Hi HN — I built Palmier. Palmier bridges your AI agents and your phone. It does two things: 1. It lets you use your phone to directly control AI agents running on your computer, from anywhere. 2. It gives your AI agents access to your phone, wherever you are — including things...
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I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work on Mac. I replaced the CUDA-specific ops with pure-PyTorch...
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Your LinkedIn AI coworker that delivers pipeline.
A lightweight way to make agents talk without paying for API usage is tracked as an emerging product signal.
Apple has quietly shipped a pretty complete on-device AI stack into macOS, with these features first getting API access in MacOS 26. There are multiple components in the foundation model, but the skills it shipped with actually make this ~3b parameter model useful. The API to...
I got tired of libvirt XML and Vagrant's Ruby/reload dance for single-host VM stacks, so I built a compose-style runtime directly on QEMU/KVM. What's there: GPU passthrough as a first-class primitive (VFIO, OVMF, per-instance EFI vars), healthchecks that gate depends_on over S...
no-mistakes is how I kill AI slop. It puts a local git proxy in front of my real remote. I push to no-mistakes instead of origin, and it spins up a disposable worktree, runs my coding agent as a validation pipeline, forwards upstream only after every check passes, opens a clea...
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I kept hitting the same wall at work every time we needed to ship an AI feature. What looked like a week of work turned into picking a model, setting up a vector DB, managing embeddings, wiring up chat history, handling retries — none of it was the actual feature. So I built M...
