About

What I Do

I design and build complex, high-reliability software systems — the kind where the architecture matters, where performance is not optional, and where AI integration has to be more than a wrapper around an API call.

I work with founders, designers, and small product teams as a technical partner. Not a resource who completes tickets — an engineer who helps decide what should exist, designs the system that supports it, and builds it to hold together over time.

Recent Work

The most recent case study on this site is the Austin Eischeid platform — a collaboration with a planting designer working at the highest level of landscape architecture. It is a good example of the kind of work I do: architecture-first, image-heavy without compromising performance, structured content over visual gimmicks, and editorial control engineered into the foundation rather than bolted on after launch.

The second published case study is Project Chimera — an editorial systems architecture project where the AI is part of the system, not the centerpiece. The trust layer around it is. Its companion article, Using AI in Real Products, Not Just Demos, extracts the engineering principles from that work at the category level. A third case study on Forges of Karinth — a deterministic simulation engine with integer-scaled math and seeded reproducibility — is in progress. Each one is documented honestly, with the decisions and tradeoffs that actually shaped the outcome — not a feature list.

What I Care About

Architecture before code. Long-term maintainability over short-term cleverness. Security as a design principle, not a plugin. Performance as a feature, not an audit you run the week before launch.

I believe the best software is built by people who think about both the product and the system — who can sit in a design review and then go write the code that holds it up. Those are not separate jobs. On a small team, they are the same job.

How I Work

Every system I build starts with understanding the problem at the architecture level — data flow, boundaries, invariants, the parts that will change and the parts that will not. Only then does code get written, under a test-first discipline that produces specifications as a byproduct.

I use AI tools throughout my workflow as a force multiplier, not a replacement for engineering judgment. When AI shows up inside the products I build, it follows the same rigor as the rest of the system: cost control, failure handling, evaluation, and honest boundaries on what it can and cannot do.

If you want the longer version of how I approach this, it is in How I Build. If you are thinking about a project, the door is at Work With Me.