In this video I look at what AI is doing to our mindset. Not to our productivity. Not to our workflows. To the way we think about ourselves and our work.
With nearly anybody I speak to these days, the conversation very quickly goes to AI and what is happening. There is a shared sense that something big is unfolding, and with that comes a very specific kind of pressure: where is my brilliant AI unicorn idea?
I wrote about catching agentic fever a few weeks ago. That was about the burnout. This is about the AI mindset underneath it. The beliefs about what you should be doing with this technology, who is winning, and what it means if you are not keeping up.
There are only two games you can play. And most people are playing the wrong one.
Bring your own metrics means refusing the success criteria a platform or technology defines for you and defining your own instead. Depth, resonance, real business outcomes over vanity numbers.
The blue ocean trap: why every AI wave creates the same AI mindset crisis
We have seen this before. Every time there is a new technology, there is a blue ocean of possibility, and great entrepreneurs do incredible things and capture enormous value.
We had the companies that saw the microprocessor. Intel, Microsoft, Apple. Then we saw the companies that understood the internet. PayPal, Stripe, Amazon. AI is another blue ocean, and we are already seeing what it enables. The one person unicorn. 10x agencies. New business models we could not have imagined two years ago.
So we feel this pressure. I have this new tech, where is my brilliant unicorn idea? And what we have here is a typical blue ocean. It is high risk. High reward. And the odds are against you. How many companies tried to sell stuff on the internet before Amazon? How many people tried to do streaming video before YouTube? Countless failures behind every success story.
Most of the AI companies are already there. You can look at the labs. OpenAI, Anthropic. Or behind the labs at Nvidia. Or behind Nvidia at TSMC that produces chips. There is already a value chain and there is already an economy. They do not create agents. They create the infrastructure for agents.
MIT Sloan’s research on generative AI and entrepreneurship points to the same thing: the clearest value for entrepreneurs lies in streamlining work they already do, not in reinventing what their business is.
This is the trap. The AI mindset that the technology wants you to have is: build something radically new or you are falling behind. The AI mindset that actually works is different.
The AI mindset shift: bring your own metrics
Let me trace a parallel with something we know about. YouTube.
YouTube gamifies everything. Views going up. Going down. Watch time. Impressions. Click through rate. And then they do something really evil. They rank me one out of ten. Against myself. My best video of the month. Against myself. That is pure evil.
If I accept these metrics, then I am playing an advertising game. Entertainment and advertising. And we know it is possible to win. We all have the leading influencer of every vertical in our feeds. But the odds are slim.
And then what happens when you do get the views? The money from advertising is not enough to sustain you. So you start selling advertising within the video. Sponsored videos. Then courses. Then school groups. Free groups. Paid groups. I know about these things because I have done all of them. When they were cool.
So you have two types of pressure. How do I keep growing? And how do I monetize this audience? Sound familiar? It is the same pressure AI is putting on founders right now. Grow or die. Monetize or miss the window.
What if we brought our own metrics instead?
My channel is called Think with Matteo Cassese. So depth, reflection, resonance. These are the things that matter to me. When I look at the dashboard with different eyes, I see 442 likes. 119 comments. If my metrics are reflections, thinking, interactions, brand, this is a really successful video. Not because of views and impressions and average view duration.
Bring your own metrics in practice: three stories
The 149 view documentary
I have a two hours, eight minutes, one second documentary of me working at the farm with my client, Sophie. It has the grand total of 149 views.
Is this good or bad? This is great. It is more than one. This video exists. This video is on brand. And if the right person watches it, they might become a client. If it already does something for them, even better.
The 128 view video that became a year long partnership
I have a video where I explain the storytelling pitch framework in a very simple way by teaching you how to do proper Italian carbonara pasta. 128 views. Some people will discard this video. Didn’t perform.
But there is one comment. After that comment, Mr. Osmond reached out to me and we started a coaching path. That coaching path brought us to partner on a project. Now, one year later, we are working together.
This is what happens when you bring your own metrics. A video with 128 views generated a year long client relationship. By YouTube’s metrics, it failed. By mine, it is one of the most successful things I have ever published.
The SEO agent and the outreach CRM
On the AI side, I take the same approach. Not creating a company based on the possibilities of AI. Looking at what AI can do for my company.
I created a CRM process for myself. It is really just a research and drafting agent. It goes out, knows what kind of conference I want to speak at, finds who is the person selecting the speakers. Then I get directly into Gmail a draft of how I would reach out to that conference. If I had spent the 30 to 40 minutes to research them. This happens in two to three minutes.
I also created an SEO agent. I took an agent and coached it. I teach it everything it needs to know about semantic SEO, semantic GEO, and the work I have already done creating my own knowledge graph with WordLift. Now this agent together with me is optimizing all of my pages in a time that I literally did not have before.
I am not going to create the next PayPal. Sorry. I am just doing more through my own way of working. It is low risk. It is low pressure. And it is fully aligned with who I already am.
Finite and infinite games: the AI mindset framework
James P. Carse wrote about finite and infinite games. A finite game has fixed rules, clear winners and losers, and an endpoint. An infinite game is about continuing to play.
Playing the game the technology defines for you is always finite. You are always boxed in. These are the YouTube metrics. This is what you should follow. These are the AI benchmarks. This is how fast you should ship.
Playing your own game is infinite. Maybe this company and this offer, how it exists now, will not exist next year. But I have been at the game of being in work somehow for 30 years. I have been in the game of being a freelancing solopreneur for 15 years. Channels will change. Technologies will change. But hopefully I am going to be still enthusiastic and still going to be there.
Harvard Business Review’s research on AI strategy makes the same point from the organizational side: AI strategy must be calibrated to what you actually do today, not to a blue ocean that may not exist for you.
The external approach asks you to perform from the outside. Show your metrics. Show how you can create something completely, radically new in a blue ocean way. Be disruptive or be irrelevant.
The inside out approach asks something different. Know deeply who you are. Know what you do. Then figure out which new tools serve that. You are not building an AI company. You are using AI for your company. If it works, great. If a specific tool does not work, you try another. You stay in the game.
How to know which game you are playing
Three questions that cut through the noise.
Am I chasing a possibility that the technology created, or am I solving a problem I already understood?
Would I still want to do this work if the AI hype disappeared tomorrow?
Are the metrics I am optimizing for mine, or did a platform hand them to me?
If you answer honestly, you already know which game you are in. The founders I work with through one to one coaching often arrive at this exact point. Not with strategy questions. With questions about what kind of operator they want to become.
What people are saying
When I posted this video, one comment stood out. Sean wrote: “If you are pursuing an unusual thread in your life, getting your message to six or seven involved and interested people can saturate the entire planet with your message.”
That is bringing your own metrics in one sentence. Not ten thousand views. Six or seven of the right people.
The real question
The real question is not what can AI do.
It is: are you going to play their game, or your game?
Take the Leverage Assessment to find out which game you are playing right now.
FAQ
What does “bring your own metrics” mean?
It means you stop measuring your work by the success criteria a platform or technology hands you and start measuring by what actually matters to your business. Depth over reach. Resonance over impressions. A 128 view video that generates a year long client partnership is worth more than a viral hit that converts nobody.
What is the right AI mindset for founders?
The AI mindset that works is inside out. You start with who you are and what you already do well. Then you use AI to speed that up. Not the other way around. Founders who chase AI possibilities before grounding in their own expertise end up with agentic fever. The ones who bring their own metrics end up with more of what they actually want.
What are finite and infinite games in business?
Finite and infinite games is a framework from philosopher James P. Carse. A finite game has fixed rules, a clear winner, and an endpoint. An infinite game is about continuing to play. In business, chasing a platform’s metrics or a technology’s blue ocean is finite. Building from who you are and adapting your tools as they change is infinite. The founders who last decades play infinite games.
Should I build an AI company or use AI for my company?
If you have a brilliant idea and deep domain expertise, build the company. But know that most of the value chain is already there. OpenAI, Anthropic, Nvidia, TSMC. For most founders, the lower risk, higher alignment path is using AI to speed up what you already do. Research, outreach, content, operations. You are not creating the next PayPal. You are doing more through your own way of working.
How do I know if I am playing someone else’s game?
Ask yourself three things. Am I chasing a possibility the technology created, or solving a problem I already understood? Would I still want this work if the hype disappeared? Are the metrics I optimize for mine or handed to me by a platform? If you are honest with those answers, you will know.
