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Show HN: Voidleap Code – agentic IDE, own harness, swap models mid-conversation https://ift.tt/IhWKXVe

Show HN: Voidleap Code – agentic IDE, own harness, swap models mid-conversation We wanted to build a development environment that can make you a better agentic engineer, not a tool that makes money when you waste tokens. A tool where you can swap models between turns, edit the context, and see every agent action. To do it, we had to build our own harness. Free to use. We don't sell inference, so bring your own key. The sore spot is Claude subscriptions. We can't support them because of Anthropic's terms. The app runs on your machine, and your data never touches our servers. We've been building Voidleap Code using Voidleap Code since January. We didn't rush to launch, but instead focused on getting the architecture and package just right. There are still more features to build, and more polishing to do, but it's ready for you to try. Judge it for yourself and tell us what you think. https://voidleap.com/ August 19, 2026 at 01:40AM

Taken with Transportation Podcast: Muni Kids

Taken with Transportation Podcast: Muni Kids By Melissa Culross For many young people, riding Muni is part of growing up in San Francisco. And they can use the system without paying a fare. Five years ago, we expanded our Free Muni for Youth program to include all young people. No matter where they live, no matter what their family’s income, anyone 18 years old and younger can ride our buses, streetcars and metro trains for free. In “Muni Kids,” the latest episode of our Taken with Transportation podcast, we discuss the origins of Free Muni for Youth and the program’s evolution. The beginning “Free Muni for Youth … was implemented in March 2013,” SFMTA... Published 2026-08-18T00:00:00Z https://ift.tt/7uHth1z

Show HN: PantheonGPU – GPU health testing and AI workload benchmarking https://ift.tt/6rMoShc

Show HN: PantheonGPU – GPU health testing and AI workload benchmarking Hi HN, I built PantheonGPU because I wanted a better way to answer a simple question: is this GPU actually healthy and performing the way it should? A GPU can show normal temperatures and utilization and still be underperforming, unstable under certain workloads, or have memory, PCIe, or configuration issues. PantheonGPU actively tests the GPU instead of only monitoring telemetry. It currently includes 45+ tests covering compute, tensor workloads, memory, cache, PCIe, thermals, stability, and AI/LLM inference. It supports both NVIDIA CUDA and AMD ROCm. I’m also exploring a larger use case: running Pantheon across GPU fleets to identify individual GPUs that behave differently from the rest of a server or cluster. I’d especially appreciate feedback from people running AI infrastructure, multi-GPU systems, local LLMs, or GPU clouds. https://ift.tt/ZLxC4fo August 19, 2026 at 01:47AM

Show HN: macOS data protection keychain for Electron apps https://ift.tt/V9XYWus

Show HN: macOS data protection keychain for Electron apps Hey HN, I've been working on Hansel [1] (an encrypted personal data store you can query with agents), and there wasn't a good way to use the modern macOS Data Protection Keychain. Electron's safeStorage [2] uses the legacy file-based keychain, which allows other apps/agents to query it with the `security` CLI. Not great when you have a dozen agents running in the background! The Data Protection Keychain is nice because it limits access via code-signing access groups and lets you set access rules like Touch ID and/or password. 1: https://hansel.so/ 2. https://ift.tt/8RWfxcF https://ift.tt/UD012Ax August 19, 2026 at 12:25AM

Show HN: Open-source comment section widget, Disqus alternative https://ift.tt/DVZ2yGl

Show HN: Open-source comment section widget, Disqus alternative https://ift.tt/ha0GWzc August 18, 2026 at 01:06AM

Show HN: UL-SMF – Open-source linear-complexity ~300x KV-cache compression https://ift.tt/cMpuKDT

Show HN: UL-SMF – Open-source linear-complexity ~300x KV-cache compression https://ift.tt/GhJjX54 August 17, 2026 at 10:56PM

Show HN: I shrank DeepSeek V4 Flash to 57GB and it wrote a compiler on my Mac https://ift.tt/q2DJupl

Show HN: I shrank DeepSeek V4 Flash to 57GB and it wrote a compiler on my Mac I built a specialized package of DeepSeek V4 Flash 0731 (originally 284B total parameters, 13B active), preserving reasoning, tool calling and coding capabilities: https://ift.tt/oDj3zTs... I let it write a minimal C compiler targeting ARM64, then test the result with Fibonacci and FizzBuzz programs, and it succeeded in less than 1 hour, with the full recording at: https://youtu.be/XiwSilmV8B0 You can run it on Silicon Macs with my engine https://ift.tt/LApE8oI , while one of the core libraries developed to obtain this result is available at https://ift.tt/zQ6yYBK . The above recording was on a 128GB memory MacBook M3 Max, but you can also run it on 32GB MacBooks with a very usable context (128K tokens) and projected 5 tok/s. I did try it on a fanless 16GB memory MacBook Air M1 (1.39 tok/s), but unfortunately the available context was very small. How: - First, efficient quantisation: mlx-iqk takes advan...