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Elon Musk’s Engineering Principles

· 3 min read
Abhi Yerra
Abhi Yerra
Founder, opsZero

Think what you want of Elon Musk, but he has achieved quite a bit in engineering novel solutions to complex problems. We’ve worked mainly on implementing the same process to great effect in what we do.

The principles are:

  1. Fix dumb requirements. Each requirement has a specific owner.
  2. Remove unnecessary parts
  3. Simplify/Optimize
  4. Speed up cycle time
  5. Automate

You can watch him describe his process here:

Fix dumb requirements​

When solving a problem for a customer, the customer may not actually know what they need. So uncover the actual requirement behind the request.

Usually, a problem such as:

The production database is high CPU and clients can’t connect

may actually be a root cause issue:

The production database is being used to replicate data to a data warehouse, which is causing the issue.

This root cause analysis can be gleaned through a five whys analysis.

Second, with these requirements there needs to be a clear owner responsible for the issue. If there is not an owner for something, then that itself is an issue. Ownership of each component means that someone exists to optimize each piece.

Remove unnecessary parts​

Systems over time become complex. Pieces are added that don’t need to exist—or they were added, then forgotten about.

Systems should get less complex, not more so.

As we build things, we build to get the task done. This means we may add complexity to the system that didn’t need to exist, but because we are pathfinding our way to the solution, that complexity is needed.

Once we get to the point of the system working as needed, we go back and remove the pieces that are not needed.

Simplify/Optimize​

After removing unnecessary parts, there may still be complexity within the current components.

To simplify these components, we need to reduce variability and increase standardization.

For example:

  • The use of multiple if-else blocks to account for variability can increase complexity.
  • Simplification requires subjective decisions on the optimal approach.

It’s best to initially build with some variability, then refine through A/B testing over time toward the optimal solution.

Speed up cycle time​

Once an optimal approach is found:

  • Remove variability
  • Standardize the approach for deliverability

This leads to faster outcomes, with fewer branching paths, creating better flow.

Automate​

Lastly, automate the processes such that things happen without intervention.