Hi I build efficient apps & libraries using the web platform. With powerful libraries, I deliver results with simpler systems. Systems that emphasize:
- powerful primitives
- bottom-up development
- domain ontology
Unlocking the vanilla web platform to deliver productivity without framework bloat. The result is fast web sites/apps & systems that expand to handle more with less.
Featured
Skill to Binary: Debugging agent-doc Live — 6-Part Mini-Series
A 7.5-hour live coding mini-series documenting the migration of agent-doc's boundary management from the Claude Code skill into deterministic binary/plugin code — and the cascade of bugs discovered along the way.
Building Agent Resume: AI-Powered Job Search Workflow with Resume Generation
A live coding session building agent-resume — a TOML-based system for generating tailored resumes for job applications, phone call transcriptions, and email correspondence using corky and agent-doc.
Building Agent-Doc: Live Debugging tmux Race Conditions & CRDT Document Sessions
A live coding session working on agent-doc, corky, and tmux-router — covering Google OAuth app verification, tmux pane proliferation debugging, CRDT document session management, and markdown AST parsing.
Lazily: Reactive Primitives Done Right — Context, Slots, Cells, and Signals
Introducing lazily — a multi-language reactive primitives library (Rust, Zig, Python) built on lazy invalidation. Deep dive into Context, Slot, Cell, and Signal abstractions, lazy vs eager reactivity, and how proper hydration (code and body) eliminates waste.
Introducing agent-doc: Documents as the UI for AI Agents
agent-doc turns markdown files into persistent, editable, version-controlled conversations with AI agents. No more ephemeral chat — your documents are the UI.
Tag Vector: Part 0: Introduction
Tag Vector is a name system where tags connected as a vector form a name. Tag Vector can name variables, functions, components, network apis, low code apps, & prose.
Recent Posts
Ep1: The CRDT Ordering Bug — Skill to Binary Series
CRDT merge preserves data but not semantic ordering. Debugging how user prompts end up below agent responses, discovering IPC caching as the root cause, and a philosophical detour about 'vibe coder' labels.
Ep2: The Snowball Bug — Skill to Binary Series
Moving boundary management into the binary reveals a cascading corruption bug. Conditional reinsertion causes each cycle to perpetuate a missing boundary. Also: AI agents as probabilistic algorithms and context window optimization.
Ep3: AST Parsing & GPU Transcription — Skill to Binary Series
Replacing regex with pulldown-cmark AST, debugging boundary markers across IPC paths, adding CUDA GPU transcription to corky, and designing the YouTube publishing pipeline.
Ep4: IPC Timeout Deep Dive — Skill to Binary Series
Why does the boundary reposition time out? Debugging the IPC layer between agent-doc and the JetBrains plugin, CRDT vs semantic ordering, and the argument for file descriptors over polling.