- San Francisco
- magnitude.run
- in/anders-lie
- @anderslie
Stars
macOS and Linux VMs on Apple Silicon to use in CI and other automations
The open-source SDK for bringing any agent into any chat platform: Slack, Microsoft Teams, Discord, Telegram - with native, Interactive UI.
IP addresses break, dial keys instead. A library that adds QUIC + NAT Traversal to your apps.
Prose diffs for any document format supported by Pandoc
A multi-hypervisor VM runtime for OCI images, supporting Cloud Hypervisor, Firecracker, QEMU, and Apple Virtualization.framework.
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing…
A browser that runs directly inside your existing terminal
A workspace-aware Cargo lint for unnecessary public Rust APIs.
A batteries-included framework for building web apps
Unofficial Rust bindings to Apple's mlx framework
Inferno aims to be a super lightweight, highly efficient Rust inference engine for running open weights models on Apple Silicon with Metal, targeting machines such as a MacBook Pro with 64 GB of un…
Open-weight emotion and refusal vector extraction and steering experiments.
Multi-platform high-performance compute language extension for Rust.
Democratizing large model inference and training on any device.
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
An all-in-one, pure C++ inference engine for audio models, powered by ggml. Supports TTS, STT, VAD, voice conversion, music generation, and more, with highly optimized performance. No Python depend…
Generate @effect/schema definitions from an OpenAPI document
Here are some skills I use. Maybe you'll find them useful. Maybe not. Goodbye.
Tool-calling quality benchmark for LLM serving stacks. 80+ deterministic scenarios testing multi-turn orchestration, safety boundaries, and structured output. Supports vLLM, SGLang, and llama.cpp.
Run frontier MoE models on hardware you already own — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦
Measuring frontier coding agents on original, long-horizon engineering tasks