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I’ve been reading a lot about building startups and founding teams in the new AI-era. I came across the NFX article on the “3-Person Unicorn Startup” after seeing a few friends on Linkedin talking about it. If you haven’t read it, the thesis is compelling. It argues that with the leverage of Generative AI, the next billion-dollar company will be built by just three people: a CEO (the seller), a CTO (the builder), and a broad Generalist (the operator).

I love the optimism of this concept. I love solving hard problems with emerging technologies, and I thrive on the idea that small, insanely smart teams can outmaneuver incumbents.

However, I believe this model overlooks a critical organ in the startup anatomy.

The NFX framework assumes that if you can code it and sell it, you have a business. But after a decade of building companies, securing patents, and navigating the unforgiving terrain of healthcare and hard tech, I see a massive gap in this 3-person lineup.

They are missing the Experience Architect.

You need a human obsessed with design interaction and holistic optimization. If you don’t have this, you might build a technical marvel that solves the world’s biggest problems, but you will end up with a “shit product” that no one can actually use.

The Illusion of AI Competence in Design

I have built 5 companies and grown 2 of them to significant annual recurring revenue. I have successfully applied for and won 10 NIH grants, resulting in over $2 million in non-dilutive funding. In my world, which often intersects with healthcare, education, data governance, and complex hardware, “user error” isn’t just a churn metric. It is a failed clinical trial or a rejected patent.

I see founders falling into a trap where they believe AI covers the “design” vertical because it can generate CSS or copycat a landing page structure.

This is a mistake.

AI models today are incredible at execution. They can write the Python script to analyze data. They can draft the SQL query. But most AI models cannot think through the experience wholistically. They cannot navigate the infinite and often illogical permutations of user actions.

AI does not have empathy. It cannot feel the frustration of a nurse trying to input patient data at 3 AM. It cannot sense the friction a non-technical user feels when navigating a climate-tech dashboard.

AI can help with bringing in design and Product-Led Growth (PLG) best practices, but you need a human in the loop to navigate and decide.

The Missing Founder

In the NFX model, the CTO is leveraging AI to code faster. The CEO is leveraging AI to sell faster. But who is ensuring the product actually makes sense?

I believe you need one of your co-founders to be purely interaction-focused.

Alternatively, if your team is truly limited to three people, the “Generalist” cannot just be an operations person. They must be a product designer who understands systems engineering.

I have seen technically superior products fail because the interaction layer was treated as an afterthought. In the age of AI, features are becoming a commodity. The code is cheap. The logic is accessible.

The moat is no longer “can we build it?” The moat is “does using this feel like magic?”

Why Systems Thinking Matters More Than Ever

My passion for building expresses itself in two ways. I run my own startups, and I serve as a commercialization partner for other innovators. I help founders navigate the path from a raw idea to a defensible product.

When I look at my work in systems engineering and cloud infrastructure, I see that complexity is increasing, not decreasing. AI adds layers of capability, but it also adds noise.

A pure coder (CTO) often thinks in terms of efficiency and inputs/outputs. A pure seller (CEO) thinks in terms of value propositions.

The Experience Person thinks in terms of flow.

I have spoken at conferences around the world from the LoRa Alliance World Expo in Paris to TEDx in Dayton, Ohio, talking about how technology shapes the world. One constant truth I have observed is that human attention is the scarcest resource.

If you rely on AI to design your product flow, you are relying on a statistical average of what already exists. You aren’t innovating on the experience. You are regressing to the mean

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The Revised Playbook

I am not arguing against the lean startup. I have managed hardware, software, and research teams, and I know the power of keeping headcount low. But if I were building a “3-Person Unicorn” today, specifically in high-stakes markets like education, climate, or health, I would tweak the roster.

1. The Visionary/Seller (CEO): Finds the market and tells the story.
2. The AI-Augmented Builder (CTO): Orchestrates the code and infrastructure.
3. The Experience Architect (CDO/CPO): The human in the loop. The person who translates “best practices” into a specific, optimized user journey.

If you leave that third seat empty, or fill it with a generic operator, you will build a fast car with square wheels.

We are entering a golden age of building. The barrier to entry has never been lower. But the bar for user experience has never been higher.

Don’t let the AI do the thinking for you. Let it do the work. You do the design.

Book	My Reasons
The Referral of a Lifetime	I loved this book because it underscores the importance of nurturing solid and lasting relationships to generate a continuous flow of referrals for my business. The practical strategies and systematic approach Tim Templeton outlines helped me transform even casual acquaintances and satisfied customers into lifelong sources of referrals. I believe in the power of personal connections and appreciate how this approach provides a sustainable, cost-effective marketing strategy that supports my startup’s growth.
The $100 Startup	I was drawn to this book because it celebrates the entrepreneurial spirit and focuses on launching businesses with minimal capital. Chris Guillebeau’s collection of case studies and insights from people who turned their passions into profits resonated with me. I love the emphasis on lean startup principles and found inspiration and practical guidance for starting my own business on a tight budget.
The Infinite Game	My approach to entrepreneurship deeply influenced Simon Sinek’s concept of treating business as an infinite game, where the goal is longevity and continuous innovation rather than short-term wins. I believe in building a business with a long-term vision and appreciate the importance of staying adaptable and resilient.
Holstee Gift Card	Holstee is more than just a brand; it’s a community that champions mindful living and sustainability. I admire how they’ve turned the principles of the Holstee Manifesto into a tangible ethos for their products and collaborations. Their commitment to ethical practices and eco-friendly materials aligns with my belief in responsible entrepreneurship.
Coffee Catch up	Coffee on me. We can talk about anything startup.

I have been struggling to reconcile AI’s place in our lives and its existence threaded throughout the internet.

While the masses have been flocking to capture the free abundance creator of chatGPT, I’ve been hesitant and have been debating the pros and cons in close circles of friends.

After reading this article, it’s clear that I am not the only one concerned and conflicted. This is my view of the world:

1. Technology evolves societies. The creation of the internet was a significant leapfrog for humanity, connecting people from near and far and creating a shared place in the world for humans to create things.
2. Companies grew where people gathered. Focused on scale and growth, companies paid for elaborate experiences that attracted people to their spot on the internet, engaged them with interactions and human-to-human generated content, then made money.
3. Growth was limited to people. Revenue was the north star. So companies chased the dollars, and dollars came from the masses, which meant that scalability was the most important quality of an internet company. Humans have limits, but with AI companies can scale infinitely faster and cheaper with AI-generated content, code, and agents. In theory, it makes sense.
4. Everyone loves a good shortcut. The problem simply is that not everyone who generates blogs, code, or anything else on the internet is ACTUALLY trained to do that. We all take shortcuts. For example, most people who write blogs are not trained as journalists. What that means is they cut corners to create content and don’t check every detail for accuracy.
5. Trash in and trash out. Compounded on this then is that AI-systems including google’s baird and openAI’s chatgpt are trained on this inaccurate human-generated content and jumbled together with “their” understanding of the context, the output of the machine fluent, readable content that seems real enough, but is actually subtly wrong.
6. Invisible defects. An average internet user can’t tell the difference between reading something accurate or inaccurate. Also, they can’t decipher if the content was written by a human or a machine.
7. Misinformation mania. This results in the new reality of low-quality, inaccurate content (i.e. misinformation). Humans act on what they consume, and unfortunately, that content they consume has a high chance of being wrong.
8. It’s not their fault. People don’t know what they don’t know. The average internet user wants to solve their problem so they search. Yet without them knowing the validity of the information this inherent trust leads to significant risk for society.

I can’t say I am surprised that we have arrived here, but I am worried about where we are headed. It seems like the entire internet as we know it is crumbling before our feet.

There is a significant shift in how we create and I believe in the value that generative AI and AI has to support humanity, yet the “new web” is struggling to find itself and figure out who it wants to be when it grows up.