I empower leaders with AI Workshops & B2B digital strategy | LinkedIn Top Voice | Public Speaker | Board Director | Podcaster🎙️

AI won’t replace communicators, but communicators who use AI will define the future.

The communications industry is evolving faster than most teams are prepared for. Those who integrate AI today, ethically, strategically, and confidently, will lead tomorrow’s conversations.

𝗧𝗵𝗮𝘁’𝘀 𝘄𝗵𝗲𝗿𝗲 𝗜 𝗰𝗼𝗺𝗲 𝗶𝗻.

I help PR and communications leaders future-proof their teams with practical, hands-on AI strategy. Through custom workshops, audits, and advisory programs, I bridge the gap between curiosity and capability, showing teams how to integrate AI into real-world workflows without losing the human voice that makes communications powerful.

I’ve trained and advised leaders across a variety of organizations like Ragan, MacMillan Publishing, Penguin Random House, PPG, etc., helping them build AI readiness, sharpen strategy, and unlock new efficiencies in content, reputation, and storytelling.

If your team wants to:
✅ Use AI responsibly, with clear governance and guardrails
✅ Build workflow efficiencies that actually stick
✅ Strengthen credibility in an AI-driven media landscape

Then 𝗹𝗲𝘁’𝘀 𝘁𝗮𝗹𝗸. Visit chrisgee.me
or send me a message here on LinkedIn.

Don't wait to future-proof your team.

Chris Gee

Communicators used to write for journalists.

Now we also have to write for 𝗺𝗮𝗰𝗵𝗶𝗻𝗲𝘀 𝘁𝗵𝗮𝘁 𝘀𝘂𝗺𝗺𝗮𝗿𝗶𝘇𝗲 𝘂𝘀.

If your message falls apart when AI condenses it to three sentences, you have a problem.

This week I found myself saying the same thing in two different conversations with communications leaders.

More and more often, 𝗽𝗲𝗼𝗽𝗹𝗲 𝗮𝗿𝗲 𝗻𝗼𝘁 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗱𝗶𝗿𝗲𝗰𝘁𝗹𝘆.

They are reading 𝗮 𝘀𝘂𝗺𝗺𝗮𝗿𝘆 𝗼𝗳 𝗶𝘁.

AI assistants, search tools, and productivity platforms are increasingly acting as intermediaries. They scan long documents, extract key points, and present condensed answers to busy executives, journalists, and stakeholders.

Which means communicators now have a new challenge.

Your message has to survive 𝘀𝘂𝗺𝗺𝗮𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻.

If the essence of your story disappears when an AI compresses it into three sentences, you have a problem.

I mentioned this a couple times this week and realized it was worth sharing more broadly.

So in tomorrow’s, this Prompt of the Week is designed to help you test exactly that.

Use it to pressure test whether your message still holds together once an AI system distills it down.

Because communicators used to focus on how journalists interpreted our stories.

Now we also need to think about how 𝗺𝗮𝗰𝗵𝗶𝗻𝗲𝘀 𝗶𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁 𝘁𝗵𝗲𝗺 𝗳𝗶𝗿𝘀𝘁.

Curious if others are already thinking about this.

Are you designing messages that survive AI summaries?

Helping PR & Comms leaders future-proof with AI strategy | Speaker + Trainer | Keynotes + Workshops | Ragan Advisor

No alternative text description for this image

We may be approaching the saturation point for synthetic content.
We tend to assume technology spreads exponentially until it becomes ubiquitous. That’s the default narrative... 𝗮𝗻𝗱 𝗶𝘁'𝘀 𝗳𝗹𝗮𝘄𝗲𝗱.

The data suggests something more complex is happening with synthetic content on social media.

AI-generated supply is rising quickly across platforms. At the same time, we’re seeing more labeling systems, more “see less AI” controls, and a sharp increase in public conversation about “AI slop” (9x year-over-year growth in usage of that term).

In one YouTube-focused estimate, between 21–33% of a new user’s Shorts feed may already be AI-generated or low-value synthetic content.

𝗧𝗿𝘂𝘀𝘁 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗨.𝗦. 𝗮𝗿𝗲 𝗱𝗲𝗰𝗹𝗶𝗻𝗶𝗻𝗴 𝗲𝘃𝗲𝗻 𝗮𝘀 𝗔𝗜 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝘃𝗼𝗹𝘂𝗺𝗲 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝘀.

That combination matters.

When supply rises faster than trust, friction emerges.

This doesn’t mean AI content disappears. It means it meets resistance.

The research outlines three possible paths:
1️⃣ Continued acceleration
2️⃣ A plateau where synthetic content becomes common but less effective
3️⃣ Or a trust feedback loop where audiences shift toward verified creators and authenticity signals

We are already seeing early signs of an “authenticity premium,” where content that signals human authorship or limited AI use outperforms baseline synthetic volume in certain categories.

And there’s something deeper here.

Humans are biologically wired for social connection. We rely on faces, voice, and perceived intent as trust shortcuts. 

𝗪𝗵𝗲𝗻 𝗳𝗲𝗲𝗱𝘀 𝗯𝗲𝗰𝗼𝗺𝗲 𝘀𝗮𝘁𝘂𝗿𝗮𝘁𝗲𝗱 𝘄𝗶𝘁𝗵 𝘀𝘆𝗻𝘁𝗵𝗲𝘁𝗶𝗰 𝘃𝗼𝗹𝘂𝗺𝗲, 𝘁𝗵𝗲 𝗰𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗹𝗼𝗮𝗱 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝘀. 𝗣𝗲𝗼𝗽𝗹𝗲 𝗲𝗶𝘁𝗵𝗲𝗿 𝗱𝗶𝘀𝗲𝗻𝗴𝗮𝗴𝗲 𝗼𝗿 𝗴𝗿𝗮𝘃𝗶𝘁𝗮𝘁𝗲 𝘁𝗼𝘄𝗮𝗿𝗱 𝗰𝗹𝗲𝗮𝗿𝗲𝗿 𝘀𝗶𝗴𝗻𝗮𝗹𝘀 𝗼𝗳 𝗮𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰𝗶𝘁𝘆.

This isn’t anti-AI.

It’s a reminder that adoption curves bend when they collide with human psychology.

AI content will continue to grow. But growth does not automatically equal acceptance.

For communicators, the question is no longer “How much AI can we use?”

It becomes:
→ Where does AI enhance experience?
→ Where does it erode trust?
→ Where does authenticity become a differentiator?

𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝘀𝗰𝗮𝗹𝗲𝘀 𝗾𝘂𝗶𝗰𝗸𝗹𝘆. 𝗛𝘂𝗺𝗮𝗻 𝘁𝗿𝘂𝘀𝘁 𝗱𝗼𝗲𝘀 𝗻𝗼𝘁.

Curious how others are seeing this play out in their campaigns and feeds.

undefined undefined

The story around “AI layoffs” is no longer just a business headline.
𝗜𝘁’𝘀 𝗮 𝗿𝗲𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗿𝗶𝘀𝗸.

Across industries, executives are framing workforce reductions as AI-driven, even when their AI deployments are still early and delivering limited automation gains.

𝗧𝗵𝗮𝘁 𝗱𝗶𝘀𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝗳𝗲𝗲𝗱𝘀 𝗮𝗻𝘅𝗶𝗲𝘁𝘆. 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝗹𝗹𝘆 𝗮𝗻𝗱 𝗲𝘅𝘁𝗲𝗿𝗻𝗮𝗹𝗹𝘆.

When people hear “AI layoffs,” they don’t hear restructuring or strategic pivot. They hear replacement. And that perception creates a breach of trust that lingers far longer than the headlines.

💡 This is where communications leadership matters.

A few principles are critical:

✅ Name the real drivers. If it’s cost optimization or a strategic shift, 𝘴𝘢𝘺 𝘵𝘩𝘢𝘵. Don’t oversell AI as the scapegoat.
✅ Ground the change in human agency. Explain what is evolving in the work 𝘢𝘯𝘥 𝘸𝘩𝘺.
✅ Lead with capability building. Show investment in reskilling, mobility, and support systems.

The perception of an event can be more consequential than the event itself.

𝗔𝗜 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗲𝗿𝗼𝗱𝗲 𝘁𝗿𝘂𝘀𝘁. 𝗣𝗼𝗼𝗿 𝘀𝘁𝗼𝗿𝘆𝘁𝗲𝗹𝗹𝗶𝗻𝗴 𝗱𝗼𝗲𝘀.

How are leaders navigating these comms in your organization? 

Let me know in the comments! 👇🏽👇🏽👇🏽

We keep talking about AI as if it’s about to replace most white-collar workers.

𝗕𝘂𝘁 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝘀𝘂𝗴𝗴𝗲𝘀𝘁𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝘃𝗲𝗿𝘆 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁.

Researchers recently constructed what they called a “Remote Labor Index,” testing AI agents across 240 real freelance projects spanning architecture, graphic design, video production, marketing assets, and game development.

🚫 Not toy prompts.
🚫 Not lab simulations.
✅ Real deliverables companies actually paid for.

Across more than 6,000 hours of paid work worth over $140,000, the best AI agent automated about 2.5 percent of the work. 𝗠𝗼𝘀𝘁 𝗳𝗿𝗼𝗻𝘁𝗶𝗲𝗿 𝗺𝗼𝗱𝗲𝗹𝘀 𝘀𝗼𝗹𝘃𝗲𝗱 𝗹𝗲𝘀𝘀 𝘁𝗵𝗮𝗻 𝟯 𝗽𝗲𝗿𝗰𝗲𝗻𝘁.

🚫 45.6% failed on quality
🚫 17.6% produced corrupted files
🚫 14.8% included inconsistencies
🚫 35.7% produced incomplete work

These weren’t minor glitches, they were breakdowns.

𝗘𝘅𝗽𝗲𝗰𝘁𝗶𝗻𝗴 𝗔𝗜 𝘁𝗼 𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝘄𝗼𝗿𝗸𝗲𝗿𝘀 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄 𝗳𝗲𝗲𝗹𝘀 𝗹𝗶𝗸𝗲 𝗲𝘅𝗽𝗲𝗰𝘁𝗶𝗻𝗴 𝗮 𝗵𝗮𝗺𝗺𝗲𝗿 𝘁𝗼 𝗱𝗿𝗶𝘃𝗲 𝗮 𝘀𝗰𝗿𝗲𝘄.

Yes, you can re-engineer the hammer.
You can keep pouring money into improving it.
But it’ll never be as effective as a $15 screwdriver. 

They have totally different strengths and are meant to solve totally different problems. 

Global AI infrastructure investment is already in the hundreds of billions annually, with projections reaching into the trillions over the next decade.

But if the best systems can only automate 2–3 percent of real-world creative and knowledge work, 𝘄𝗲 𝘀𝗵𝗼𝘂𝗹𝗱 𝗵𝗼𝗹𝗱 𝗼𝗳𝗳 𝗯𝗲𝗳𝗼𝗿𝗲 𝗱𝗲𝗰𝗹𝗮𝗿𝗶𝗻𝗴 𝗳𝘂𝗹𝗹 𝗱𝗶𝘀𝗽𝗹𝗮𝗰𝗲𝗺𝗲𝗻𝘁 𝗶𝗻𝗲𝘃𝗶𝘁𝗮𝗯𝗹𝗲.

The math just ain’t math-ing.

The real opportunity is not wholesale worker replacement. It’s building the ideal human co-pilot.

✅ AI excels at narrow tasks.
✅ It accelerates drafting, summarizing, iteration.
🚫 But it struggles with end-to-end ownership and messy coordination.

𝗧𝗵𝗮𝘁’𝘀 𝗻𝗼𝘁 𝘄𝗲𝗮𝗸𝗻𝗲𝘀𝘀. 𝗧𝗵𝗮𝘁’𝘀 𝗱𝗲𝘀𝗶𝗴𝗻 𝗿𝗲𝗮𝗹𝗶𝘁𝘆.

The real win re: AI?

💪🏽 Human judgment + AI speed.
💪🏽 Human accountability + AI leverage.

Maybe the future isn’t about building the perfect hammer.

Maybe it’s about recognizing when the screwdriver already works better to drive screws? 🤷🏽

What do you think? Are we evaluating AI the wrong way? Let me know in the comments. 👇🏽👇🏽👇🏽

I recently joined Monica Talan on her “𝘐𝘧 𝘐 𝘖𝘯𝘭𝘺 𝘏𝘢𝘥 10 𝘔𝘪𝘯𝘶𝘵𝘦𝘴” podcast to talk about what’s actually changing in communications right now.

A few themes:

1️⃣ AI is exceptional at speeding up output. Slides, drafts, repurposing. That means our value moves to the 20 percent that drives real impact: judgment, empathy, and creativity.

2️⃣ Prompting matters. But imagination matters more. Models follow instructions. Humans decide what’s worth asking.

3️⃣ Agents are not automations. Automation is linear. Agents have autonomy. That difference is a real governance flag.

We also discussed how AI is accelerating the fractional model and why human connection becomes more valuable in a sea of synthetic content.

Just a short, 10-minute conversation. Check it out and let me know what you think! 

https://lnkd.in/ear2mzNT

AI can draft the slides.
But are we using it to think bigger?

AI expert Chris Gee breaks down where the real opportunity lives, where the risk sits, and how communicators can lead instead of react.

Get clear perspective on the future of comms in just 10 minutes...

I recently joined Monica Talan on her “If I Only Had 10 Minutes” podcast to talk about what’s actually changing in communications right now.

Not the hype.
The practical shifts.

A few themes:

The execution layer is being commoditized.
AI is exceptional at speeding up output. Slides, drafts, repurposing. That means our value shifts to the 20 percent that drives real impact — judgment, positioning, risk, and context.

Creativity beats coding.
Prompting matters. But imagination matters more. Models follow instructions. Humans decide what’s worth asking.

Agents are not automations.
Automation is linear. Agents have autonomy. That difference isn’t technical — it’s governance.

We also discussed how AI is accelerating the fractional model and why human connection becomes more valuable in a sea of synthetic content.

Short conversation. Big implications.

https://lnkd.in/ear2mzNT

The AI debate is stuck on the wrong premise.
Instead of asking “Will AI replace workers?” we may need to ask something more uncomfortable.
What happens if there simply 𝗮𝗿𝗲𝗻’𝘁 𝗲𝗻𝗼𝘂𝗴𝗵 𝘄𝗼𝗿𝗸𝗲𝗿𝘀 𝗹𝗲𝗳𝘁?

Let's look at the demographics.

Across the developed world — and increasingly in the United States — populations are aging rapidly. Birth rates are falling. Labor force growth is slowing.

The constraint may not be too many workers displaced by AI.

It may be too few workers available without it.

Think about the math:

• The U.S. fertility rate is around 1.6 births per woman, well below the replacement rate of 2.1.
• By 2034, adults 65+ will outnumber children for the first time in U.S. history.
• The worker-to-retiree ratio continues to shrink, placing pressure on productivity.

That creates a different framing.

AI isn’t just a cost-cutting technology.

It may become a demographic stabilizer.

Automation in:

• healthcare
• logistics
• software development
• design
• marketing production
• research

...could partially offset structural labor shortages rather than cause mass unemployment.

In other words:

The biggest economic impact of AI might not be replacing workers.

It might be helping societies function with fewer of them.

We may look back and realize the real question was never:

“Will AI take jobs?”

It was:

“Could our economies keep growing without it?”

Curious how others see this.
Are we underestimating the demographic side of the AI story?

Instead of asking “Will AI replace workers?” we may need to ask something more uncomfortable.
What happens if there simply 𝗮𝗿𝗲𝗻’𝘁 𝗲𝗻𝗼𝘂𝗴𝗵 𝘄𝗼𝗿𝗸𝗲𝗿𝘀 𝗹𝗲𝗳𝘁?

Let's look at the demographics.

Across the developed world — and increasingly in the United States — populations are aging rapidly. Birth rates are falling. Labor force growth is slowing.

𝗧𝗵𝗲 𝗶𝘀𝘀𝘂𝗲 𝗺𝗮𝘆 𝗻𝗼𝘁 𝗯𝗲 𝘁𝗼𝗼 𝗺𝗮𝗻𝘆 𝘄𝗼𝗿𝗸𝗲𝗿𝘀 𝗱𝗶𝘀𝗽𝗹𝗮𝗰𝗲𝗱 𝗯𝘆 𝗔𝗜.
𝗜𝘁 𝗺𝗮𝘆 𝗯𝗲 𝘁𝗼𝗼 𝗳𝗲𝘄 𝘄𝗼𝗿𝗸𝗲𝗿𝘀 𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗶𝘁.

A few numbers to consider: 

📉 The U.S. fertility rate is 𝗮𝗿𝗼𝘂𝗻𝗱 𝟭.𝟲 𝗯𝗶𝗿𝘁𝗵𝘀 𝗽𝗲𝗿 𝘄𝗼𝗺𝗮𝗻, well below the replacement rate of 2.1.
📉 By 2034, 𝗮𝗱𝘂𝗹𝘁𝘀 𝟲𝟱+ 𝘄𝗶𝗹𝗹 𝗼𝘂𝘁𝗻𝘂𝗺𝗯𝗲𝗿 𝗰𝗵𝗶𝗹𝗱𝗿𝗲𝗻 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝘁𝗶𝗺𝗲 𝗶𝗻 𝗨.𝗦. 𝗵𝗶𝘀𝘁𝗼𝗿𝘆.
📉 The 𝘄𝗼𝗿𝗸𝗲𝗿-𝘁𝗼-𝗿𝗲𝘁𝗶𝗿𝗲𝗲 𝗿𝗮𝘁𝗶𝗼 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗲𝘀 𝘁𝗼 𝘀𝗵𝗿𝗶𝗻𝗸, placing pressure on productivity.

Based on those numbers, we may be looking at this the wrong way. 

Automation in:
→ Healthcare
→ Logistics
→ Software development
→ Design
→ Marketing production
→ Research

Could partially offset structural labor shortages rather than cause mass unemployment.

In other words:

𝗧𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗲𝗰𝗼𝗻𝗼𝗺𝗶𝗰 𝗶𝗺𝗽𝗮𝗰𝘁 𝗼𝗳 𝗔𝗜 𝗺𝗶𝗴𝗵𝘁 𝗻𝗼𝘁 𝗯𝗲 𝗿𝗲𝗽𝗹𝗮𝗰𝗶𝗻𝗴 𝘄𝗼𝗿𝗸𝗲𝗿𝘀.
𝗜𝘁 𝗺𝗶𝗴𝗵𝘁 𝗯𝗲 𝗵𝗲𝗹𝗽𝗶𝗻𝗴 𝘀𝗼𝗰𝗶𝗲𝘁𝗶𝗲𝘀 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗳𝗲𝘄𝗲𝗿 𝗼𝗳 𝘁𝗵𝗲𝗺.

We may look back and realize the real question was never:

“Will AI take jobs?”

It was:

“Could our economies keep growing without it?”

Curious how others see this. 🤔

Are we afraid of the wrong thing regarding AI? 

Let me know in the comments. 👇🏾👇🏾👇🏾

𝗔𝗜 𝗷𝘂𝘀𝘁 𝗰𝗼𝗹𝗹𝗶𝗱𝗲𝗱 𝘄𝗶𝘁𝗵 𝗮𝘁𝘁𝗼𝗿𝗻𝗲𝘆-𝗰𝗹𝗶𝗲𝗻𝘁 𝗽𝗿𝗶𝘃𝗶𝗹𝗲𝗴𝗲.
𝗧𝗵𝗲 𝗼𝘂𝘁𝗰𝗼𝗺𝗲 𝗵𝗮𝘀 𝗶𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗮𝗿 𝗯𝗲𝘆𝗼𝗻𝗱 𝘁𝗵𝗲 𝗰𝗼𝘂𝗿𝘁𝗿𝗼𝗼𝗺.

A federal judge in the Southern District of New York just issued a ruling that should get the attention of anyone using AI for strategy work.

In this case, a defendant used Anthropic’s Claude to help think through a legal defense. When federal agents seized the AI outputs, he argued they should be protected under attorney-client privilege and the work-product doctrine.

𝗧𝗵𝗲 𝗰𝗼𝘂𝗿𝘁 𝗱𝗶𝘀𝗮𝗴𝗿𝗲𝗲𝗱.

The key reason: the AI interaction happened outside the direction of his attorneys. Claude is not a lawyer, and its terms of service state that user prompts may be used to train the model and may be shared with authorities. Because of that, the judge ruled there was no reasonable expectation of confidentiality.

In other words, the AI conversation was discoverable.

𝗙𝗼𝗿 𝗮𝗻𝘆𝗼𝗻𝗲 𝘄𝗵𝗼 𝗵𝗮𝘀 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁𝗹𝘆 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗲𝗱 𝘁𝗵𝗮𝘁 𝗔𝗜 𝘄𝗶𝗹𝗹 𝘀𝗼𝗼𝗻 𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝗵𝘂𝗺𝗮𝗻 𝗹𝗮𝘄𝘆𝗲𝗿𝘀, 𝘁𝗵𝗶𝘀 𝗿𝘂𝗹𝗶𝗻𝗴 𝗼𝗳𝗳𝗲𝗿𝘀 𝗮 𝘂𝘀𝗲𝗳𝘂𝗹 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝗰𝗵𝗲𝗰𝗸.

The legal system runs on relationships, responsibility, and accountability. None of those concepts map neatly onto a chat interface.

There are a few broader implications here.

1️⃣ First, AI prompts are not automatically private. If you are using public AI tools to think through strategy, assume those interactions could become part of a record.

2️⃣ Second, AI is not a substitute for privileged relationships. Legal protections rely on a human relationship and a clear expectation of confidentiality.

3️⃣ Third, this reinforces something many organizations are still catching up to: AI governance is not just about productivity. It’s about risk management.

If teams are using generative AI to explore sensitive strategy, litigation risk, or internal planning, 𝘁𝗵𝗲𝘆 𝗻𝗲𝗲𝗱 𝗰𝗹𝗲𝗮𝗿 𝗽𝗼𝗹𝗶𝗰𝗶𝗲𝘀 𝗮𝗿𝗼𝘂𝗻𝗱 𝘄𝗵𝗲𝗻 𝗮𝗻𝗱 𝗵𝗼𝘄 𝘁𝗵𝗼𝘀𝗲 𝘁𝗼𝗼𝗹𝘀 𝗰𝗮𝗻 𝗯𝗲 𝘂𝘀𝗲𝗱.

The takeaway isn’t “don’t use AI.”

It’s understand that how you use it changes the legal and reputational context around the work you produce.

Curious how others are thinking about this as AI becomes embedded in more professional workflows. Let me know in the comments! 👇🏾👇🏾👇🏾

Former GE Capital Executive | I help founders and executives see what their financials aren’t telling them.

I spent 25 years inside the machine.

GE Capital. GE Vernova. NBCUniversal. Unilever. Structured finance, capital markets, project finance across Latin America. I was the CFO who sat across from banks, governments, and Fortune 500 boards and made the numbers make sense. I closed an $800 million power plant deal. I managed capital market teams and hundred-million-dollar sales budgets. I built financial models that moved real money in real markets.

I was good at it. For a long time, that was enough.

Then it wasn't.

I stayed almost eight years past the moment I knew I was done. Eight years of golden handcuffs, institutional momentum, and not having a single person in my corner who could help me think through what leaving actually looked like -- financially, strategically, personally.

When I finally left, I made mistakes. I jumped into a startup that looked great on paper and had no financial foundation underneath it. I learned the hard way that passion without financial intelligence is just expensive optimism. Then I spent hundreds of thousands of dollars learning the things corporate never taught me -- how to sell, how to communicate with conviction, how to walk into a room and make people feel what I knew to be true about their business.

That education nearly broke me. And it turned me into something rare: a former Fortune 500 CFO who can read your financials like a surgeon reads an MRI and sit across from you like a partner who actually gives a damn.

That's what I do now.

I work with a small number of founders and executives -- people who've already built something substantial and want a strategic partner with real financial depth. Not a coach. Not a consultant recycling frameworks. Not a bookkeeper calling themselves a fractional CFO. Someone who's been in the rooms, closed the deals, read the balance sheets, and came out the other side with a clear point of view about what actually matters.

If you're a founder past $1M who can feel that the way you got here won't get you to the next level, I can show you exactly where the growth is hiding and where the model breaks.

If you're an executive who knows you're meant for something bigger than the title on your business card, I've been where you are. I made the leap. I can help you think through yours.

I don't work with everyone. I'm selective about who I take on because the work only works when both sides are all in.

One conversation is all it takes to know if we're the right fit.

Cruz Gamboa

Most founders don’t go bankrupt overnight.

They bleed slowly.
From numbers they refused to look at.

Revenue looks good.
Growth feels exciting.
Ego feels validated.

But:

➡️ Cash flow is tight
➡️ Margins are thin
➡️ One client controls everything
➡️ Burn rate is “we’ll figure it out”

That’s how businesses die.

Not from lack of ambition.
From lack of financial discipline.

Here’s the cheat sheet I wish every founder read earlier.

Ignore red flags early → pay the price later.

If you want to find your biggest 1% opportunities,
check out scalingcfo.io

Free assessment.

If this helped, save it.

Your P&L Is Hiding the Real Problem.

Most founders check 3 things:

Revenue.
Profit.
Growth rate.

Then they relax.

That’s the mistake.

Because your P&L is a scoreboard.

Not a diagnosis.

And scoreboards don’t tell you why you’re winning,
or why you’re about to lose.

Here’s what it’s not showing you 👇

If revenue is growing but cash is tight…

You don’t have a profit problem.
You have a cash flow problem.

If sales are strong but margins are shrinking…

You don’t have a demand problem.
You have a pricing or delivery problem.

If profit exists but stress keeps increasing…

You don’t have a money problem.
You have an operational problem.

Most businesses don’t collapse overnight.

They erode slowly:

➡️ Slightly rising CAC
➡️ Slightly lower margins
➡️ Slightly higher payroll
➡️ Slightly longer collections

Small leaks.

Compounded monthly.

And because the P&L still “looks fine,”
no one panics.

Until they should have.

Here’s what real operators track:

✓ Gross margin trends
✓ Cash runway (in months) 
✓ Revenue per employee
✓ CAC payback period
✓ Churn rate

Those numbers tell you where the fire is starting.

Revenue is vanity.
Profit is sanity.
Cash flow is survival.

Read your P&L.

But interrogate it harder.

Because the businesses that scale aren’t the ones with the best revenue.

They’re the ones who catch problems before they show up on the bottom line.

Your financial reports are perfect.

Clean P&L.
Accurate balance sheet.
Cash flow that ties out.

Yet decisions still feel slow, reactive, or unclear.

That’s because reports don’t create leverage.
Interpretation does.

Most founders read numbers like history.
High-performing operators read them like instructions.

Every metric should force a decision:
→ double down
→ fix fast
→ kill it

If nothing changes after reviewing your numbers,
you didn’t review them, you admired them.

This cheat sheet breaks down:

➡️ The questions that actually matter
➡️ The metrics that lie
➡️ And how to spot 1% changes that unlock outsized results

Save this before your next finance review.

cruzgamboadrive

patagonia-solar-llc

This guy bought one random car dealership.
Turned it into a $5B empire.

No fancy startup.
No venture capital.

Just one smart business move.

Terry Taylor started like most people in the auto industry:

Working inside dealerships.

Climbing the ladder.

But he realized something important:

No matter how hard you work…
You’re still building someone else’s business.

So in 1982, he bought his first dealership in Daytona Beach.

Most people would stop there.

He didn’t.

But the real genius wasn’t buying more dealerships.

It was how he structured them.

Instead of hiring managers, he:

• Gave them 20–25% equity
• Helped finance their buy-in
• Let them run the store

Now managers weren’t employees.

They were owners.

And owners think differently.

They protect profits.
They grow the business.
They care about reputation.

So scaling became easy.

1 dealership → 10 → 50 → 120+ dealerships

Today the network does $5B+ in revenue.

Simple lesson:

People work harder for ownership than salaries.

Build partners.
Not employees

If you want to find your biggest 1% opportunities,
check out scalingcfo.io

Free assessment.

If this helped, save it.

Terry Taylor

He spent 31 years running Trader Joe’s.
Mastered pricing. Supply chains. Consumer psychology.
But one thing bothered him more than anything else: food waste.

Every year, the U.S. throws away 120 billion pounds of perfectly good food.
Not unsafe. Just didn’t fit profit models.

Millions of families struggle to afford groceries.
Most CEOs see this as “business as usual.”
Doug saw it as broken design.

After retiring, he didn’t join a board. He didn’t consult.
He asked a different question:

💡 What if food waste became the foundation, not a byproduct?
What if access mattered more than margin?

✅ Daily Table is born.
✅ Grocery store built on surplus food.
✅ Affordable meals. Nutritious produce. Dignity first.
✅ No charity branding. No eligibility checks.
✅ Nonprofit by design. Every surplus reinvested in lowering prices.

Critics say it can’t scale. Doug agrees.
It wasn’t meant to dominate. It was meant to fix a failure everyone ignored.

From grocery CEO → noticing waste everywhere → building a store that feeds people, not profits.

If you want to rethink how systems work, look at incentives, not supply.
This is the anti-profit grocery model.

Daily Table

He was a waiter at Red Lobster.

He had $40.

Most people would complain. He built a $6B brand.

Here’s how:

✅ Saw a problem: kids in his neighborhood paying too much for hats.

✅ Took action: taught himself to sew, made hats at home.

✅ Scaled smart: sold locally → hip-hop stars wore FUBU → national attention.

✅ Got creative: turned his living room into a factory, raised money when banks said NO.

✅ Played the long game: built FUBU → became Shark Tank investor → mentors hundreds of startups.

Most people chase attention.
He chased problems that matter.

Critics said it wouldn’t work. He did it anyway.

You don’t need permission. You don’t need hype.
You need clarity, hustle, and persistence.

From $40 → living room hustle → global empire → Shark Tank.
That’s how legends are built

If you want to find your biggest 1% opportunities, check out scalingcfo.io

Free assessment.
If this helped, save it.

Daymond John

Most people think billion-dollar companies start with experts.

Crumbl Cookies started with two tech guys who had never baked a cookie.

In 2017, they noticed something simple:
Cookies were America’s favorite dessert, but the category hadn’t evolved.
So they focused on a few key moves:

▶ Perfected one cookie first
▶ Kept the menu simple (1 classic + 4 rotating flavors)
▶ Turned weekly flavor drops into social media events

That simple strategy turned a 900 sq ft store and $10K into

✅ 800+ locations
✅ 1M cookies sold daily
✅ $1B+ valuation

They didn’t win by doing more.
They won by focusing on the few decisions that drive everything.

That’s true in finance too.

If you want to find your biggest 1% opportunities, go to scalingcfo.io
Take the free assessments and see exactly where to focus first.

Crumbl Cookies

Some people launch snacks.
Some create global empires from leftovers.

Arch West did the second.

➡️ 1960s. Disneyland.

Casa de Fritos. Tons of stale tortillas. Wasted daily.
A small vendor saw opportunity.
“Cut them into triangles. Fry them. Add some seasoning.”

No PR. No hype. No flashy launch.

Just execution.
Just obsession.
Just seeing value where others saw trash.

1966 → Plain Doritos, national launch.
1972 → Nacho Cheese.
From leftover tortillas → multibillion-dollar snack empire.

Scaling lesson:

Opportunities are everywhere. Most ignore them.
Those who see the leverage, execute relentlessly, and scale turn accidents into legends.

Some people chase attention.
Some quietly turn scraps into billions.

#scalingup #ceo #founder #businesslessons

Doritos

$30,000 → $7 BILLION.
No hype. No fluff. Just strategy.

Dennis Washington was 30, broke, and borrowing $30k from a Caterpillar dealer.

He bought one bulldozer and started doing construction in Montana.

Within 5 years? He was the largest contractor in the state.

But he didn’t stop there.

He asked a simple question:
"Where is everyone running from?"

Then he built a formula:

✅ Buy failing businesses that everyone else ignores.
✅ Fix the basics cut costs, improve management, unlock cash flow.
✅ Use the profits to buy the next one.
✅ Repeat.

First test: a worthless copper mine.
Bought for $15M → $100M profits in 3 years.

Next: a struggling global construction firm, merged it → Washington Group International → sold for $2.6B.

Now? Real estate, aviation, railroads, marine services… a $7B empire all from turning broken things into cash.

Most people run from broken businesses. Dennis Washington built a $7B empire fixing them.

If you want to find your biggest 1% opportunities, check out scalingcfo.io

Free assessment.
If this helped, save it.

Dennis Washington

He had nothing.
No friends. Barely spoke English. ADHD made school unbearable.

At 16, he dropped out. Taught himself to code. Became obsessed with modifying video games.

At 22, he moved to Canada. New country. No network. Just a laptop and a love for snowboarding.

Started an online snowboard store → it failed.

But the software he built to run it? People wanted it.

💡 Lightbulb moment: Forget snowboards. Sell the software.

✅ Shopify is born.
✅ Made e-commerce simple.
✅ Millions of stores. 175 countries. Even Amazon switched.

From high school dropout → coding every week → building the internet’s mall worth $147B.

If you want to find your biggest 1% opportunities, check out scalingcfo.io
Free assessment.
If this helped, save it.

TOBIAS LÜTKE

Most “profitable” companies are one bad month away from dying.

Here’s why.

Profit is an opinion.
Cash is oxygen.

You can look profitable on paper and still miss payroll.
I’ve seen businesses doing 7 figures collapse because one client paid late.

Revenue doesn’t matter if:

• It’s delayed
• It’s unpredictable
• It’s already spent in your head

Growth makes this worse.

You hire early.
Lock in fixed costs.
Sign long-term tools.
Upgrade lifestyle.

Now your burn is permanent…
…but your income isn’t.

That’s the trap.

Another hard truth:
If the founder steps away and sales stop, you don’t have a business.
You have a high-stress job with employees.

Margins won’t save you.
Busy won’t save you.
Brand won’t save you.

Only cash flow will.

Simple rules that keep companies alive:

• Collect faster than you spend
• Keep fixed costs boring
• Build 3–6 months of runway
• Systems before scaling
• Liquidity before vanity growth

The strongest businesses aren’t the loudest.

They’re the ones that can survive a bad month without panicking.

That’s real leverage.

Peter Steinberger could have built “cool” software.

He didn’t.

He built useful software.

PDFs were everywhere. Developers were stuck with messy workflows. Peter asked:

What if developers had tools that just worked? That solved real problems, not just looked good on a portfolio?

✅ PSPDFKit → powers PDF apps across mobile & web.
✅ Open-source projects → simplify workflows, save engineers hours.
✅ OpenClaw → personal AI agent that actually helps you code.

Most people chase attention. Peter chases problems.

Critics say niche tools won’t scale. Peter doesn’t care.
He’s not in it for hype. He’s in it for impact.

From engineer → spotting friction everywhere → building tools that make developers’ lives better.

If you want to build something meaningful, solve real problems.
The market rewards results, not ideas.

If you want to find your biggest 1% opportunities, check out scalingcfo.io

Free assessment.
If this helped, save it.

Peter Steinberger

Most founders don’t fail overnight.

They bleed slowly.
From decisions they ignored.
From processes they never set.
From metrics they refused to measure.

Revenue looks fine. Growth feels exciting. Ego feels validated.

But underneath:

➡️ Decisions get delayed → chaos spreads
➡️ Processes depend on you → hero culture burns out
➡️ Metrics are “nice to have” → guesswork rules
➡️ Accountability is optional → everyone points fingers

That’s how scaling dies.

Not from lack of ambition.
From lack of rules.

If you want to find your biggest 1% opportunities, check out scalingcfo.io

Free assessment.
If this helped, save it.
#scalingup #founders #ceo

Most people saw a ping pong table.

Max Koehler saw a business.

In 2019, he noticed something strange:

Table tennis is one of the most played sports in the world,
but in U.S. cities there were very few places to play regularly.

Most founders would open a traditional club.

Max built PingPod instead.

Small glass studios.
Open 24/7.
Booked entirely through an app.
No staff. No front desk.

But the real genius?

A camera above every table.

Every rally gets recorded.
One tap → instant replay → share on social.

Players created the content.
The content created the marketing.

Clips went viral.
Bookings exploded.

Today PingPod is valued around $40–60M.

All from one simple observation.

The best founders don’t just build products.
They build systems that grow themselves. 🚀

If you want to find your biggest 1% opportunities, go to
scalingcfo.io

Take the free assessments and see exactly where to focus first.

#scalingup #founders #CEO

Max Koehler

The trillion-dollar scoreboard isn’t just impressive.

It’s a warning. ⚠️

AI is no longer a feature.
It’s infrastructure.

Distribution beats product.
Platforms compress margins.
Specialisation scales faster than breadth.

And the giants NVIDIA, Microsoft, Alphabet, Amazon, Meta, Apple aren’t just companies anymore.

They’re rails.

If you’re a $1M–$10M founder, here’s the real play:

➡️ Build on top of giants, don’t compete with them.
➡️ Own your audience, don’t rent it.
➡️ Go narrow, dominate a micro-niche.
➡️ Push recurring revenue.
➡️ Move faster than anyone with a board meeting.

The economy is consolidating at the top.

But execution speed is still decentralised.

That’s your edge.

If you're building between $1–$10M and want to scale intelligently, not just aggressively

Come to the workshop → https://lnkd.in/efBiFQRg

I keep having the same conversation.

Founder calls me. Revenue is up -- sometimes way up. 

But they're taking home less than when the business was half the size. 

They hired the consultants. They wrote the plan. They pushed harder on sales. And somehow the business keeps snapping back to the same number like a rubber band.

After sitting across from enough of these founders, I started seeing the pattern. It comes down to three things nobody wants to talk about -- and none of them have anything to do with selling more.

I broke it all down in this week's newsletter.
#scalingup #founders #growth #CEO

I talk to a lot of founders. Like, a LOT. And something keeps coming up that I can't ignore anymore. Almost every conversation -- doesn't matter what 

Open article: The 3 things nobody tells you about getting stuck by Cruz Gamboa • 5 min read

The 3 things nobody tells you about getting stuck

LVMH is worth $292.9 billion.

You're worth $10M and stressed about payroll.

Same industry. Completely different money game. Here's why.

I've sat inside dozens of $5M–$50M businesses as a fractional CFO.

The pattern never changes.

Founders confuse 3 separate problems:

❌ "We have a cash flow problem."

No. You have a timing problem. Revenue is fine. Your money is just in the wrong place at the wrong time. That's fixable in 90 days.

❌ "We have a scaling problem."

No. You tried to grow before your operations could hold the weight. Every single time. Growth didn't break you, the lack of systems did.

❌ "We have a fundraising problem."

No. Investors don't fund vision. They fund numbers that prove the vision is real. You don't have a pitch problem. You have a financial story problem.

Now look at the billion-dollar brands:

Inditex built Zara to $193B by selling inventory before the bill came due.

Hermès built $235B by turning scarcity into a balance sheet strategy.

Fast Retailing scaled Uniqlo globally because they built finance infrastructure first.

None of that is luck.
All of it is decisions, financial decisions dressed up as brand decisions.

The difference between them and you isn't capital.

It's that they stopped running on gut feel and built a machine that tells them exactly where every dollar is going, and why.

You don't need a $500K CFO on payroll.

You need 10 hours a month of the right financial brain in the room.

That's the actual arbitrage most $5M–$50M founders are sleeping on.

If your finances are running you instead of the other way around,

Comment "CFO" below and I'll show you exactly where to start.

99% of founders do this backwards.

They try to scale a business
that no one has proven they want.

Then they try to sell a business
that only works because they exist.

Here’s the real order:

1. Start
Don’t build the product.
Sell it first.

If no one pays, it’s not a business.
It’s a fantasy.

2. Scale
Do less. Better.
One offer. One audience. One channel.

Systemize everything.
If it needs you to survive, it’s not scalable.

3. Sell
Buyers don’t pay for hype.
They pay for predictable cash flow.

Clean books.
Recurring revenue.
Low founder dependency.

Start with proof.
Scale with systems.
Exit with leverage.

That’s how you build something that prints money, not something that prints stress.

If you want to find your biggest 1% opportunities,
check out scalingcfo.io

Free assessment.

If this helped, save it.

Most founders don’t have a growth problem.
They have a focus problem.

Their dashboards are full.
Their results are not.

Tracking more KPIs doesn’t make you smarter.

It just gives you more ways to avoid the hard decision.

Here’s how serious founders think about metrics:

If a number doesn’t change what you do this week,
it doesn’t belong on your dashboard.

That’s why the only startup metrics that actually matter answer 4 questions:

1. Is demand growing?
2. Are customers staying?
3. Are they paying more over time?
4. Are we running out of cash before we figure it out?

Everything else is noise.

The best operators I’ve seen track 5–7 metrics max.
They review them weekly.
And they tie each metric to a clear action.

Everyone tracks KPIs.
Very few track the right ones.

If you want to find your biggest 1% opportunities,
check out scalingcfo.io.

Free assessment.

If this helped, save it.

The Hidden Cost of Optimism in Your Financials

Optimism doesn’t build businesses.

Cash flow does.

Here’s how optimism quietly kills companies:

1. Optimism delays action
“I’ll hire a CFO at $10M.”
No.
You’re stuck at $3M because you didn’t.

2. Optimism ignores the downside
You planned for the average outcome.
Business gave you the worst one.
That’s not bad luck. That’s bad planning.

3. Optimism spends future money
You’re spending like next quarter’s revenue is guaranteed.
It isn’t.
Hope doesn’t clear payroll.

4. Optimism hides leaks
2% margin loss feels small.
Until it happens across 4 lines.
Now you’re bleeding 8% and wondering why growth feels hard.

5. Optimism skips the buffer
No cash reserve isn’t confidence.
It’s arrogance.
Survivors don’t guess right, they prepare longer.

6. Optimism assumes peak performance
Your model requires you to crush it every quarter.
You won’t.
Systems beat motivation. Every time.

7. Optimism creates fragile plans
If losing one client breaks your business,
you don’t have a model.
You have a wish.

8. Optimism avoids hard calls
Cutting bad products.
Renegotiating vendors.
Walking away from “almost profitable” deals.
These feel bad.
They work.

9. Optimism makes scaling harder
The best founders plan pessimistically
and execute aggressively.
Everyone else just “stays positive” until reality shows up.

Here’s the truth:
Real confidence isn’t thinking things will work out.
It’s knowing your numbers so well
you can survive when they don’t.

taplio

The Battle

Chris Gee

Cruz Gamboa

Followers

Posts

Engagements

Likes

Performance ScoreChris Gee's LinkedIn Performance

Performance ScoreCruz Gamboa's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Chris Gee

Cruz Gamboa

Followers

Posts

Engagements

Likes

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

Performance ScoreCruz Gamboa's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreChris Gee's LinkedIn Performance