. Custom scope. Revised SOW. Extra calls.

My contact's team was supportive and wanted to move forward. But the decision-maker? 

He was a great person however, he was struggling with how fast everything in AI is moving.

This caused indecision.

That led to paralyzed decision making.

Which led to no progress in 5 months.

I hung up the phone and realized something:

I was chasing a deal I didn't even want.

So I processed it and sent a note. 

Took the high road. 

And walked away from $150K.

Here's what I've learned building a bootstrapped company from zero to product market fit:

The clients you say NO to define your business more than the ones you say yes to.

Bad-fit clients drain your energy.

They erode your team's confidence.

They take 3x the time for half the result.

And they never refer anyone worth working with.


The math is simple:

One bad $150K client costs you three great $100K clients — because you didn't have the energy or capacity to serve them.

Every entrepreneur hits this moment.



The question is: do you take the money and the misery? 

Or do you protect the thing you're building?

I chose the second.



And the same day? We added a $100K services deal with a client who texts me ideas on weekends because they're that excited about what we're building together.



That's the business I want.

Not every dollar is worth earning.

P.S.- Here are 3 AMAZING clients and people I have got a chance to work with Andrew Morton , Negin Kamangar  and Brandon Taylor  and was lucky enough to have them all in the same room at a GTM conference.

Founder & CEO, Whale Boss | Demystifying AI Agents | Helping revenue leaders 2x team results through AI Led GTM | Trusted by $50M-$20B PE-backed and Publicly Traded Companies | AI ROI for your team in 60 days

3.5 Months in, three operating systems later, and I'm officially hijacked by Claude Code.

Not in the way you think.

Let's skip the AI hype and get real.

I stopped reading about "AI use cases" and got my hands dirty.

Fifteen solid hours, two weeks, zero fluffy prompts.

Just building actual operating systems.

Not content.

Not lists.

Real, working systems that actually run my business better.

Here's what happened:

1. The CEO Operating System (Annual Planning)

Forget hope and guesswork. This system turns chaos into a clear plan.
- Pick the few things that matter (not 27 "priorities")
- List what we're not doing
- Map risks and constraints
- Build a real 90-day action plan
- Log decisions, assumptions, and learnings as we go
- Use 10 battle-tested frameworks for tough calls

The result? Not a plan that "looks good" in a slide deck, but one that actually runs when the rubber meets the road.

2. The Sales Intelligence Operating System (Client Interaction Analysis at scale)

My new force multiplier.
It chews through a mountain of sales calls, client emails, and feedback in seconds, not weeks.
- Finds trends, patterns, and recurring objections
- Spots churn risk and expansion signals
- Surfaces the REAL words buyers are using, not what we wish they'd say
- Highlights opportunities we're missing

This thing can scrape thousands of data points and hand me something actionable before the coffee gets cold.

3. The Product Intelligence Operating System (Continuous Improvement)

Where delivery drifts, this system pulls it right back.
Because my edge is delivering actual AI transformation training, not just talking about it.
This OS hunts for patterns in:
- What features clients love (and which get ignored)
- What gets real results vs. wasted effort
- Where new modules, examples, or sequences are needed

It's the antidote to vibes-only product improvement. Decisions made on facts, not feelings.

Let's get honest about what made this work.

It wasn't "AI did it for me."

It was orchestration.

I skipped the mega-prompt lottery and ran swarms of specialized agents, each with a clear job.

Every OS had something even more important: memory. They don't just spit out answers and forget. They get smarter. They remember what works, what doesn't, why we made certain calls, and how we define "good."

Every week, outputs compound instead of vanish.

Here's your anti-hype PSA: it's not magic. If you feed it garbage, you get garbage,just a lot faster, and prettier.

The unlock isn't the tech.

It's having:

- Real-world skills 
- Guardrails
- Repeatable workflows
- And, most important, systems that learn instead of reset every time you open a new chat window

Thinking about breaking this down in detail on LinkedIn, YouTube, maybe even my podcast.

Drop a comment, tag someone who needs to see this, or just tell me if you want more.

I was running a C-Suite AI workshop this week.

$300m+ company. Frameworks. Use cases. Hands-on practice.



Then I made a decision that wasn't in the agenda.

I showed them the agent operating system I built for my own business.



Not a slide deck about it. Not a concept diagram.

The actual system. Running. Live. In real time.



I walked them through how AI agents handle my:

-pipeline reviews

-score candidates

-generate content from my daily notes

 -build client deliverables 




ALL orchestrated from one environment.



The energy in the room shifted instantly.

One executive said: "We need this for our team."

Another asked: "What would it take to have you build something like this for us?"

Later that same day, two other clients in completely different industries told me the same thing: "Build this for us."



Three companies. One week. Same request.

Here's what I realized:

The gap in the market isn't AI tools. Everyone has access to tools.

The gap is AI SYSTEMS - purpose-built, connected, learning from your actual data and workflows.



Tools answer questions.



Systems run operations.



When those executives saw a live system that manages a real business, they didn't see a cool demo.



They saw the 30 hours a week they're currently burning on work that an agent could handle.



They saw decisions being made faster because context was already synthesized.



They saw what their company could look like in 6 months.

And they wanted it immediately.

The companies that figure this out first won't just be more efficient.

They'll be operating from a completely different architecture.



They will be playing 3d Chess when everyone else is playing checkers.



And the gap between "we use AI tools" and "we run on AI systems" is about to become uncloseable.

This week, multiple enterprise clients - independently - asked me to build the same thing.

An agent operating system.

Not an AI tool. Not a chatbot. Not a "copilot."

An operating system with Claude Code where AI agents handle core business functions: pipeline management, content generation, candidate evaluation, client deliverables, and reporting.

All connected. All learning. All orchestrated from one environment.

Here's my prediction:

Within 18 months, every company above $50M in revenue will need one of these.

Not want one. NEED one.

Here's why:

Right now, most companies use AI like it's 1995 internet. One tool at a time. Disconnected. Manual.

"Use ChatGPT for this."

"Use Copilot for that."

"Here's a prompt template for the other thing."

That's not a strategy. That's a collection of experiments.

An Agent Operating System is different:

**It connects.** Your CRM data flows into your pipeline agent, which informs your content agent, which feeds your outreach agent. Information moves across the business automatically.

**It learns.** Every interaction teaches the system how your team operates. What you prioritize. What you skip. Where you need help. It gets smarter every week.

**It orchestrates.** Instead of 10 employees using 10 separate AI tools in 10 separate ways, one system coordinates agents that work together like a team.

**It compounds.** The system you build in Month 1 makes Month 2 better. Month 2 makes Month 6 dramatically better. By Month 12, you're operating at a level that's structurally unreachable for companies that started late.

When I showed my own Agent OS to executives this week, I saw the same reaction every time:

Not "that's cool."

"We need this. Now."

They saw what their company could look like when AI isn't a collection of tools but an actual operating layer.

The companies that build their Agent OS in 2026 will have a 12-18 month compounding advantage over those who start in 2027.

And in AI, 18 months of compounding is a lifetime.

The race isn't to adopt AI.

The race is to architect it.

Are you building an operating system? Or are you still buying tools?

Cowork dropped a Schedule Task feature — and the use cases Anthropic built into it are WILD.

Here's why this matters more than 90% of what gets posted about AI this week.

There's been a massive gap in the market between two worlds.


World 1: A chatbot. Easy to use. Limited. Reactive. You ask, it answers. Nothing changes when you close the tab.


World 2: A sophisticated coding agent. Insanely powerful. Almost zero adoption because the average executive has no idea how to deploy it.


NOBODY has solved that gap.


Until now.


Cowork with Schedule Task sits DIRECTLY in the middle. It's the bridge non-technical executives have been waiting for.
Here's what you can actually do today:


Click Schedule Task → Use Cases → pick a workflow that runs for you automatically.


That's it. No code. No engineers. No 6-month implementation.

You're now operating with agentic automation that most companies spend $200K trying to build.


NOTE: The executives who find these features first and build habits around them are the ones who will look like AI geniuses in 12 months. 

The window to be early is still open — but it's closing fast.


What's the number one task on your team that should already be running automatically?

Microsoft just did something that changes the game for every frustrated Copilot user.

They're integrating Anthropic's Cowork directly into Co-Pilot.

And Sonnet 4.6 is ALREADY live in the main interface right now.

I wasn't expecting that. The model is insanely good.

Here's what this means if you've been frustrated with Copilot not delivering what was promised:

You've been using it like a smarter search bar. A question here. A summary there. Helpful, but not transformational.

That era is ending.


Cowork inside Copilot means an agent that EXECUTES across your entire Microsoft 365 environment. 

Calendar, email, files, meetings — all connected.
It cleans your calendar. 

Protects your focus time. 

Builds your meeting packets from live email and file context. 

Generates competitive intel and pitch decks for product launches.

Not as suggestions. As COMPLETED work.


This is the difference between AI answering questions and AI doing work.


The Copilot users who felt let down weren't wrong to expect more. The capability just caught up to the promise.



I have been using Claude Co-Work extensively and I'm really impressed with what it's been able to deliver. In addition I've been using Co-Pilot and I've seen it get better and better in the more recent months, which makes this announcement very exciting and promising.



NOTE: I have not tested this personally yet — but this is the most significant Microsoft AI release I've seen in 3 years of watching this space. Full honest breakdown coming once I'm hands on.

Google just changed the game for every executive using Workspace.

And most people won't notice for 6 months.

Here's what happened:

Gemini just got upgraded ACROSS the entire Google Workspace suite. Slides. Sheets. Drive. All of it.

I have early access. I've been testing it.

And I'm genuinely impressed with what Google is doing here.

Here's what matters:

1. Gemini in Slides now creates professional layouts and fully editable diagrams from scratch. You describe your story. It handles the design. Minutes instead of hours.
2. Gemini in Sheets is now a full spreadsheet BUILDER. Describe what you need. It creates, organizes, and edits entire sheets from basic tasks to complex data analysis.
3. Ask Gemini in Drive lets you search in natural language and get an AI Overview at the top of your results. It pulls insights across your documents, emails, calendar AND the web.

This isn't a feature update.

This is Google turning Workspace into an AI operating system.

NOTE: The companies that retrain their teams on these capabilities in the next 60 days will operate at a completely different speed than those who wait.

The gap between AI-first and AI-last companies just got wider.

Which of these 3 updates would save YOUR team the most time?

I recently wrapped a 60-day AI Transformation with a $3B services company with over 600 enterprise clients.

Their CRO told me in our kickoff: "Our win rate is in the mid-teens. We're managing 250 deals a quarter across 5+ lines of business. Our people can't research fast enough, can't respond to RFPs fast enough, and can't expand into accounts they're already sitting in."

We didn't add headcount.

We attacked 4 constraints across their sales, account management, and BDR teams:

📊RFP responses were the bottleneck killing their pipeline. 70% of their deals come through RFPs, and the proposal process was manual, slow, and inconsistent. We built a system that ingests previous responses, compliance requirements, and solution details — then generates targeted RFP responses. Their proposal team said it "blew their minds." What used to take days now takes hours.


📈White space mapping across existing accounts was manual and reactive. With 8 lines of business and 600 clients, account managers couldn't see what else they could sell into accounts they already owned. We built a system that instantly maps client challenges to their full solution portfolio. One account manager used it to identify $40K in new opportunities from a single SOW analysis. White space mapping went from days to less than a minute.


📊Client research for meetings was shallow and slow. Reps were manually searching dozens of websites, pulling financials, and trying to find hidden initiatives. We built a deep research system that analyzes public data, financials, and industry trends in minutes. One rep used it to uncover a secret project name at a Fortune 500 client that gave him an unfair advantage walking into the meeting.


📈Competitive positioning was inconsistent across verticals. With major global competitors, reps needed to speak different languages for healthcare, financial services, and telco — but the messaging was generic. We built AI systems that generate vertical-specific competitive comparisons, joint value propositions, and tailored outreach by industry.



The result?

White space mapping: days to under 1 minute.

Massive new opportunities from AI-surfaced SOW gaps.

Research depth: 10x, with reps analyzing 96+ data sources in minutes.

Zero new hires.



Their CRO said it: "This is the most relevant investment we can make for immediate impact."



NOTE: We didn't try to "transform the whole org." We found the TOP 4 constraints on their revenue team and attacked each one with a specific AI system. That's the difference between AI strategy and AI transformation. 

Strategy is a deck. 

Transformation is pipeline.

What would nearly doubling your win rate do for your revenue team?



DM me to see if you're a fit for us to help you.

I rebuilt core features of an AI operating system from my phone.

While watching TV.

Not a prototype. Not a mockup. Actual working features — memory systems, skill frameworks, and communication channels — all built from my cell phone on the couch.

A year ago this would have required:

→ A development environment

→ A software engineer

→ 2-3 months of sprints

→ $40K-$80K budget

I did it between Olympic events on the commercial break.

Here's what this means:

The barrier to building AI is gone.

Not "lowered." Gone.

The excuse era is over.

You don't need a technical background.

You don't need a big screen.

You don't need a dev team.

You don't need a budget.

You need clarity on what to build and the willingness to describe it in plain language.

I've never formally coded anything. 

I built 15+ AI agents, 3 operating systems, and now I'm shipping features from my phone.

Every week I hear leaders say: "We need to hire engineers before we can start our AI strategy."

No. You don't.

You need someone who understands your business deeply enough to describe what AI should do — and then let AI build it.

That person might already be on your team.

It might be you.

The question isn't whether you have the technical skills.

It's whether you have the clarity and the courage to start.

AI agents are not a pipeline strategy. They're a pipeline ACCELERANT.
And if you pour accelerant on a broken foundation, you don't get growth.
You get an explosion.


After working with 3,100+ executives on AI transformation, here are the 3 levels I see teams operating at:


LEVEL 1: AI as a toy Teams copy-paste prompts from LinkedIn. No process. No integration. No results. They declare AI "overhyped" and move on.


LEVEL 2: AI as a tool Teams plug agents into existing workflows. Some time savings. Some pipeline lift. But they hit a ceiling because the foundation underneath was never built for AI.


LEVEL 3: AI as an operating system Teams redesign their workflows AROUND AI capabilities. ICP is specific enough for agents to act on. 

Data is clean. 
Processes are documented. 
Definitions are aligned across sales, marketing, and ops.


THAT is where the math changes.

Most teams are stuck between Level 1 and Level 2 and wondering why AI 
isn't delivering.


I'm joining ☁️ Cliff Simon, Manoj Ramnani, and Jonathan M Kvarfordt, MBA SalesIntel.io for a live webinar TOMORROW to break down exactly how to build the foundation that gets you to Level 3.


Which level is your team at right now?

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