AI · Systems · Security · Rust
I build software at the intersection of AI, systems programming, and security.
- Systems software in Rust — concurrent runtimes, sandboxed execution, services that stay correct under real load
- AI agent infrastructure — orchestration, permissioned tool execution, persistent memory across sessions
- Applied security — cryptographic protocols, container isolation, input sanitization pipelines
- Production-grade constraints — bounded memory, capability-based auth, graceful failure, not demo-quality shortcuts
I'd rather build the system underneath the API than wrap one and call it a product.
A multi-model AI orchestration platform. Client research briefs go in, a team of specialist agents researches them in parallel, every claim gets checked against its source before it reaches the user, and a memory layer carries context forward so the third project with a client doesn't start from zero.
Grew into a full multi-service system: a FastAPI backend, a Next.js frontend streaming a live decision log as the orchestrator works, cross-provider model routing so no single provider's quota or outage can take a run down, and its own release process, specs, and docs.
Focus: AI orchestration · distributed systems · production infrastructure
The security-first agent runtime Clannon's pipeline is built on, distilled into a standalone CLI. Every input passes through a fixed pipeline before a model ever sees it:
intake → sanitizer → normalizer → verifier → orchestrator → output filter → delivery
ClamAV/YARA scanning, modality-aware sanitization, a small model making the final safety call, and four memory tiers (wiki, semantic, episodic, procedural) with trust ordering so user-authored facts always win. Tools and expert agents self-register through one capability registry — adding a new one is a decorated file, no wiring.
Focus: AI agent security · orchestration · persistent memory · tool permissioning
A local workbench that spins up a disposable Linux container and shows you exactly what happened inside it — real container PTY over WebSockets, timestamped process/file/network activity, and immutable workspace snapshots you can fork back into a fresh environment.
Runs on rootless Podman, capability-based auth (no passwords, no sessions — a private URL is the credential), and outbound networking disabled by default. It's careful about what it claims: sampled events are labeled as sampled, not pretended to be continuous tracing.
Focus: systems programming · sandboxing · Rust · WebSockets · security boundaries
End-to-end encryption for chat platforms that don't have it. A Chrome extension where the cryptographic core is written in Rust and compiled to WebAssembly — X25519 for key agreement, ChaCha20-Poly1305 for authenticated encryption. Keys are generated locally; there's no GhostLayer server or account.
The protocol is versioned and independent of the extension, so any client could implement GhostLayer v1 without touching this codebase. Tested end-to-end on Discord, Slack, X, and Messenger.
Focus: Rust · WebAssembly · applied cryptography · browser internals
Alpha. Not audited. Limitations are documented in-repo, not hidden.
A Chrome extension that filters emotionally harmful content out of your feed using a local NLP model — nothing leaves your machine. A MutationObserver-driven content script pulls post text, a local FastAPI service runs a RoBERTa model fine-tuned on GoEmotions, and posts crossing your sensitivity threshold get blurred with a one-click reveal.
Focus: local inference · NLP · TypeScript · FastAPI · browser extensions
Currently going deeper into Rust and systems programming while keeping one foot in AI infrastructure. Areas I keep coming back to:
- operating systems and kernel design
- high-performance and concurrent systems
- AI inference infrastructure
- sandboxing and isolation
- security engineering
- local-first, private AI
The common thread: understanding what's happening underneath the abstraction instead of trusting that it's magic.
Languages: Rust · Python · TypeScript Systems: Tokio · Axum · Podman · Linux · WebAssembly AI/ML: PyTorch · Hugging Face · FastAPI
Most of my work lives across my personal repos and Clannon Labs.

