SwiftGate
One OS for AI agents with shared brain, skills and logs
What it does
SwiftGate is an operating system for AI agents. Connect Claude Code, OpenCode, and other agents in one shared environment, alongside SwiftGate’s own agent harness. Give every agent shared knowledge, memory, peer communication, scheduled wakes, MCP integrations, and full action logs. Because agent traffic passes through SwiftGate, actions remain traceable. Use your API keys, connect local machines via the SwiftGate CLI, and manage agent teams from desktop, mobile, Apple Messages, or Telegram.
SwiftGate AI verbindet interne KI-Agenten mit deinen lokalen Coding-Agenten — OpenCode, Claude Code, Aider. Ein Knowledge Graph, ein Audit-Log, von überall. Kostenlos starten.
Interne KI-Agenten und deine lokalen Coding-Agenten teilen sich einen Knowledge Graph und einen Audit-Trail — von überall. Desktop, Handy, Chat — Agenten, Boards und Wissen arbeiten in einer Umgebung. Von überall. Eine Zeile. Dann arbeiten deine lokalen Agenten — OpenCode, Claude Code, Aider — im SwiftGate-Team. SwiftGate ist ein Betriebssystem für AI-Agenten. Es bringt native SwiftGate-Agenten und externe Agenten wie Claude Code, OpenCode und Aider in eine gemeinsame Umgebung. Agenten werden zu Nodes mit eigener Identität, Konfiguration und Fähigkeiten — und teilen sich das gleiche System um sie herum. Die meisten Agent-Tools fokussieren den Agenten selbst. SwiftGate fokussiert das System…from swiftgateai.de
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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