agumbe.dev
AI workspaces for building and running apps on Kubernetes
What it does
Agumbe helps teams go from idea to production-ready applications - without stitching together 10 different tools. Instead of starting with infrastructure diagrams, YAML sprawl, or templates, Agumbe gives you: - Workspace-based isolation (projects → environments → applications) - GitOps-native Kubernetes deployments powered by CD tools - AI-assisted app evolution (blueprints, codegen, and safe diffs) - Built-in CI/CD, secrets, observability, and environments
Does the same job
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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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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, March 2026
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Switch from ChatGPT to Claude with import memory feature
AI · Mar 2026 · claude.com
