Nathan Payne

Nathan Payne

Most product decisions are invisible—until they aren’t.

Context

Over the past ten years, I worked on the streaming platforms behind Disney+, Hulu, and ESPN. I started at MLB.com and BAMTECH, joined Disney through the 2017 acquisition, and spent the last five years leading the Native Client Platform across PlayStation, Xbox, Amazon Fire TV, Linux set-top boxes, and smart TVs.

Approach

The work that interests me is usually hiding at a boundary—between systems, between sources of truth, or between what a product claims and what it can actually prove. A codec mismatch, an ambiguous financial rule, and an AI agent that knows a policy but doesn’t follow it are versions of the same product problem: uncertainty that somebody eventually has to resolve. I like turning that ambiguity into something explicit enough to design, test, and operate.

Now

The current boundary is where AI coding agents meet real product work. I build end-to-end with Claude Code, Codex, and Cursor under an enforcement system I designed to catch the failure modes agents miss. The interesting part isn’t generation speed; it’s deciding what to trust, what to measure, and where a human or a machine needs authority. Open to senior product and platform roles—especially where streaming infrastructure, developer tools, or AI-augmented workflows are the center of gravity.

Read my résumé
October 2026
Projects

Selected Projects

The case studies focus on the decisions, tradeoffs, and evidence behind them; I built each with AI agents under a review system I designed.

A multiplayer bingo game built in eight days for a nine-night cruise, then operated live at sea—where real players exposed what the architecture could and couldn't prove.

Agents could recite the no-direct-push rule and skipped it anyway, so enforcement became gates that refuse—then an audit found eight of ten repos enforcing zero of five checks.

Broadway financing turned from static documents into an interactive model of the deal—built as an AI coding exercise, and still untested on a real capitalization.

Five fragmented data feeds became one device registry, with AI drafting the heaviest intake and humans deciding what becomes authoritative.

Paused with better instruments and the same 48% extraction and 19% match against an 80% bar: the last two working weeks fixed the ruler, not the product.

Swipe WatchEXPERIMENT

A swipe-first streaming recommender whose prototype accidentally faked the payoff it was meant to test—making reactions to the demo impossible to separate from reactions to the idea.

Shared billing for nine people that handles the explaining and asking without recipient accounts. Its three biggest failures shared one gap: the model was right before the interface was.

Consumer · Enterprise · Finance · Developer tooling
Community

Giving & Governing

Outside work, I’ve spent years organizing around causes I care about—raising more than $105,000, building campaigns, and staying involved after the fundraising ended.

  • Larkin Street Youth Services
    $16,684 raised
    Raised for Safe & Seen, a campaign for LGBTQ+ youth experiencing homelessness in San Francisco, supporting housing, education, and healthcare through Larkin Street Youth Services.
  • San Francisco AIDS Foundation
    $80,195 raised
    Three AIDS/LifeCycle rides: $9,166 in 2023, $45,646 in 2024, and $25,383 in 2025, supporting HIV prevention, care services, and housing stability through the San Francisco AIDS Foundation.
  • Jewish Pride Fund
    $8,959 raised
    After the campaign, I joined one of the country’s few LGBTQ+ Jewish giving circles to interview grant applicants and help decide where its grants go.
ScopeFundraising · Campaign Building · Grantmaking · Community Organizing
Connect

Connect

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