Senior Software Engineer · Zapier

Senior software engineer building applied AI systems, agent infrastructure, and developer tools.

For more than a decade I’ve built production systems — and, increasingly, the infrastructure and tooling other engineers rely on. My focus now is making LLM-powered products dependable: agent infrastructure, evaluation, retrieval, and long-running execution.

Selected work

All work →

Selected writing

All writing →
Confusion matrix of LLM-judge verdict vs. real outcome, with the false-pass cell highlighted
Evaluation

Ground-Truthing Your LLM Judge: Does Your Eval Actually Track Reality?

LLM-as-judge is the default eval now — but a judge is just another unreliable model. Here is how to check whether its verdicts correlate with real outcomes, and catch the leniency bias most judges have.

Photo by park ingyeom on Unsplash
Agents

I Built 50 AI Skills for the Parts of My Day I Never Got Around To

The biggest productivity gap isn't code — it's context gathering, note-taking, and status updates. I built 50 AI workflow skills to make those 15-minute tasks actually happen every day.

Weights
Evaluation

Reward Engineering and Evaluation: Making Your System Learn What Matters

This is the third post in our series on probabilistic prompt pipelines. In our first post, we explored why static prompts become bottlenecks. The second…

cart-unsplash
Retrieval

Building the Selector: Retrieval, Bandits, and Cold Start Solutions

This is the second post in our series on probabilistic prompt pipelines. In the first post, we explored why static prompts become bottlenecks and saw a…

blue sign
Retrieval

Why Static Prompts Fail and How Probabilistic Selection Solves Real Problems

This is the first post in a four-part series on building production-ready probabilistic prompt pipelines. By the end of this post, you'll understand why…

apple II
Agents

Claude Code: The Hidden Testing Ground for AI Agents

I've been using Claude Code daily since it launched for general use. After months of working with it, I've developed a theory about what's actually…

What I work on

Applied AI

  • Agentic workflows
  • Tool use & orchestration
  • Retrieval & RAG
  • Evaluation & feedback loops
  • Model integration & routing
  • Human-in-the-loop systems

Product engineering

  • Frontend architecture
  • Backend services
  • API design
  • Data-rich interfaces
  • Experimentation
  • Production observability

Let’s compare notes

Working on reliable AI products, agent infrastructure, or developer tools? I’m always interested in comparing notes with serious builders.