AI-Native Builder & Advisor

What I'm building after Pixly

I'm riding the models to stay at the edge of AI.

We're in a transition era. The models are getting good enough to execute real work once the problem is framed clearly. That makes building faster and cheaper, but it also makes average output more abundant. The scarce work is moving up a level: knowing what to build, giving the models the right context, reviewing the result, and turning what works into reusable systems.

After nearly a decade building Pixly, I stepped back in 2025 to focus on family and explore that frontier. Right now that means building AI products and systems, advising founders, occasionally investing, and chasing a toddler around SF.

Somewhere in the spring of 2025, the tools crossed a line for me. Claude Code, Notion AI agents, MCP servers, Cursor, Wispr Flow. Suddenly I could sit down on a Saturday morning and ship something useful by lunch. No dev team, no ticket queue. Just a clear frame, the right context, and a bunch of models doing the heavy lifting.

That became the work.

What I'm actually doing

Three things, and they all feed each other.

Building. I use AI tools every day to design and ship practical systems for myself and people in my network: internal ops dashboards, booking flows, agent-driven workflows, marketing sites, prep automations, and lightweight products. Most of the source of truth lives in Notion, with Claude Code doing the heavy lifting whenever something needs real code.

Advising. I work with founders and operators on how to use AI in the actual flow of their business. Not "AI strategy" decks. The useful question is: what should stop being manual next Monday? Most of the work is hands-on: audit the workflow, find the few places where an agent can help, build the first version together, and add a review loop so quality does not drift. Sometimes that looks like a focused advisory sprint. Sometimes it is literally sitting next to someone over lunch, connecting the tools on their laptop, and helping them leave with their first real agent workflow.

Content. This part surprised me. I am enjoying building in public, documenting the work, and engaging with the online community around AI processes, workflows, trends, and how company-building changes when the models are part of the operating system. Some of it is useful and practical, like Your AI Lunch Guy. Some of it is internet-native and weird, like Discomorphism. A lot of it is just fun little projects in my personal repos: schedulers, Notion tools, personal websites, sync scripts, and experiments that help me understand what this new workflow actually feels like.

Where this is going

I do not fully know yet, and I like that. After 9 years of running one company, I wanted room for the work to tell me what it wants to become.

But the thesis is getting clearer: the best AI-native work will not come from chasing generic output. It will come from people and teams who can turn their context, taste, and judgment into systems that get better every time they run.

That is what I am building toward.