The best silent switches in 2026 use dual-damping silicone pads and high-quality TPE materials to eliminate both the “clack” of bottoming out and the “ping” of the spring returning - all without reducing the satisfying tactile bump that makes mechanical keyboards worth using in the first place. If you want truly quiet office typing, look for “Silent Linear” options that combine factory lubing with a dampened bottom-out for a deep, muted sound.

Professional Home Assistant dashboards are achieved by using custom CSS Grid layouts and HACS cards like button-card to create responsive, mobile-first interfaces. Moving beyond the default grid allows you to design a “control center” that looks like a native high-end app rather than a scrolling list of toggles. This guide walks through every layer of that transformation - from understanding why the default UI falls short, to applying CSS Grid fundamentals, building a cohesive theme, structuring room-based navigation, and making everything work beautifully on the HA Companion App.

CSS container queries (@container) style components based on the width of their parent container instead of the browser viewport. Add container-type: inline-size to a parent element, write @container (min-width: 400px) { ... } rules on the children, and those children automatically adapt their layout based on the space available to them - not the screen size. All major browsers have supported container queries since early 2023 (Chrome 105+, Firefox 110+, Safari 16+), and as of 2026 they sit at over 96% global support according to Can I Use .

Fixing LLM hallucinations in production requires a layered defense strategy: rigorous Chain-of-Verification steps at inference time, grounding the model’s output in verified external data sources, and automated evaluation suites that give you a hallucination rate you can track and regress against in CI . No single technique eliminates the problem, but combining prompt-level constraints, retrieval-augmented grounding , inference-time self-verification, and architectural validation layers reduces it to a manageable - and measurable - engineering challenge.

You can breathe new life into a 2012–2015 MacBook Pro by replacing the HDD with an SSD and installing a lightweight Linux distribution. A machine that felt sluggish and unsupported under macOS becomes a snappy, capable computer for web browsing, writing, and development work. This transformation keeps perfectly functional hardware out of landfills and provides a secure, up-to-date machine for years more of productive use.

Which MacBook Models Are Worth Restoring in 2026?

Not all old MacBooks are equal candidates for Linux revival. The most important factor is hardware upgradability - and Apple’s transition from user-serviceable to sealed hardware is a hard dividing line.

Bayesian sensors in Home Assistant give you a single, highly reliable presence signal by fusing multiple weak signals - phone Wi-Fi, GPS zones, motion detection, power consumption, and more - into a calibrated probability estimate. Instead of asking “is this one sensor on?”, the bayesian platform asks “given everything I can observe right now, how confident am I that someone is home?” The result is a presence system that tolerates sensor dropouts, handles sleeping occupants, and eliminates the embarrassing moment when the lights click off while you are sitting on the couch.

Matter-over-Thread provides a more universal standard for device interoperability, but Zigbee2MQTT remains superior for power users who require deep, local control over a wide range of legacy hardware. Most 2026 home automation setups benefit from a hybrid approach: use Matter for new purchases and energy management devices, while keeping your existing Zigbee network intact for battery-powered sensors and the thousands of devices that will never ship a Matter firmware update.

A private voice assistant that runs entirely on your own hardware - no Amazon, no Google, no cloud - is not just achievable in 2026, it is genuinely practical. Using Whisper v3 for speech-to-text, a quantized Llama model for intent parsing, and Piper for natural text-to-speech synthesis, you can build a voice-controlled home automation system on a Raspberry Pi 5 that never sends a single audio sample outside your home network. This guide covers every layer of the stack, from wake word detection to Home Assistant integration, with a focus on minimizing latency so the experience actually feels like a real assistant rather than a science project.