The Power of Simplicity in Design Amidst Competitive Complexity

I need to get back into the habit of writing regularly. Some of these posts will be random in topic. I hope you enjoy them—but more than anything, they’re here to help me rebuild my writing muscles.

The other week, I was at the University of Indianapolis for a dive event when, by happenstance, a state robotics competition was taking place in an adjacent building. These were non-school-affiliated teams from all over Indiana—mostly high school students aged 12–18. At first glance, it was clear many of these teams had gone through multiple design iterations and likely competed before. The robots were impressive.

Each robot was built to compete in a basketball-like game. The battlefield was a 6x6-foot square with two open cylinders positioned in adjacent corners as goals. At the base of each cylinder was an inclined rack that funneled made wiffle balls to a gate. When triggered by a robot, the gate would release the balls back into play. Two white lines extended from the goals and met at the center of the field, forming a triangle. In the opposite corners, there were small plexiglass squares where out-of-bounds balls could be returned to play.

Each match featured four robots—two teams of two—competing to score the most baskets, earn style points, avoid fouls, and defend against their opponents. Matches lasted two and a half minutes.

The robots varied widely in size and function. Some were tall cubes; others were compact and low. Some had multiple launch mechanisms. Some used wheels, others skids. Most could move in all directions. Many followed a similar design: front-facing retrieval bay, internal loading system, and a launcher.All of them—except one.

There was one robot, small and unassuming, that immediately stood out. It had retrieval bays and gate levers on each side (side-bot). It featured a fixed launcher and sat low to the ground. It was fast. When the match started, it quickly gathered a few wiffle balls, moved to the white line, aligned itself, and fired—making every shot. Then it slid sideways to the gate, released the balls it had just scored, collected them again, slid back to its original position, adjusted slightly, and fired again—making every shot.

Over and over.

The side retrieval system eliminated the need to turn its body to collect balls from the gated area. The fixed launcher reduced mechanical complexity and alignment error. Its small size improved speed and reduced collisions. Every design choice removed friction.After 45 seconds, side-bot had already doubled the opposing team’s score. Then came phase two.

With a comfortable lead, the robot shifted strategy. It parked near its own gate, preventing balls from re-entering play. The opposing team’s supply dwindled. When they tried to recover, side-bot would briefly abandon the gate, scatter balls across the field, and disrupt positioning—creating chaos. Meanwhile, its partner added points steadily to maintain the lead.

Final score: 140 to 50.

The next match looked the same. A different team, same outcome.

I didn’t stay to see how far side-bot advanced, but I’d be surprised if it didn’t go deep into the tournament.

What struck me most was that no other team used this design. If I had built a robot, I likely would have overcomplicated it—like many of the others. I would have prioritized versatility: full mobility, adjustable launch angles, multi-ball loading. More features, more options, more control. But that wasn’t the objective.

The objective wasn’t to build the most versatile robot. It wasn’t to prepare for every possible variation of the game. It was to win this game, as it was designed. And side-bot did exactly that. It focused entirely on the objective—and eliminated everything else.

It made me think about how often we do the opposite. We build complexity. We iterate endlessly. We borrow ideas from others who aren’t necessarily succeeding. We focus on what we can do instead of what we should do. It’s easy to drift away from the objective.

Understand the objective. Stay focused on it.

I was just as impressed with the strategy as the design. Side-bot found an edge—and exploited it relentlessly. No deviation. No boredom. No hesitation. How often do we abandon something that’s working just because we’re bored? Or because it feels too simple? Or because we assume the edge won’t last? We complicate things. We change for the sake of change. That’s a mistake.

If you’re hitting the target every time, you should welcome the boredom.

In my own work, my job is to treat patients and train internists. Those are two distinct responsibilities, but focusing on the latter—training—I see a similar problem.

We accept variability in outcomes across trainees, even though the objective is the same for all.

Why?

Maybe we’re overcomplicating it.

To simplify the training steps:

See the patient.

Gather information.

Understand the situation clearly.

Develop a strategy.

Execute.

Assess. (Learn from the experience)

Repeat.

Teach and refine each step until it becomes second nature—until it becomes boring.

Because that’s where mastery lives.

Release the gate.

Gather the balls.

Move to the line.

Line up your shot.

Launch.

Repeat.