Early in my career, I worked with an engineer who spent three months searching for the “perfect” motor for a project. He evaluated dozens of options. Built spreadsheets comparing specs. Ran simulations. Requested samples from manufacturers in four countries.

The project shipped late. The motor he eventually chose? It was fine. Any of the first five he’d considered would have worked just as well.

The Unicorn Trap

Inexperienced engineers chase unicorns. They’re looking for the perfect component, the optimal architecture, the ideal solution. They believe that with enough research, they’ll find the answer that makes everything easy.

Here’s the truth: that answer doesn’t exist.

Every engineering decision involves tradeoffs. There is no motor that has the best torque and the best efficiency and the lowest cost and the smallest size and the most availability. You pick the tradeoffs that matter for your application and move on.

Good Enough Wins

The best engineers I know aren’t optimizers. They’re satisficers. They find solutions that meet the requirements and ship. Then they iterate.

This isn’t about being lazy or cutting corners. It’s about recognizing that:

  1. Perfect is the enemy of done. A shipped product beats a perfect prototype that never leaves the lab.

  2. Requirements change. The “optimal” solution for today’s requirements might be wrong for tomorrow’s. Don’t over-invest in decisions that might not matter.

  3. Learning beats planning. You learn more from building than from analyzing. Ship something, get feedback, improve.

When to Optimize

Optimization has its place. Optimize when:

  • You’ve shipped and have real data about what matters
  • The constraint is truly binding (cost, size, power that can’t be compromised)
  • You’re in production and small improvements compound

Don’t optimize when:

  • You’re still figuring out what to build
  • You’re pre-revenue and burning runway
  • The “improvement” delays shipping by weeks

The 80/20 Rule

In most projects, 80% of the value comes from getting the basics right. The last 20% of optimization takes 80% of the time.

Know when you’re in the first 80%. Ship fast, learn fast, iterate fast.

Know when you’re in the last 20%. Be deliberate about whether that extra effort is worth it.

Expertise Engineering helps teams ship hardware products without chasing unicorns. Let’s talk about your project.