About Zac Peterson

Hands-on, across the boundaries.

My work connects cloud-native platforms, machine learning delivery, and application engineering. I care about the seams: how code reaches production, how a model becomes a service, and how a team understands what its systems are doing.

Engineering approach

Simpler is a serious engineering goal.

Understand the constraint. Build the smallest durable solution. Measure what changed. Leave the team with a system they can own.

The useful work often happens between disciplines: connecting a deployment pipeline to the application it serves, a model to its operational constraints, or a cloud decision to its cost.

I stay close to implementation. The goal is not architecture for its own sake; it is software and infrastructure that a team can understand and depend on.

Practical principles

Make the tradeoffs visible.

  1. Work from the real constraint

    Map the existing system and clarify the failure or bottleneck before choosing another tool. Preserve what already works.

  2. Make progress observable

    Use small changes, reproducible checks, and operational signals. A design needs evidence, not just a diagram.

  3. Keep ownership clear

    Prefer explicit interfaces, reviewable configuration, and a handoff that explains both the decisions and their limits.

Stay connected

Start with something concrete.

San Francisco, CA

Bring a technical question, a project brief, or an engineering opportunity.

A useful next conversation

What needs to work better?

A system, a delivery bottleneck, or an engineering opportunity. Tell me what you are building and where you want to go.

Let’s talk

Technical glossary: definitions, connected ideas and further reading.

Optional analytics off. Contact works either way.

How measurement works