Organic Systems

A quote by the late Ken Robinson has become central to how I think about innovation and leadership:

“Human organizations are not like machines, though they’re often represented that way. They are more like organisms. They thrive on feelings and sentience and aspirations and motivation. And like all organisms, they flourish under certain conditions and they wilt under other ones. Great leaders I believe are not like industrialists; they’re like farmers. Farmers know that you cannot make a plant grow. The plant grows itself. What you do is create the conditions under which it will do that.”

This quote captures something I keep seeing in my work but couldn’t articulate for years: we spend so much time trying to optimize organizations like machines that we miss the effectiveness that comes from nurturing them like gardens.

The more I work with teams, the clearer this pattern becomes. Companies invest heavily in new tools, implement rigid processes, and create elaborate systems—all trying to force growth. But the ones that thrive think about process and people differently.

They create environments where good things happen naturally.

The Problem With Mechanical Thinking

Robinson’s observation about farmers versus industrialists points to something deeper: we’ve been conditioned to see organizations as machines that need fixing rather than living systems that need nurturing.

When something isn’t working, the mechanical instinct kicks in immediately. Team collaboration feels slow, so we add a communication tool. Projects fall behind schedule, so we implement more processes. Quality slips, so we create additional checkpoints and controls. Each intervention seems logical—something’s broken, so we fix it. Something’s slow, so we optimize it. Something’s missing, so we add it.

I used this approach for years when building my first teams. Sometimes it worked. More often, it just made problems more complex. I’d watch a team struggle and think, “We need a better system for this,” then add another layer—another tool, another process, another coordination mechanism. Each addition made sense in isolation, but together they created a maze that slowed everyone down.

This is the trap of mechanical thinking. It’s seductive because it promises predictability and control. But organizations aren’t machines—they’re complex systems of human relationships, motivations, and behaviors. The mechanical approach treats symptoms, not causes. It adds complexity instead of creating clarity. Worst of all, it often works against the natural patterns that would make teams more effective.

What if there’s a different way?

Shifting to the Farmer’s Mindset

Think about how a successful farmer approaches growing crops. They have tools—trowels, irrigation systems, greenhouses—but they understand something fundamental: tools don’t make plants grow. The farmer’s job is creating the right conditions. Preparing the soil, ensuring proper drainage, understanding the climate. The tools support this work, but they’re never the main story.

This same pattern exists in successful organizations. The secret isn’t having better tools or more sophisticated processes. It’s creating an environment where good things happen naturally.

When I lead product teams, I can give people the most sophisticated design tools available, but if they’re afraid to experiment, they won’t create anything interesting. When I create an environment where experimentation feels safe, real creativity emerges. The difference isn’t the tools—it’s the conditions.

Here’s something that might surprise people who know me, since I’m often the person introducing new tools to teams: I believe processes are only a means to an end. The difference is in why and how I choose to introduce them. A good farmer has favorite tools, but they don’t start by buying tools. They start by understanding the environment. The tools they choose flow from that understanding, and they introduce them thoughtfully, at the right time, in the right way.

When a team struggles, the easy answer is throwing another collaboration tool at the problem. I’ve learned to spend time understanding how information naturally flows first. Often, existing tools are fighting against the team’s natural working style. Simplifying the toolkit and aligning it with real work patterns—rather than ideal ones—can improve output dramatically.

The 7 Principles of Organic Systems

After years of watching organizations succeed and fail (and making plenty of mistakes myself), I started paying attention to the naturally thriving ones. What made them different? How did they manage to grow without becoming overly mechanical?

I discovered seven patterns that show up consistently in these organic systems. These aren’t just observations—they’re the fundamental principles that guide how we create environments where both technology and human potential can flourish naturally.

1. Manage Complexity, Lead People

A conductor doesn’t make a sound. They manage the complexity of the orchestra—the timing, the dynamics, the interplay between sections—so that each musician can play their part beautifully. Great leaders are conductors. They don’t play the instruments; they create the conditions for a masterpiece to emerge.

People don’t need to be managed—they need clarity, support, and trust. What needs managing is the complexity that gets in their way: the tools, processes, and systems that either help them work or slow them down. Good organizations obsessively manage their complexity—regularly auditing tools and processes, removing anything that doesn’t serve a clear purpose. They create simple systems with clear boundaries, then trust people to work within them.

Instead of asking “How do we manage people better?” ask “What’s getting in people’s way?” I spent years thinking more processes meant better results. When a team struggled, I’d add another system, another tool, another layer of coordination. The shift came when I started removing things instead of adding them. We simplified our communication channels, cut our meeting cadence in half, and gave engineers more autonomy over their deployment schedules. The result: people spent their time doing work, not navigating systems.

2. Design for Natural Growth

You can’t force a plant to grow by pulling on it. You create the right conditions—good soil, adequate water, proper sunlight—and the plant grows itself. Organizations work the same way. Natural growth is resilient; forced growth is brittle.

Sustainable growth is an emergent property of a healthy system. It happens when people have clarity about where you’re going, the autonomy to figure out how to get there, the resources they need, and the trust that experimentation won’t be punished. Create those conditions and growth emerges naturally.

Focus on the environment first, solutions second. Instead of setting aggressive top-down targets, ask: “What conditions would make this outcome inevitable?” Do people have the right information? Is it safe to fail? Is there a clear connection between their work and the company’s purpose?

3. Balance Technology and Humanity

A great chef uses the best knives, but the magic isn’t in the steel; it’s in their hands. Technology should make human interactions better, not replace them. The best tools fit into existing workflows so naturally that people barely notice them.

Technology is an amplifier. It makes good teams better and dysfunctional teams more chaotic. The most common failure I see is trying to solve a human problem with a technical solution. Start by understanding how people naturally work, then find technology that supports those patterns. Be willing to choose a less sophisticated tool if it fits better with how your team actually operates.

4. Focus on Context, Not Components

A great architect doesn’t just design a building; they design how the building fits into the neighborhood. They think about sunlight, foot traffic, and how it will feel to walk past it every day. They understand that everything is connected. Your organization is an ecosystem. Change one thing and you affect everything else.

Local optimization often creates global dysfunction. Someone optimizes the sales process for speed, which floods the customer success team with bad-fit customers. Engineering improves deployment frequency, which overwhelms the support team with small but frequent changes. Before changing anything, ask: “How will this affect the rest of the organization?” Look for leverage points—places where small changes can have large effects because of how they interact with other parts of the system.

5. Build Trust Through Design

A well-built bridge doesn’t need a sign that says “This is safe.” The design itself communicates trustworthiness. Trust in organizations is the same. It’s not built with words; it’s built into the design of the systems people use every day.

Trust isn’t a feature you can add later; it’s the foundation everything else builds on. Excessive approval layers signal “we don’t trust your judgment.” Monitoring systems signal “we assume you’re not working unless we can measure it.” Design systems that assume good intent. Processes designed for the 99% of people who do the right thing, not the 1% who might not.

6. Drive Decisions with Purpose

A ship in the middle of the ocean can be rocked by storms and thrown off course, but if the crew knows their destination, they can always reorient. Purpose is the North Star for your organization.

Financial targets are a result, not a purpose. When teams lose their way, it’s rarely because they lack tools or processes. It’s because they’ve lost sight of why they’re doing what they’re doing. When purpose is clear, decisions become easier. Make purpose the first filter for every major decision.

7. Learn Through Evolution

Nature’s most resilient designs weren’t created in a single stroke of genius; they were refined over millions of years of trial and error. Evolution is the ultimate learning algorithm.

The world is too complex and changes too fast for any plan to be perfect. The evolutionary approach is resilient: make an educated guess, try something small, learn what actually happens, and adjust based on reality. Treat every initiative as an experiment with a hypothesis to test, not a plan to execute. You build to discover what works rather than to implement what you think will work.