Tiago Forte's latest video sparked something. Here's what his framework looks like from inside the lab, and why "we help clients with AI" is not a positioning.
I've watched this movie before.
When the web first came along, you could stand out because you were one of the first to use it. Then everyone else caught up, and the tools got easier. When "digital transformation" became the thing, early movers had an edge. Until every firm was doing it (and honestly, the tools never really caught up on that one, but the herd stampeded anyway).
Now it's AI. And right now, if you're an early adopter who isn't afraid to figure things out, you've got an advantage. Enjoy it. It has a shelf life.
Because two things are about to happen. Again. Every firm is going to be helping their clients deploy AI. And some big platforms are going to build micro-layers that weave AI through enterprise systems in ways that make today's custom implementations look quaint. Is the window where "we do AI" a differentiator? Three to five years, maybe.
This is the part that matters for everyone, whether you're running an agency, building a career, or just trying to figure out where to invest your time:
AI proficiency is a commodity on a timer. The human skills underneath it are the actual assets.Tiago Forte dropped a video last week called "The Career Skills AI Will Never Replace" that crystallized this beautifully. His central idea: AI is collapsing the cost of cognitive labor. Everything that can be automated, scaled, or generated is racing toward zero. But AI can't do everything effortlessly? That's about to become dramatically more valuable.
He's right. Go watch it. It's seven minutes, and it reframes how you should think about your career.
What I want to do here is take his framework and run it through something messy and real: the daily experience of building AI solutions across multiple businesses and a household of 11. Because I've been living inside this shift for months, watching specific skills become less valuable in real time while others explode in importance.
Tiago gave us the map. I want to show you what the terrain actually looks like. And for my fellow agency owners, I want to have an honest conversation about what this means for how we position our firms.
The Cognitive Labor Reversal Is Happening Faster Than You Think
Tiago frames this beautifully. For generations, the more specialized your cognitive labor, the more valuable it was. Now that equation is flipping. Specialized knowledge that can be captured in text, data, or patterns? AI eats that for breakfast.
I see this every week at Rocket Media. Tasks that used to take my team hours (first-draft copy, competitive research summaries, initial SEO analysis) now take minutes. The World Economic Forum's Future of Jobs Report 2025 confirms this at scale: nearly 40% of core job skills will need to change by 2030, with AI and big data topping the list of fastest-growing skill demands across industries.
But here's what I've noticed from the builder's seat: the skills that are exploding in value aren't abstract categories. They're capabilities you develop by doing real work alongside AI and noticing where it falls apart.
I've been keeping a running list. Every time AI fails me, truly fails, not just gives a mediocre answer, I write down what human skill saved the situation.
That list has become one of the most valuable things I own. Here's what's on it.
Problem Framing: The Skill That Makes Everything Else Work
Tiago nailed this one. He said we need to shift from working on answers to framing the right questions. I want to show you how dramatically true this is.
Last month, a client came to us frustrated that their "AI marketing strategy" wasn't working. They'd been feeding ChatGPT prompts like "write me better ads" and wondering why nothing improved.
The problem wasn't the AI. The problem was the question.
When we sat down and actually diagnosed their situation, through conversation, not prompts, we discovered their positioning was broken. They were targeting the wrong customer segment entirely. No amount of AI-generated copy was going to fix a fundamentally misframed problem.
I'm building a conversation-to-strategy system at Digital Ignitor specifically because of this pattern. The AI handles the extraction and analysis beautifully once you point it in the right direction. But figuring out which direction to point it? That's the human skill that's becoming worth more every month.
Microsoft's research backs this up. Their 2025 study of 200,000 Copilot users found that in 40% of conversations, what users wanted to accomplish was completely different from what the AI actually did. The gap between intent and execution is where human problem-framing lives, and it's not shrinking.
Taste and Judgment: Knowing What "Good" Actually Looks Like
Tiago talked about using AI for first drafts and spending more of your effort on the final polished version. That resonated with me, and I want to build on it, because the skill this requires is more nuanced than it sounds.
I call it the "Is this actually good?" problem.
AI generates content that looks professional. It hits the right structure, uses appropriate vocabulary, and flows logically. And about 60% of the time, it's mediocre dressed up as competent.
At Rocket Media, we use AI for first-draft content constantly. But the team members who've become indispensable aren't the ones who write fastest. They're the ones who can look at an AI output and immediately sense what's off. The tone that's slightly wrong for this specific client. The argument that's logically sound but emotionally flat. The structure that follows "best practices" but buries the actual insight.
This is taste. And taste comes from experience, exposure, and caring deeply about quality. Things that can't be trained into a model.The World Economic Forum found that creative thinking is the fourth most in-demand skill globally and is growing faster than almost any other skill, particularly in industries you wouldn't expect: insurance, education, and telecommunications. Not because these industries suddenly need more artists. Because they need people who can evaluate, curate, and refine what AI produces.
Developing the judgment to know what good looks like. That's the skill AI can't learn from your data.
Tacit Knowledge: What Your Body Knows That Data Can't
This is the one from Tiago's video that hit me hardest. He used the example of a surgeon who knows something's wrong before the monitors show it, or a manager who can sense burnout two weeks before anyone says anything.
I live this one daily, on both the business and family side.
My wife (who honestly runs most of our household) can walk into a room and know something's wrong with one of our kids before anyone says a word. Body language, energy, and the specific quality of silence. She's not analyzing data. She's reading a situation with decades of accumulated human pattern recognition.
I see the business version constantly. Last month, I was on a sales call for Rocket Media, and about ten minutes in, I could feel the prospect's energy shift. Nothing in their words changed. They were still saying positive things. But something was off. I adjusted my approach, addressed a concern they hadn't voiced yet, and saved the deal.
No AI transcription or sentiment analysis would have caught that. I know because I ran the call recording through one after the fact. AI scored the entire conversation as "positive engagement." It missed the moment completely.
When AI can instantly access every fact, every best practice, every framework, the person who wins is the one who knows things that aren't in any database. Things learned through years of reading rooms, building relationships, and making mistakes that taught lessons no textbook covers.
Relational Trust: The Moat AI Makes Wider
Tiago raised something important about investing in deeper relationships over wider networks, and about creating physical, in-person experiences. I want to expand on this because it's playing out in my businesses in ways that surprise me.
At Modern Moments, our wedding venue, couples are making one of the most emotional purchasing decisions of their lives. I've tested AI for follow-ups, scheduling, and FAQ responses. It works fine for logistics. But the moment a bride calls with anxiety about her wedding day? AI is useless. Not because it can't generate empathetic language, it can. But because the bride doesn't want empathetic language. She wants a human who cares.
AI is making the digital world more efficient. That's simultaneously making the physical, relational, analog world more rare, and therefore more valuable.
If your business can deliver genuine human presence, not just "customer service" but actual care, you're building a moat that AI makes wider, not narrower.
Cross-Domain Pattern Recognition: One I'd Add to the Conversation
Everything above builds on Tiago's framework. This one I want to contribute from my own experience, because I think it's one of the most underrated skills in the AI era, and it's something my unusual life circumstances have taught me a lot about.
AI is exceptional at finding patterns within a dataset. It's not great at connecting insights across unrelated domains, the kind of thinking that happens when you're building a family scheduling system and suddenly realize the architecture solves a problem in your client onboarding workflow.
I experience this constantly. My pool chemistry diagnostics project taught me something about how to structure client data analysis. The vehicle maintenance tracking system I built shares architecture with business asset management. What I learned about emotional decision-making at our wedding venue completely changed how I approach consumer marketing at Rocket Media.
These cross-domain leaps happen because I'm operating in wildly different contexts simultaneously. AI can't do this because it doesn't live across contexts. It processes whatever you feed it, one conversation at a time. It doesn't have the experience of building a treehouse with your kids and suddenly understanding something about project scoping that you couldn't see when you were staring at a Gantt chart.
This is why I believe the future belongs to curious generalists who go deep in multiple areas, not hyper-specialists optimizing one narrow domain. The specialists' knowledge is exactly what AI replicates most easily. The generalist's ability to connect dots across domains? That's something AI can't touch.
Emotional Regulation Under Uncertainty: Leading When the Map Disappears
Tiago mentioned emotional intelligence and self-awareness as critical skills. I want to get specific about one dimension that I think deserves its own spotlight: the ability to stay calm and make good decisions when you genuinely don't know what's going to happen.
AI is confident. Dangerously, consistently confident. It will give you a plan, a framework, a recommendation with the same tone, whether it's brilliant or completely wrong.
The human skill that matters is knowing when to trust the AI-generated plan and when to throw it out. And more importantly: staying regulated enough emotionally to make that call clearly, especially when the stakes are high, and the data is ambiguous.
I'm not great at this yet, honestly, I'm still figuring it out. Running multiple businesses means I face genuine uncertainty daily, and the temptation to let AI make the decision "because it processed more data than I could" is real. But the times I've overridden my gut in favor of AI's recommendation? Those are some of my most expensive mistakes.
The WEF report lists "resilience, flexibility, and agility" as one of the fastest-growing skill demands globally. That's a clinical way of saying:
the world needs people who can hold steady when everything is uncertain, make judgment calls with incomplete information, and adapt when those calls turn out wrong.That's not a skill AI develops. It's a skill humans develop through struggle, failure, and practice.
An Honest Word for My Fellow Agency Owners
Everything above applies to anyone building a career. This section is specifically for those of us running marketing agencies, because I think our industry needs to hear something it doesn't want to hear.
We help clients deploy AI" is not a positioning. It's a service offering. And it's a service offering with a timer on it.
We did it with websites. We did it with social media. We did it with "digital transformation." And we're doing it again with AI. The pattern is always the same: early movers get a real advantage, the herd catches up, and suddenly everyone's competing on price for the same undifferentiated service.
Right now, there's genuine demand for helping clients deploy AI. That's good. Take the money. But if you're building your entire firm identity around "AI implementation," you're building on sand. The same positioning principles that were true before AI still apply:
the firms that win will help a specific kind of client deploy AI, not every client deploy AI.Here's what I think the honest promise should sound like:
Client, our job is to get you to the place where you don't need us for the same things anymore. We know that most of you have some in-house capability, and those folks aren't our competition. We're here to guide from an outside, objective position and to make their jobs easier.
Bringing clients up to speed on AI is a service offering that falls underneath a positioning. It's not the positioning itself. And this window, where being AI-capable is a differentiator, lasts maybe three to five years. After that, every agency will claim AI capability the way every agency now claims to "do digital."
The firms that will thrive long-term are the ones investing in the human skills I listed above: problem framing, taste, tacit knowledge, relational trust, cross-domain pattern recognition, and emotional regulation. Those aren't commodities on a timer. They're compounding assets that get more valuable as AI makes everything else cheaper.
Build AI services. Absolutely. But build them on top of a positioning that would survive even if every other agency had the same AI tools you do. Because in a few years, they will.
From Framework to Action
Tiago's video is a great starting point for thinking about where to invest in your career. What I've tried to do here is add the ground truth, what this looks like from inside the lab, from someone building with AI daily across businesses, home, and family.
The pattern I keep seeing:
AI makes you faster at the things that are becoming commodities. The skills that actually matter are the ones you develop by being human in complex, messy, real-world situations.If I could distill this into three things worth doing this week:
1. Build something with AI. Not "use AI" — build. Take a real problem in your work or life and prototype a solution. You'll immediately discover where AI excels and where your human skills fill the gap. That experiential knowledge is worth more than every think piece on this topic combined.
2. Start documenting where AI fails you. Every time it lets you down, write what happened and what human skill saved the situation. In six months, you'll have a personal map of exactly which capabilities to develop. Mine include judgment under ambiguity, relationship repair after miscommunication, and cross-domain pattern recognition.
3. Go deeper in one relationship this week. Not wider — deeper. Have a real conversation. Show up in person if you can. In a world where AI handles the transactional, the relational becomes the rarest and most valuable currency you have.
Tiago Forte's video is worth your seven minutes; he frames the big picture with the clarity he's known for. My goal here was to add the view from the trenches. If you're figuring out where to invest in your own skills or your firm's future, I hope seeing both the framework and the ground truth helps you find your path.
What skills are you noticing AI can't replace in your work? I'd love to hear. I'm still building my own list.
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