The Founder's Paradox, Too Big Teams, The Future of Work with AI Agents, and Pricing AI Software
In today’s rapidly evolving tech landscape, founders face a unique set of challenges—what I call the Founder’s Paradox. We’re told to dream big, scale fast, and build teams, but at what point does growth start to hinder progress instead of fueling it?
The Founder’s Paradox
Every founder wants to build something lasting. Yet, as companies grow, founders often find themselves caught between two conflicting forces: the need for speed and the need for structure. Move too quickly, and you risk chaos; move too slowly, and you lose momentum. The real challenge is knowing when to push for scale and when to double down on focus.
Teams Too Big to Think
There comes a point when teams become so large that decision-making slows and creativity suffers. In my experience, the most innovative breakthroughs happen in small, tightly-knit groups where everyone feels ownership. As teams grow, communication overhead rises, and alignment becomes harder. The solution? Optimize for enthusiasm—build teams around motivated individuals and keep them small enough to move fast.
There comes a point when teams become so large that decision-making slows and creativity suffers. In my experience, the most innovative breakthroughs happen in small, tightly-knit groups where everyone feels ownership. As teams grow, communication overhead rises, and alignment becomes harder. The solution? Optimize for enthusiasm—build teams around motivated individuals and keep them small enough to move fast.
There comes a point when teams become so large that decision-making slows and creativity suffers. In my experience, the most innovative breakthroughs happen in small, tightly-knit groups where everyone feels ownership. As teams grow, communication overhead rises, and alignment becomes harder. The solution? Optimize for enthusiasm—build teams around motivated individuals and keep them small enough to move fast.
The Future of Work with AI Agents
AI agents are rapidly changing the way we work. Instead of replacing humans, the best AI tools augment our abilities, freeing us from repetitive tasks and allowing us to focus on higher-level thinking. In the near future, every team will have AI “colleagues” working alongside them, handling everything from scheduling to data analysis. The companies that thrive will be those that seamlessly integrate AI into their workflows.
Software Is Changing (Again)
The shift toward AI-native products is reshaping the software landscape. Traditional SaaS models are being challenged by tools that learn, adapt, and automate. To stay ahead, founders need to embrace experimentation and be willing to rethink their product strategies from the ground up.
How to Price AI Software
Pricing AI software presents its own set of challenges. Usage-based models are gaining traction, but the key is to align pricing with the value delivered. Think in terms of outcomes, not features. Customers will pay for results—faster insights, better predictions, more automation—not just another dashboard. There’s a metric I keep coming back to: user enthusiasm. Are people excited to use your product every day? Do they tell their friends and colleagues about it? Enthusiasm is contagious, and it’s the best indicator of long-term success.
What Is an AI-Native Company?
An AI-native company doesn’t just use AI—it builds its DNA around it. From hiring and training to product development and customer support, every aspect is designed to leverage AI’s strengths. These companies move faster, adapt quicker, and deliver more value.
MCP Is the New WWW
Just as the World Wide Web transformed business in the 1990s, Multi-Agent Collaboration Platforms (MCPs) will redefine how teams operate in the age of AI. The future belongs to those who can harness the collective intelligence of humans and machines working together.