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.

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

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.

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 CEO told me last week he'd never tried Claude Code.
 
"That's for technical people, right?"
 
He uses AI every day. And he's been scrolling past the most powerful tool in his stack because of how it was positioned.
 
He's not alone. I hear this from revenue leaders, ops executives, and founders constantly.
 
I put an operator's guide together - let me know if you want it. 

Let me tackle this directly. 
 
Claude Code is not a code editor. It's an AI operating system.
 
The terminal is just where you type. That's it. 

Just like you type a text message to your friends or loved ones. 
 
Here's the mental model I use to explain the difference between Code and Cowork:
 
𝗖𝗼𝘄𝗼𝗿𝗸 is a smart contractor you hire for a day. They do great work. They leave. Next session, you re-explain everything from scratch.
 
𝗖𝗼𝗱𝗲 is a full-time operator who sits at your desk every day. They remember everything. They build systems. They get better over time. Every session starts where the last one ended.
 
Same model underneath. Completely different relationship.
 
Four things make Code different. None of them require writing code.
 
1. CLAUDE.md = Your Business Operating System
  
In Cowork, every session resets. You re-explain. You re-upload. You re-establish context.
 
In Code, it's architecturally guaranteed to load. The compound effect over months is significant.
 
2. Named Agents = Your AI Team
 
Cowork sub-agents are ephemeral — one task, then gone.
 
In Code, you build agent specs. Your CMO agent knows your positioning. Your Competitive Intel agent knows your rivals and preferred format. You build it once. You refine it over time.
 
I run 90+ agents. When I need a competitive battlecard, the agent already knows everything. What used to take an hour takes 7 minutes.
 
3. Your File System Is Already There
 
Cowork works in a sandbox. Code works in your actual world.
 
"Read the pipeline export in Downloads and tell me which deals are at risk this quarter."
 
You type that. It reads it. No upload prep. No copy-paste. No re-explaining where things live.
 
This sounds minor until you've done the upload dance three times in one week.
 
4. Automation That Actually Runs
 
Cowork's scheduled tasks are beta and unreliable right now. They work sometimes. You can't build a business process on "sometimes."
 
Code supports hooks, cron jobs, and full automation pipelines. 

Things I have running in production today:
 
→ Daily competitive monitoring that flags pricing changes 
→ Automated content pipeline: research → draft → review 
→ Weekly research digests from 10+ sources synthesized automatically 
→ Pipeline health alerts triggered by CRM events
 
None of those required writing code. They required describing what I wanted.
 
"But I'm not technical"
 
This isn't either/or. 

I use Cowork for quick documents and one-off tasks. 

I use Code as the operating system underneath — context, agents, automation, memory.

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? 👀👀

Spent an hour watching 🚀 Victor Adefuye run 3 crazy workflows in Claude Cowork and its freakin rad. 

Want to see it? Comment below.

Victor has been in GTM enablement for over a decade. 5 years as an MD at Winning by Design. 

Teaching reps how to write emails, run discovery, execute MEDDPICC. 

The guy knows what "good" looks like better than almost anyone.Then Cowork dropped. 

And he turned 10 years of enablement IP into AI agents.

Here's what he showed my man Jonathan M Kvarfordt, MBA live on the GTM AI Podcast .

He pointed Cowork at 360 conference leads and typed 3 sentences. Cowork spun up 15 parallel sub-agents. 

Each one independently researched a company, scored it against his ICP, and wrote personalized nurture emails that pulled from his 110-page content library. Matched by pain point.

He fed 7 sales calls into a folder. A custom MEDDPICC skill scored every single one in parallel. Individual scorecards with direct quotes and timestamps. 

Then a synthesis agent rolled up a team-wide gap analysis showing exactly where reps were weak: economic buyer, champion development, paper process.

And then came the one that broke my brain.

Victor is NOT a developer. Never has been. 

But in 2 weeks he built 7 𝗠𝗮𝗸𝗲.𝗰𝗼𝗺 automations by having a conversation with Cowork. 

It opened Make in his browser. Selected the modules. Configured connections. Wrote the prompts. One automation finds newly hired CROs every week and builds drip campaigns off the trigger. Built through chat.

He said something I can't stop thinking about: "The same training I used to give to humans and hope they would remember, I now give to AI. It's more reliable.

"That's the whole game right there. Your enablement playbook IS your AI moat. The people who spent years defining what good looks like are now the most dangerous builders in the room.

Stop prompting. Start packaging your expertise.

All 3 workflows are broken down step-by-step in my latest newsletter. Full playbook. Skill templates. MEDDPICC scoring rubrics. 

Everything you need to build these yourself this week.

Want to see it in action and get the full playbook?

-Like this post--Comment "Cowork Playbook"---Repost if you know a GTM leader who needs this

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

Enjoy!

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?

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.

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.

They said ideas are cheap and execution is king. AI has flipped that for the most part.

OpenAI is a $730 billion company doing what every $730 billion company eventually does.
 
Abandoning the product that made it famous to protect the product that actually makes money.
 
ChatGPT's web traffic share dropped from 86.7% to 64.5% in twelve months. 

Google Gemini went from 5.7% to 21.5% over the same period. 

DeepSeek is matching GPT-5 performance at 1/30th the cost.
 
When the commodity version of your product is 97% as good and nearly free, you don't have a product problem. 

You have a business model problem.
 
Meanwhile, the numbers on the enterprise side are going in the opposite direction:
 
→ Codex crossed 1.5M weekly active users with 20x growth since August 2025 
→ Enterprise seats grew 9x year over year 
→ 92% of Fortune 500 companies are using ChatGPT products
 
Revenue per enterprise user dwarfs consumer subscriptions. 

Switching costs are orders of magnitude higher. 

And the customer who has Codex embedded in their engineering workflow doesn't cancel because a cheaper model exists.
 
Fidji Simo ran Instacart. She's been inside brutal unit economics, where every order can lose money if you're not obsessive about the math. She knows exactly what "the consumer unit economics are breaking" looks like from the inside.
 
So she told the all-hands: stop chasing side quests. Go win where it matters.
 
That's the right call. But it comes with a sentence nobody's saying:
 
OpenAI's $280 billion revenue target by 2030 requires consumer subscriptions at $20/month to become the foundation of an enterprise infrastructure play. 

Those are different companies. 

The mission was AGI for humanity. 

The strategy is Codex for Fortune 500 engineering teams.
 
You can run both narratives for a while. Eventually the spreadsheet picks one.
 
The interesting question isn't whether enterprise AI is the better business (it obviously is).
 
It's whether OpenAI gets there before Anthropic locks up enough Fortune 500 contracts to make the race irrelevant against a projected $143 billion in cumulative losses and a market that's compressing faster than anyone expected.
 
That's not a rhetorical question. It's the actual race.

What’s holding your business back? Helping Founders to SMBs accelerate growth with GTM + Sales strategies that are powered by AI & fueled with Human insight | 7x Founder - 3 Exits | Coffee Snob & Foodie

What’s holding your business back?

I help entrepreneurs, founders, and businesses accelerate Revenue, Sales & Impact through proven GTM Strategy that aligns People, Process, and Product so the right buyers hear the right message and take action fast.

My playbook was forged building 7 companies, scaling 2 globally, and exiting 3: lessons earned through experience, now delivered with clarity and speed.

I launched my first company at 19 and grew it to a team of eight. Since then, I’ve partnered across the USA, EMEA, and APJ with some of the world’s largest companies bringing bold thinking, strategic clarity, and relentless execution so businesses don’t just survive - they scale with purpose.

I blend modern tech and AI to streamline operations and drive smarter decisions, while staying rooted in what actually fuels growth: H2H - human-to-human connection.

Across thousands of hours of training and coaching, I’ve helped leaders step up with clarity, confidence, and intention turning messy complexity into simple, repeatable motion.

Here’s how I help:
🔷 GTM Strategy: Revenue-driven strategies that align product, positioning, and sales motion to the right buyers. From segmentation and ICP to channels, pricing, and enablement, I build growth engines designed for now and ready for what’s next.

🔷 Revenue Enablement: Misaligned GTM teams bleed revenue. I install the systems, tools, and training that turn chaos into clarity - so teams sell smarter, shorten cycles, improve win rates, and grow profitably.

🔷 One-on-One Coaching: High - impact coaching for founders and leaders ready to break through roadblocks and level up fast. Delivered in focused 90-day engagements because transformation doesn’t happen in a single session.

As a seasoned leader, I’ve built and led high - performing teams rooted in trust, transparency, and execution working across Sales, Marketing, Product, HR, Customer Success, and Partnerships to turn aligned strategy into measurable results.

Signature outcomes clients come for: 
✔ A clearer story buyers believe
✔ A repeatable sales motion
✔ Pricing that captures value
✔ A team that knows exactly what to do next.

👉 My mission: Elevate businesses through connection and trust. Refine systems, unlock talent, and champion leadership that drives both people and performance.

If growth feels harder than it should, that’s a signal.
We’ll fix the strategy, tune the motion, and get momentum back on your side.

📩 Let’s talk: pjcanhelp@gmail.com

Paul “PJ” Jackson👇

I’m going to keep this short.
 
It’s my birthday today.  

So I’m taking myself & a few others out to lunch.
 
Just me, myself…  
and the other 99 personalities in my head.
 
Need to get a few things done first.
 
See you tomorrow.

Paul “PJ” Jackson 📌

Accelerating Growth ! Optimizing People, Process & Product via GTM + Sales strategies | Powered by AI, fueled by Human insight | 7x Founder - 3 Exits | Coffee & Foodie Snob

🌧️ 𝗠𝗮𝗿𝗸𝗲𝘁 𝗗𝗮𝘆 𝗼𝗿 𝗪𝗮𝘁𝗲𝗿 𝗣𝗮𝗿𝗸? 𝗬𝗼𝘂 𝗗𝗲𝗰𝗶𝗱𝗲.

They say you can't buy happiness, but you can buy fresh stroopwafels in a downpour, and honestly, that’s a pretty close second.

I headed down to the 𝗪𝗲𝗲𝗸𝗲𝗻𝗱 𝗠𝗮𝗿𝗸𝗲𝘁 today, and while the weather forecast said "light showers," my umbrella and I have decided to file a formal grievance. 

I’m currently 70% human and 30% rainwater, but did that stop me from securing the goods? 𝗔𝗯𝘀𝗼𝗹𝘂𝘁𝗲𝗹𝘆 𝗻𝗼𝘁. 

There’s something uniquely humbling about trying to look cool in a selfie while your hat is slowly becoming a sponge and you're dodging pigeons who seem much better prepared for the elements than you are.

My thought process...
• 𝗧𝗵𝗲 𝗩𝗶𝗯𝗲: Damp, but delicious.
• 𝗧𝗵𝗲 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Walk fast, smile through the splashes, and follow the scent of the hot kebabs and Pastel de nata.
• 𝗧𝗵𝗲 𝗟𝗲𝘀𝘀𝗼𝗻: A little rain never hurt anyone; it just makes the coffee at the end taste significantly better.

If you need me, I’ll be at home drying out until Monday. 

Wishing you all a weekend that is significantly drier (and just as fun) as mine!

𝗛𝗼𝘄 𝗮𝗿𝗲 𝘆𝗼𝘂 𝗱𝗼𝗱𝗴𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗮𝗶𝗻 𝘁𝗼𝗱𝗮𝘆? ☔👇

An influencer told one of his mentees in a live video:
 
“Your life at the pinnacle of success is the same as everyone else’s.”
 
Honestly? That’s BS
 
Because the 𝘷𝘪𝘦𝘸 might look similar…
But the 𝘄𝗲𝗶𝗴𝗵𝘁 is not.
 
At the top, you carry things most people never see.
 
Responsibility for people’s livelihoods. 
Decisions that move millions.  
The quiet pressure of knowing one wrong call can unwind years of work.
 
Success doesn’t make life “the same.”
It raises the 𝘀𝘁𝗮𝗸𝗲𝘀.

The late nights are different. 
The doubts are different. 
Even the wins feel different.
 
Because when you build something real, you know exactly what it costs to get there.
 
Most of the founders I know don’t feel like they’ve reached a “pinnacle” anyway.
They just feel the next problem…  the next responsibility…  the next thing that needs fixing.
 
That’s the paradox of building.
 
The higher you climb,  the less it feels like a peak and the more it feels like 𝗱𝘂𝘁𝘆.
 
So no.
Life at the top isn’t the same.
 
But the people who reach it usually aren’t chasing comfort anyway.
They’re chasing 𝗶𝗺𝗽𝗮𝗰𝘁.
 
Curious… Do you think success makes life easier or just heavier in different ways?

You won’t see me shouting about “success” on here in the way of...
Rolex posts.
Private jets.
Screenshots of $10m in revenue hiding what’s actually going on underneath.

That isnt me and because I’ve seen what that looks like up close “behind the curtains”.

Everything behind it stretched thin.
People carrying weight they were never meant to.
Founders holding it all together through sheer force.

From the outside, it looks big and successful.
From the inside, it’s fragile.
That’s not success. That’s a pressure cooker.

I’ve lived both sides of it.
Lost everything. Started again. More than once.
Built from zero. Moved countries. Exited.
And still wanted to rebuild.
So no… I’m not interested in “look at me” 

I care about what actually holds:
* Can the business run without you?
* Does revenue repeat without heroics?
* Are you making money?
* Is the structure carrying the load… or hiding the cracks?

If you’re building right now, don’t chase validation.
Build something that can carry its own weight – People Process Product.
Powered by Ai, fueled with Human insight!

Paul "PJ" Jackson

Really, what's the point of having a North Star without a map!
 
A lot of leaders think their job is to stand on the mountain and point at the horizon.
 
“That's where we're going.”
 
That’s a compass.
 
It feels inspiring for about five minutes.
 
Then Monday morning arrives.
Most teams already know the destination. 
They understand the ambition.  
They want to win.
 
What they don’t have is the 𝗿𝗼𝘂𝘁𝗲.
 
The sequence.  
The structure.  
What happens when things go wrong?
 
Vision tells people 𝘄𝗵𝗲𝗿𝗲.
A map shows them 𝗵𝗼𝘄 𝘁𝗵𝗲 𝗵𝗲𝗹𝗹 𝘁𝗼 𝗴𝗲𝘁 𝘁𝗵𝗲𝗿𝗲.
 
When teams stall, leaders often double down on motivation.
More vision.  
More speeches.  
More “North Star.”
 
But the real issue is usually structural.
No clear path. 
No sequence. 
No operating map.
 
Leadership isn’t pointing at the horizon.
It’s building the path others can follow.
 
Are you giving your team a direction… or a 𝗿𝗼𝘂𝘁𝗲 𝘁𝗵𝗲𝘆 𝗰𝗮𝗻 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗲𝘅𝗲𝗰𝘂𝘁𝗲?

♻️ 𝗣𝗲𝗼𝗽𝗹𝗲. 𝗣𝗿𝗼𝗰𝗲𝘀𝘀. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁
Paul “PJ” Jackson for bold GTM Strategies, Business & Sales Insights that deliver.

It’s weird when you realise… you’re working harder than ever, and things are getting slower.

I've hit that point at different stages while building several businesses.
More hours.
More conversations.
More “trying to push it "forward"... 
and everything started to feel just heavy.

So one Saturday afternoon I sat with a drink in hand
I knew that effort wasn’t the solution anymore.
Something else was off.

I looked at my 3Ps
People carrying things they shouldn’t.
Process of doing the job of clarity.
Product not pulling its weight.

I saw that the more I pushed, the more drag I created.
That’s a hard thing to admit as a founder.
Because effort feels noble.

But in reality?
It can be expensive noise.
Once we fixed the structure, I could breathe, and things moved again.

Not faster because we worked harder, faster because we stopped fighting the business.

If it feels heavy right now, don’t just push harder.
Look at what your effort is hiding.
What are you carrying that the business should be built to handle?

𝗬𝗼, 𝘄𝗮𝘁’𝘀 𝗰𝗿𝗮𝗰𝗸𝗶𝗻𝗴?

It’s Friday. 
Go grab some Vitamin D and a drink, mine’s a rum. 🥃

Before the weekend hits, sit in silence for a minute and actually reflect on the week. 

Mine? A "little" busy:
• 𝗧𝗵𝗲 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Deep-dived with 4 founders (revenue between $10M–$32M) on H2 scaling. We’re cutting the friction and building processes that actually breathe.
• 𝗠𝘆 𝗛𝗲𝗮𝗹𝘁𝗵: Got a lump on my eyelid checked. Not glamorous, but surgery is booked. 
  Take care of your temple, folks.
• 𝗧𝗵𝗲 𝗣𝗿𝗼𝗱𝘂𝗰𝘁: Ran a dry run on a new workshop. It’s sharp.
• 𝗧𝗵𝗲 𝗣𝘂𝗹𝘀𝗲: Called 2 clients to audit their team implementation. 
  No half-baked processes on my watch. You'll own it as much as we will with you!
• 𝗧𝗵𝗲 𝗪𝗶𝗻: Onboarded a new $1.3M client. Churn is sitting at 11.8%, sales have stalled, and we’re about to find out exactly why and fix the leak.

𝗜 𝘀𝗲𝗲 𝘁𝗵𝗲 𝗳𝗲𝗲𝗱. 
Everyone’s "crawling to the finish line" and dreaming of Saturday. 
Honestly? 
I hope your Friday doesn't feel like an escape room. If so, it's time to change the game you're playing.

I’m finishing the week with the energy that I started with. 
The wins we stacked since Monday aren't just boxes ticked, they’re premium fuel.
I love orchestrating my week.

Dont be like most who spend Friday afternoon checking the clock. 
Get checking the scoreboard.

𝗡𝗼𝘄...
Stay loud. Stay dangerous. 
And for heaven’s sake, have a drink that costs more than your Netflix subscription, you deserve it!

Start treating your AI like a high-performance engine.

I just went down a rabbit hole on the "Needle in a Haystack" data from Google, and honestly? 
Most of us are using these models wrong.

We’re dumping 100-page PDFs into a chat and wondering why the response feels "fuzzy" or slow.

𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝗜 𝗳𝗼𝘂𝗻𝗱 𝗼𝘂𝘁: 
Just because a model 𝗰𝗮𝗻 remember 1 million tokens (about 750,000 words), doesn’t mean it 𝘀𝗵𝗼𝘂𝗹𝗱, at least not if you want top-tier reasoning.

If you want your AI to actually think and not just "search," here is how:

𝟭. 𝗥𝗲𝘀𝗽𝗲𝗰𝘁 𝘁𝗵𝗲 "𝗚𝗼𝗹𝗱𝗶𝗹𝗼𝗰𝗸𝘀 𝗭𝗼𝗻𝗲"
If you need deep strategy or complex code, keep your context under 𝟯𝟮,𝟬𝟬𝟬 𝘁𝗼𝗸𝗲𝗻𝘀 (roughly 24k words). This is where the model is at its sharpest. 
Go over that, and you’re asking for "Context Rot."

𝟮. 𝗔𝗜 𝘀𝗽𝗲𝗮𝗸𝘀 𝗶𝗻 𝗧𝗼𝗸𝗲𝗻𝘀, 𝗻𝗼𝘁 𝗪𝗼𝗿𝗱𝘀
AI doesn’t read words; it processes "chunks" of characters (tokens).
• 𝗧𝗵𝗲 𝗥𝘂𝗹𝗲: 1,000 tokens, approx 750 words.
• Think of it like this: 𝗧𝗼𝗸𝗲𝗻𝘀 𝗮𝗿𝗲 𝘁𝗼 𝘁𝗵𝗲 𝗔𝗜 𝘄𝗵𝗮𝘁 𝘄𝗼𝗿𝗱𝘀 𝗮𝗿𝗲 𝘁𝗼 𝘂𝘀. It’s the actual "currency" of its brain. Stop counting pages and start counting these "building blocks."
  
𝟯. 𝗨𝘀𝗲 "𝗔𝗻𝗰𝗵𝗼𝗿𝘀" (𝗫𝗠𝗟 𝗧𝗮𝗴𝘀)
Don't just paste a wall of text. Wrap your data in tags like <𝚍𝚘𝚌𝚞𝚖𝚎𝚗𝚝𝚜> or <𝚒𝚗𝚜𝚝𝚛𝚞𝚌𝚝𝚒𝚘𝚗𝚜>. 
It’s like giving the AI a map instead of a pile of loose papers.
It helps the model distinguish between what it needs to 𝘬𝘯𝘰𝘸 and what it needs to 𝘥𝘰.

𝟰. 𝗧𝗵𝗲 "𝗥𝗲𝗰𝗲𝗻𝗰𝘆" 𝗛𝗮𝗰𝗸
Put your most important commands at the very 𝗯𝗼𝘁𝘁𝗼𝗺 of your prompt. 
Models have a "recency bias", they pay the most attention to the last thing they read before they start typing.

𝗧𝗵𝗲 𝗕𝗼𝘁𝘁𝗼𝗺 𝗟𝗶𝗻𝗲:
The "Haystack" is getting bigger, but your "Needle" (the insight you actually need) is only as good as your prompt structure.

Optimize and stop blaming the model for being distracted by the noise you introduced.

👉 Go try this out and let me know what changed!

Years ago, I threw a headline at a magazine editor.

He asked, " PJ, you worked in media, what headline would you suggest?"

He was reviewing a high-end headphone amp from an Australian brand.
I said: call it "It’s A Bloody Ripper.”

He laughed.
We both did.
Felt a bit too much… for a serious European hi-fi magazine.
He ran it anyway.

What stood out for me, not because it was clever.
Because it was honest. 
To do this was very different from the 'norm", let alone print it.
The editor really loved this product.

Most people water themselves down in rooms they want to belong in.
Safer words.
Softer edges.
Same voice as everyone else.
And then wonder why no one remembers them.

I’m an Australian living in Europe.
That makes me distinct.
The way you see things, say things, push things…
That’s not something to smooth out.
That’s the whole point.

If you sound like everyone else in the room… why would anyone choose you?

Your growth system is already decaying.

You just haven’t called it that yet.
Not because things are failing.
Because they still work… with effort.

I remember being in that spot.
You start noticing little things you can’t quite explain.
Results that don’t repeat the same way twice.
Conversations where no one can clearly point to what’s actually driving performance.

That’s not noise.
That’s a signal.

The 6 signals your growth system is already decaying:
1. Performance depends on specific people
2. Wins feel inconsistent, not engineered
3. Pipeline looks right but behaves unpredictably
4. Teams are active but not aligned on what matters
5. Decisions keep flowing back to you
6. Add pressure… and performance drops instead of holds

Nothing here feels urgent.
That’s why most leave it.
But this is the stage where growth either compounds…
or quietly starts working against you.

Just for you - Which one of these is already happening inside your business?

The 6 Signals

𝗣𝗿𝗼𝗽𝗲𝗹𝗹𝗶𝗻𝗴 𝗧𝗵𝗼𝘂𝗴𝗵𝘁 🤔
 
Most people talking about AI agents right now are focused on 𝘸𝘩𝘢𝘵 𝘵𝘩𝘦𝘺 𝘤𝘢𝘯 𝘥𝘰.
 
Very few are asking a more important question:
 
𝗪𝗵𝗮𝘁 𝘀𝗵𝗼𝘂𝗹𝗱 𝘁𝗵𝗲𝘆 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗯𝗲 𝗮𝗹𝗹𝗼𝘄𝗲𝗱 𝘁𝗼 𝗱𝗼?
 
Once agents move beyond analysis and start taking action, updating CRM records, triggering campaigns, adjusting workflows, you’re no longer talking about insights.
 
You’re talking about 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝘂𝘁𝗵𝗼𝗿𝗶𝘁𝘆.
 
That changes everything.
 
In our thinking, agents shouldn’t interact directly with GTM systems without a 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗹𝗮𝘆𝗲𝗿 𝗶𝗻 𝗯𝗲𝘁𝘄𝗲𝗲𝗻.
 
Something that manages:  
• identity  
• permissions  
• action boundaries  
• audit trails  
and escalation when something looks wrong.
 
Not because AI isn’t capable.
 
Because 𝘁𝗿𝘂𝘀𝘁 𝗶𝗻 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗶𝘀 𝗯𝘂𝗶𝗹𝘁 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗮𝗻𝗱 𝘃𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆.
 
The future won’t be agents running wild across the stack.
 
It will be 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗶𝗻𝘀𝗶𝗱𝗲 𝗮 𝘄𝗲𝗹𝗹-𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗱 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲.
 
Smarter execution doesn’t come from more automation.
 
It comes from 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝘁𝗵𝗮𝘁 𝗸𝗻𝗼𝘄𝘀 𝗶𝘁𝘀 𝗹𝗶𝗺𝗶𝘁𝘀.
 
Curious where others are landing on this.
 
𝗔𝗿𝗲 𝘆𝗼𝘂𝗿 𝗮𝗴𝗲𝗻𝘁𝘀 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗱𝗶𝗿𝗲𝗰𝘁𝗹𝘆 𝗶𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘀𝘆𝘀𝘁𝗲𝗺𝘀… 𝗼𝗿 𝗱𝗼 𝘁𝗵𝗲𝘆 𝗽𝗮𝘀𝘀 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗮 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗹𝗮𝘆𝗲𝗿 𝗳𝗶𝗿𝘀𝘁?

♻️ 𝗕𝘂𝗶𝗹𝗱 with clarity. 𝗟𝗲𝗮𝗱 with conviction. 𝗦𝗰𝗮𝗹𝗲 with impact.
Paul “PJ” Jackson for bold GTM Strategies, Business & Sales Insights that deliver.

You can’t market through this, it simply won't work!
 
I learned that the expensive way.
At one point, we thought the problem was demand.
 
So we spent more.
More ads.  
More outbound.  
More noise.
 
Nothing moved. I thought what the f@*k
Ive spent a ton of money and nothing!
 
Because we weren’t facing a visibility problem.
We were facing a structural wall.
 
Founder bottleneck. 
Positioning fog.  
Product carried by heroics.
 
And marketing doesn’t break concrete.
It just sometimes sends more traffic into it.
 
That’s the part founders hate.
 
The question I eventually asked myself: 𝘐𝘧 𝘳𝘦𝘷𝘦𝘯𝘶𝘦 𝘥𝘰𝘶𝘣𝘭𝘦𝘥 𝘵𝘰𝘮𝘰𝘳𝘳𝘰𝘸,  𝘸𝘰𝘶𝘭𝘥 𝘺𝘰𝘶 𝘴𝘤𝘢𝘭𝘦… 𝘰𝘳 𝘸𝘰𝘶𝘭𝘥 𝘵𝘩𝘦 𝘳𝘦𝘥 𝘭𝘪𝘨𝘩𝘵𝘴 𝘴𝘵𝘢𝘳𝘵 𝘧𝘭𝘢𝘴𝘩𝘪𝘯𝘨?
 
Most businesses don’t stall because of marketing and maintain it long-term.
They stall because there is a process inside that can’t carry more weight than it wasn't designed to.
 
Where’s your barrier if you looked right now?

Im known to be a straight and direct person, so here it is...
Your revenue could be a lie.

I sat in a swanky room a few months back.
Nice place. 
Glasswhite boards covered in numbers, pipeline, and hiring plans.
Dam good coffee.

The team was pumped, and you could feel it
Everyone felt it.

Though you know that feeling in your gut when something is a little off
The more we talked, the more it didn’t add up.
Because underneath all that “growth”…
Things were fractioning.
The team? As I found out were cooked. 
Running on caffeine and good intent.

The process? 
Held together with workarounds no one wanted to admit existed.
The product? Not pulling its weight… so the people were.

And revenue?
Just sitting on top of it all.
Adding pressure. Making the cracks worse.

No one says it out loud in those rooms…
but you can feel it.

This doesn’t get fixed by hiring more people.
Or buying another tool.
Or “optimising” a funnel.
That just spreads the weight faster onto a process that is already cracking

Their shift happened when realization hit and the conversation changed.
Not “how do we grow this”
but
“What’s carrying weight it was never built to hold?”

Then things got real.
Because once you see it… you can’t unsee it.

Most businesses don’t crumble overnight.
They stretch.
They bend.
They hold… until they don’t.

And it’s usually right when things are supposed to scale.

The structure that got you here?
Won’t carry what comes next.
You either rebalance it…or it does it for you.

Really, did you make a decision?
 
If nothing changed after it… it wasn’t a decision.
 
Didn't you say you “decided” to fix growth?
 
Then came the...
Same meetings.  
Same pipeline.  
Same rational.
 
Nothing changed.
 
That "decision", was simply comfort dressed up as intent.
 
“𝘼 𝙧𝙚𝙖𝙡 𝙙𝙚𝙘𝙞𝙨𝙞𝙤𝙣 𝙞𝙨 𝙢𝙚𝙖𝙨𝙪𝙧𝙚𝙙 𝙗𝙮 𝙩𝙝𝙚 𝙛𝙖𝙘𝙩 𝙩𝙝𝙖𝙩 𝙮𝙤𝙪’𝙫𝙚 𝙩𝙖𝙠𝙚𝙣 𝙖 𝙣𝙚𝙬 𝙖𝙘𝙩𝙞𝙤𝙣. 
𝙄𝙛 𝙩𝙝𝙚𝙧𝙚’𝙨 𝙣𝙤 𝙣𝙚𝙬 𝙖𝙘𝙩𝙞𝙤𝙣, 𝙮𝙤𝙪 𝙝𝙖𝙫𝙚𝙣’𝙩 𝙩𝙧𝙪𝙡𝙮 𝙙𝙚𝙘𝙞𝙙𝙚𝙙.”
 
I use that line for myself, because it exposes what I don’t want to admit.
 
Once you realise it
 
Real decisions show up fast.
Structure changes.
Bottlenecks get removed.  
Those "oh we can't change that" stops being protected.
 
Straight away!
 
If nothing in your business has 𝗺𝗼𝘃𝗲𝗱… come on, admit it, you didn’t decide.
 
You had good intent. 
That's okay if that is all you wanted to do.
 
What’s the decision you keep saying you’ve made…  but haven’t backed with action yet?

♻️ 𝗣𝗲𝗼𝗽𝗹𝗲. 𝗣𝗿𝗼𝗰𝗲𝘀𝘀. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁
Paul “PJ” Jackson for bold GTM Strategies, Business & Sales Insights that deliver.

𝗜𝗳 𝘆𝗼𝘂𝗿 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 𝗶𝘀 𝘀𝘁𝗶𝗹𝗹 “𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜”…  𝘆𝗼𝘂’𝗿𝗲 𝘄𝗮𝘆 𝗯𝗲𝗵𝗶𝗻𝗱!.
 
AI isn’t the moat.
𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗶𝘀.
 
Here are four things you need to understand about surviving the AI age.
 
𝟭. 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗲𝗳𝗳𝗲𝗰𝘁𝘀 𝗱𝗼𝗻’𝘁 𝘀𝗮𝘃𝗲 𝘄𝗲𝗮𝗸 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀.
You don’t “build” network effects.
You build the 𝗰𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝘀 that allow them to survive.
If your teams are misaligned and your GTM is chaotic, nothing compounds.
Growth just leaks.
 
𝟮. 𝗗𝗮𝘁𝗮 𝗶𝘀 𝗰𝗵𝗲𝗮𝗽. 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗶𝘀 𝘁𝗵𝗲 𝗺𝗼𝗮𝘁.
Most companies are collecting data.  Almost none are building intelligence.
Defensibility comes from signals AI can’t replicate.
Not dashboards.  Not spreadsheets.
 
But things like:
• Founder Dependency Index  
• Real-time GTM signals  
• Structural diagnostics across the company
That’s not data.
That’s 𝗰𝗼𝗺𝗽𝗼𝘂𝗻𝗱𝗶𝗻𝗴 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲.
 
𝟯. 𝗦𝘁𝗼𝗽 𝗵𝗶𝗿𝗶𝗻𝗴 𝗽𝗲𝗼𝗽𝗹𝗲 𝘄𝗵𝗼 𝗱𝗿𝗼𝗽 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 𝗮𝗻𝗱 𝗱𝗶𝘀𝗮𝗽𝗽𝗲𝗮𝗿.
Shiny slides don’t fix companies.
You need people who understand the workflows, constraints, and operating model of how your business actually runs.
AI can assist.
It can’t diagnose architecture.

𝟰. 𝗗𝗲𝗳𝗲𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 = 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻.
Don’t wait for regulatory moats.
Get inside the 𝗻𝗲𝗿𝘃𝗼𝘂𝘀 𝘀𝘆𝘀𝘁𝗲𝗺 of the company.
Because when you become part of the architecture…
 
You’re not a vendor.
You’re the foundation.

𝗔𝗜 𝘄𝗼𝗻’𝘁 𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀.
But companies that only 𝘦𝘹𝘱𝘦𝘳𝘪𝘮𝘦𝘯𝘵 with AI  will be replaced by the ones that 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹𝗶𝘇𝗲 𝗶𝘁.

ARE GTM problems actually GTM problems?
 
From talking to hundreds of entrepreneurs and founders, in many ways, it's a guessing problem.
 
There is no real signal on...
Who the real customer is.  
Which message will actually land.  
Which activities actually move revenue.
 
So teams stay "busy" doing.
 
Busy building decks.  
Busy running campaigns.  
Busy chasing pipeline that was never going to close.
 
You sit there thinking:
“Why the hell are we working this hard for results this inconsistent?”
 
I recently worked with a B2B SaaS founder in Europe living exactly this.
Nothing was “broken.”  
Sales were feeding the business.  
Pipeline existed and was solid to a degree.
 
I could see they were
• Chasing noise instead of signal  
• ICP signals that looked good on paper but failed out in the field 
• Pricing fighting the sales motion instead of fueling it
 
So we stopped the guesswork and realigned the GTM architecture around real signals.
 
Not theory.  
𝗥𝗲𝗮𝗹𝗶𝘁𝘆.
 
Within 60 days:
✅ 30% reduction in wasted sales activity  
✅ A stronger (and honest) pipeline  
✅ Total clarity on exactly where revenue actually comes from & why

𝗬𝗼𝘂 𝗸𝗻𝗼𝘄 𝘄𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝘄𝗵𝗲𝗻 𝗚𝗧𝗠 𝘀𝘁𝗼𝗽𝘀 𝗯𝗲𝗶𝗻𝗴 𝗴𝘂𝗲𝘀𝘀𝘄𝗼𝗿𝗸?
More signal.  Better decisions.
 
So I’m curious… How much of your GTM is actually designed, and how much of it is still guessing?

It nearly broke their company.

It wasn't a failure on their part. 
Not churn. 
Not market shifts.
𝗜𝘁 𝘄𝗮𝘀 𝗚𝗿𝗼𝘄𝘁𝗵.

Their GTM, behind the scenes, was bleeding out.

Decisions are bottlenecked at the founder. 
Process built for $5M, trying to carry $20M. 
Sales compensating for positioning that was never fully clear.

From the outside, it looked like steel. 

Inside, it was bending.

What got you to where you are today will never get you to the next stage.

Systems built for survival can’t carry expansion. 
One-off heroics don’t compound. 
Structure does.

When growth starts to feel heavy instead of energising, it’s not a motivation problem.

It’s architectural.

𝗣𝗲𝗼𝗽𝗹𝗲 carrying weights they were never designed to hold. 
𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 duct-taped instead of engineered. 
𝗣𝗿𝗼𝗱𝘂𝗰𝘁 stretched to cover strategic ambiguity.

Growth doesn’t break companies.
Unprepared structure does.

And at the next stage…  it won’t bend.
It will snap.

Overloaded

Most “revenue stage” models look neat.
$1–5M. $5–10M. $10–100M.

Nice buckets with a great curve.

Real growth doesn’t care about neat buckets.
It bends around strain.

Around $5M: founder-led sales start creaking.
Around $10M: segmentation gets messy.
Around $25M: the operating model you built at $8M simply can’t carry the load anymore.

I’ve seen it many times in other companies and my own!
The curve looks fine on paper.
Inside? Totally different

Something always snaps.

Because no one rebuilt what was carrying it.

Growth stalls because the architecture was never redesigned.

If you want to know where you really are, forget ARR for a second.

Ask yourself:
❓If you vanished for 30 days… would decisions still get made or would everything bottleneck?
❓When a big deal closes… does the team execute calmly or does Slack explode?
❓After a “great” sales month… is CS relaxed or bracing?
❓If I asked which 10 accounts are most likely to churn… would you know immediately?

That’s the pressure test.

When strain shows up, don’t optimise around it.
Don’t hire your way out.
Don’t tool your way out.
Don’t motivational-speech your way out.

Map the load.
Who truly owns revenue end-to-end?
Where does it stall?
What only works because someone heroic is carrying it?

That’s where the rebuild starts.

Growth compounds when the structure carries it.
Not when people compensate for it.

𝗜𝘁’𝘀 𝗯𝗲𝗲𝗻 𝗻𝗲𝗮𝗿𝗹𝘆 𝟭𝟬 𝘆𝗲𝗮𝗿𝘀.  
And somehow, people are still catching up

This article was written in 2016.
Let that sink in.

While most businesses are still “figuring out AI,” the signal was already there nearly a decade ago.
That’s the bit too many leaders miss.

𝗕𝗶𝗴 𝘀𝗵𝗶𝗳𝘁𝘀 𝗱𝗼𝗻’𝘁 𝗮𝗿𝗿𝗶𝘃𝗲 𝘄𝗶𝘁𝗵 𝗮 𝗯𝗮𝗻𝗴. 
They show up quietly. 
In articles. In edge cases. 
In strange little breakthroughs, people dismiss these because it all feels too early.
Until it isn’t.

That’s how businesses get caught flat-footed. 
Not because the future was invisible. 
Because they kept looking away.

𝗔𝗜 𝗶𝘀 𝗻𝗼 𝗹𝗼𝗻𝗴𝗲𝗿 𝗮𝗻 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁. 𝗜𝘁’𝘀 𝘁𝗵𝗲 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁.

And the real question isn’t whether it matters.
It’s whether your business is structurally adapting fast enough for what it changes: how people work, how decisions get made, how value gets created, and where margin disappears.

Most won’t be beaten by AI.
They’ll be beaten by leaders who moved earlier.

𝘚𝘰𝘶𝘳𝘤𝘦: 𝘑𝘢𝘮𝘪𝘦 𝘞𝘢𝘭𝘬𝘦𝘳, “𝘙𝘪𝘴𝘦 𝘰𝘧 𝘵𝘩𝘦 𝘔𝘢𝘤𝘩𝘪𝘯𝘦𝘴,” 𝘛𝘩𝘦 𝘈𝘶𝘴𝘵𝘳𝘢𝘭𝘪𝘢𝘯 (2016). 
𝘖𝘳𝘪𝘨𝘪𝘯𝘢𝘭 𝘭𝘪𝘯𝘬 𝘪𝘯 𝘵𝘩𝘦 𝘤𝘰𝘮𝘮𝘦𝘯𝘵𝘴; 𝘴𝘶𝘣𝘴𝘤𝘳𝘪𝘱𝘵𝘪𝘰𝘯 𝘮𝘢𝘺 𝘣𝘦 𝘳𝘦𝘲𝘶𝘪𝘳𝘦𝘥.  
𝘙𝘦𝘧𝘦𝘳𝘦𝘯𝘤𝘦𝘥 𝘧𝘰𝘳 𝘥𝘪𝘴𝘤𝘶𝘴𝘴𝘪𝘰𝘯 𝘢𝘯𝘥 𝘤𝘰𝘮𝘮𝘦𝘯𝘵𝘢𝘳𝘺. 𝘕𝘰 𝘢𝘧𝘧𝘪𝘭𝘪𝘢𝘵𝘪𝘰𝘯 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘢𝘶𝘵𝘩𝘰𝘳 𝘰𝘳 𝘱𝘶𝘣𝘭𝘪𝘴𝘩𝘦𝘳.

𝗪𝗵𝗮𝘁’𝘀 𝗼𝗻𝗲 𝘁𝗵𝗶𝗻𝗴 𝗶𝗻 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 people are still calling “too early” that you think will hit hard sooner than they expect?

♻️ 𝗣𝗲𝗼𝗽𝗹𝗲. 𝗣𝗿𝗼𝗰𝗲𝘀𝘀. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁
Paul “PJ” Jackson for bold GTM Strategies, Business & Sales Insights that deliver.

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