Software engineer with 20+ years building products, infrastructure, and open source software. Founder of JSON Resume and co-founder of cdnjs. Currently working across AI agents, programming languages, compilers, GPU computing, model training, and formal verification. I enjoy building complex systems from first principles.
A dependently typed programming language and compiler for AI learning systems. Compiles model mathematics, training loops, host code, and GPU instructions into self-contained executables without conventional machine-learning runtimes.
Founded the open standard for representing resumes as JSON. Now an ecosystem of schemas, themes, developer tools, AI job matching, and agent integrations.
Co-founded one of the web's largest open-source JavaScript and CSS content delivery networks, now operated with Cloudflare.
An evidence-first knowledge system for AI agents, built in Rust and PostgreSQL. Stores contradictory claims with provenance, bitemporal history, query-time reconciliation, and formal verification.
An experimental computing platform where language models generate literal executable machine bytes rather than source code, which are validated and executed on a custom virtual computer.
Developing a general-purpose agent execution harness for persistent sessions across web, CLI, and local development environments.
An experimental mathematical reasoning platform connecting ideas, Lean 4 formal proofs, theorem libraries, and AI agents.
Tool Package Manager for AI Agents. Discovers, validates, and exposes npm packages as tools through MCP, SDKs, and command-line interfaces.
A semantic validation system for AI-generated code, using domain specifications to detect inconsistencies and implementation drift.
An adversarial research-paper replication engine that extracts scientific claims, constructs evidence graphs, runs independent checks, and records reproducibility verdicts.
An AI-powered Discord agent with 80+ tools, multi-database memory, code execution, and autonomous improvement workflows.
CLI for using language models to optimize functions, validate functional equivalence, and benchmark implementations across languages and providers.