Aftlog
A flight recorder for AI coding agents. A local daemon records what a session changed and produces a readable receipt with a backup-first revert plan.
A decade of zero to one.
I taught myself to code at twenty-two, after an engineering degree that never once asked me to build anything. The first months were miserable. Then it clicked, and within six months I was shipping complete products. I have not stopped since.
The decade since has been uneven, and I would rather tell you that than perform a highlight reel. I once spent thirteen months building a multiplayer game and less than thirteen days telling anyone it existed; almost nobody came. A smaller game I built in two months found thirty thousand visitors in a single night. It took me longer than I would like to admit to accept what those two facts were saying: the code was never the problem.
Everything on this page I designed, built, and shipped myself: AI systems, developer tools, games, native software, and the infrastructure underneath. For most of the decade there was simply no one else; owning every layer was never a strategy. A few of the later ventures brought co-founders on the business side, but the code stayed mine, end to end. Building this way made me fast from zero to one, and it made me honest about what building harder can and cannot fix.
People sometimes ask what my specialty is, and the honest answer is that the product decides. One year it was a game engine, another year a browser automation farm, then email infrastructure, then a native macOS app, and lately AI systems. None of these are my identity. They were what the problem in front of me required, and a decade of this has taught me to trust that I can pick up whatever the next one requires.
Building is also just how I make sense of the world. When something interests me, the itch is never to talk about it; it is to make a working version and see what it teaches me. That instinct has cost me time I will not get back, and it has given me more than anything else could have.
These days the itch has a direction: AI that has to earn its place inside real operations, where the work is messy, the stakes are real, and people only trust what they can verify. That is what I am building now at Akisto, an AI supplier coordinator for manufacturers, with a co-founder who spent years living the problem we are automating.
What follows is the record, kept honestly: what worked, what did not, and what each one taught. If you are carrying a hard problem you think software might fix, I would like to hear about it.
A flight recorder for AI coding agents. A local daemon records what a session changed and produces a readable receipt with a backup-first revert plan.
Document intelligence for commercial real estate review. Compares title commitments with surveys and reads plan sets against building and zoning code, with every finding tied to its source.
Conversational editing for image, audio, and video. Describe an outcome; the system plans the operation, writes executable code, and returns finished media files.
A native macOS accountability companion built as a relationship, not a dashboard. Layered memory, a schedule-aware notification interface, and personal state that stays on the machine.
Automated sports commentary. Samples footage, writes timestamped play-by-play, and renders a synchronized voice track and subtitle file back onto the source timeline.
A multiplayer race in which nobody controls the racer. Roughly 30,000 people arrived in a night, turning a small zero-player game into an exercise in real-time coordination.
A separate email identity for the transactional life of the internet. Keeps app sign-ins, OTPs, and notification mail away from a person's primary address.
A shared multiplayer economy where giving creates power. Every transfer of points changes both social alignment and future earning power on one global leaderboard.
One subscription across independent websites and SaaS products. A single account and payment in front of routing, partner entitlements, and access rules.