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gbfish/README.md

Illustration: walking from mobile apps toward local LLM agents, MCP, and point-in-time data, notebook in hand

Software engineer, 10+ years. Mobile (React Native, Swift), Rust, embedded, and lately: making AI agents actually work.

What I'm doing now

  • Running local LLMs through real agent loops and writing down where they break — agent-lab. Every conclusion in that repo is traceable to a raw trajectory; if a number isn't backed by a run, it isn't in the README.
  • Researching MCP as infrastructure: what a server can and can't do on iOS, why MCP gateways became a category, and where the protocol has no answer yet (physical-safety envelopes, RBAC).
  • Quantitative trading as a data-engineering problem: point-in-time datasets, cost-aware backtests, and the honest arithmetic of small accounts.

How I work

I write things down. Research notes, dead ends, and corrections stay in the repo next to the code. If I was wrong, the correction is marked, not silently edited.

Elsewhere

Writing: gbfish.github.io (RSS) · Houston, TX · equalbean@gmail.com

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  1. agent-lab agent-lab Public

    Experiment bench: where does local model + Goose break when running a real agent loop? Every conclusion traceable to raw trajectories.

    Python