From Static to Dynamic Software

There has been this SaaSpocalypse discussion bouncing around public market and private equity investment committees throughout 2026. I believe it’s the wrong way to view AI Disruption Risk.

It’s not about SaaS versus AI-Native, it’s about Static vs Dynamic software.

This shift has been made real, and is becoming ever more real by the day.

OpenAI and Anthropic built a platform for dynamic software while the rest of the industry continues to build on static software foundations.

The difference is cycle times.

For example, recursive self-improvement and continuously updating software like Biologic Intelligence reduces the time between training, learning, and updating the model from years, months, days, hours, minutes, to every moment in time.

When the neural network, much like the human brain, is learning and adapting, the weights and the connections between neurons are constantly changing. They either make new connections or remove old connections, and strengthen or reduce the intensity of those connections.

What does this mean for your business?

If your people, your software, your organization, and your AI models are learning more slowly than your competitors, then you lose.

It’s really that simple.

When the slope of your learning line is greater than the slope of your competitor’s learning line, you edge out wins more often in the market, make better products, create stronger relationships with customers, and do it faster and better than the next company.

You then earn market share. You grow. You don’t die.

This is why startups like OpenAI and Anthropic are running circles around century-old Fortune 500 companies and, within a few short years, became the most valuable companies on the planet.

• They got all the internet’s data.
• They built a model that describes that data.
• Then they pointed that model at specific use cases and built apps on top of it like ChatGPT and Codex.
• Then they built always-on, personal agents that work continuously in the background to help you get things done across your work and personal life.

Meanwhile, these F500s are still stuck in meetings debating what the right data platform is and what access permissions they should give to groups of employees. And then they realize they’re moving too slowly, and Wall Street is yelling at them for profits and growth, so they lay people off.

Uhh, what? That is not the strategy toward growth.

Selling sugar water may have worked in the 1990s, but it certainly doesn’t work in the 2030s.

So, it’s time you ask yourself a simple, but hard and honest question:

• Are you building a hyper-learning autonomous organization and set of AI-native emerging tech products made for the 2000s?
• Or, are you still steady as she goes, building a legacy business made for the 1900s.

— Sean