I’m a cloud engineer and developer passionate about building scalable Cloud and AI infrastructure. I enjoy working with modern technologies to create efficient, production-ready solutions.

This blog is where I share my experiences and learnings in software architecture, distributed systems, and engineering leadership.

🕹️ Learned to code on a Commodore, and I’ve basically been hitting RUN ever since.

Languages / Tools Used

Programming Languages: Go Rust Python TypeScript JavaScript Bash SQL C++

Development Tools: Neovim Git gitgui cmux Terraform Ansible Docker Kubernetes Helm Containerd Firecracker Cosign Prometheus etcd

Security & code intelligence: Semgrep Bandit Gitleaks Trivy

Frameworks & Libraries: FastAPI Actix Tonic gRPC QUIC libp2p BitTorrent Next.js Angular React GraphQL PostgreSQL MongoDB RocksDB Tailwind CSS shadcn/ui

GPU & accelerators: CUDA Metal Apple Silicon NEON AVX2 SIMD GGUF

Vector search & databases: Qdrant HNSW FAISS cuVS

LLM inference engines: vLLM SGLang llama.cpp TensorRT--LLM MLX Ollama Frink

Services Used

Cloud Platforms: AWS Google Cloud Vercel Fly.io

APIs & Integrations: Binance OpenAI Anthropic OpenRouter

Social Media APIs: Facebook Meta LinkedIn Twitter X Pinterest Telegram

Notable Projects

  • Frink Crates.io - Pure-Rust GGUF inference engine: quantized CPU, Apple Metal and CUDA kernels, mixture-of-experts support, and an OpenAI-compatible server. Every speed claim is benchmarked head-to-head against llama.cpp on the same host and file. Write-ups: a Rust GGUF engine, measured against llama.cpp and Frink on Metal, at parity with llama.cpp and past it.

  • MARS - GPU-resident multimodal memory substrate for real-time embodied AI. Episode-scoped retrieval as a CUDA kernel-level primitive: 197 µs p99 at N=1M with perfect cross-modal hit@15, 33× faster than FAISS-Flat-GPU on the same hardware. Companion paper: MARS: Episode-Scoped GPU Retrieval for Real-Time Embodied AI.

  • Cognitora inference - Open-source, datacenter-scale LLM orchestration above vLLM, SGLang, TensorRT-LLM, and llama.cpp: KV-aware routing, prefill/decode disaggregation, multi-tier KV cache, static Rust binaries for bare metal, Kubernetes, or cloud.

  • gitgui - A git GUI that runs inside the terminal, next to your coding agent. One Rust binary paints an iced interface as pixels into a cmux, Ghostty or kitty pane over the kitty graphics protocol, or opens a desktop window where the terminal has no graphics: commit graph, staging by file, hunk or line, a three-way conflict resolver, history rewriting, a built-in editor, draggable panes, and a socket so agents like Pi drive it. Write-up: gitgui: a real git GUI inside cmux, next to Pi.

  • Rondine 🐦 - Hardware-aware local LLM launcher. Detects the machine, picks a model that fits, and applies tuned configs for Mac, NVIDIA GPUs and DGX Spark instead of leaving you to do flag archaeology. Write-up: Rondine: hardware-aware local LLM serving.

  • s0-cli - LLM-driven CLI agent that finds security vulnerabilities and AI-slop patterns: stub auth, hallucinated imports, dummy crypto, prompt-injection sinks. Hybrid of classic scanners (semgrep, bandit, gitleaks, trivy) with LLM triage on top, plus a self-optimizing meta-harness loop. Write-up: the meta-harness that tunes its own scanner.

  • VittoriaDB - Zero-configuration embedded vector database with HNSW indexing, ACID storage, and REST API. Single Go binary for local AI development.

  • DistX Crates.io - High-performance vector database written in Rust. Features HNSW indexing with SIMD optimizations, Qdrant-compatible REST API, and gRPC support.

  • PeerClaw - Decentralized P2P AI agent network in a single static binary. BitTorrent shape applied to inference: peers share compute, agents earn and spend tokens for it.

Connect

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