What I Build

The products are the work.

Builder First

I’m a builder, not a consultant. Everything I know about AI-augmented development, personal data infrastructure, and orchestrating agents across a full portfolio comes from shipping these products day after day, not from advising about them from the sidelines.

Here’s the evidence.

Fig. 1 A year of the work, read as a tabulator reads a punched card. One column a day from 12 October 2025 to 11 October 2026, one row a product, and a hole for every day that product took a commit. On 293 of the 365 days, at least one did.

The Portfolio

The Silo Ecosystem

Tractor and Silo

Life-tracking ecosystem
Web, live
iPhone, on the App Store

The flagship. A platform across web and iOS for the kind of personal data a generation of us has been deliberately capturing for years without anywhere worth keeping it. Built around a capture-enrich-synthesize arc, and all three ship today.

Solo-built and operated since 2016. Rails web app, and a native iOS app shipped to the App Store.

Lens

Quantified-self desktop companion
macOS, public beta

A local-first macOS app that captures what happens on your computer (screen, audio, context) and turns it into hourly recaps and daily summaries you can read back. Phase 1 ships standalone today. Later phases push journals into Tractor and Silo and pull the timeline back, so the desk joins the cross-source synthesis. The desktop half of the ecosystem.

Also from the studio

Answers to Answers

iPhone, on the App Store
Web, live

One question a week to your whole family. Everyone answers privately, and when the question closes every voice is revealed at once.

Marquee

macOS, notarized

Folders of photos in, a single MP4 out. A notarized Mac app that turns the archive you never look at into a slideshow that plays on any screen.

PKM Vault

Personal knowledge management with LLM enrichment

A document ingestion pipeline that pulls anything I read, write, or annotate into a structured vault. Five-Ws metadata extraction, local-model enrichment via LM Studio, and a retrieval layer designed to work with the rest of the portfolio. A production test of an always-on local agent inside my own stack.

What the practice looks like.

The same AI-augmented workflow that runs my day job as VP of Engineering also lets me operate the entire portfolio end-to-end as a solo developer. The capabilities below are visible in the products themselves. They’re not pitched, they’re demonstrated.

AI-native operations

Orchestrating agents across a full product portfolio, from code generation to autonomous review cycles to long-running planning workflows that span multiple repos.

Personal data infrastructure

Designing systems around the capture-enrich-synthesize arc, with the person using the product owning the record, on devices they control.

Technical strategy and architecture

System design, data modeling, and infrastructure decisions for products you intend to live inside for decades, not quarters.

Engineering leadership

Code review standards, workflow patterns, and the discipline that lets a one-person engineering team move like a much larger one.

A note on consulting.

I don’t advertise consulting. The portfolio is the work, and that’s where my time goes.

If a project comes to me, I’ll hear it out. No pitch, no engagement model. Just a conversation if it’s the right shape.