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Hands-on experience with AI, self-hosting, Linux, and the developer tools I actually use

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Hands-on experience with AI, self-hosting, Linux, and the developer tools I actually use

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NVMe Gen5 Linux Benchmarking: 12K-14K MB/s Expected Performance

NVMe Gen5 Linux Benchmarking: 12K-14K MB/s Expected Performance

To benchmark your SSD on Linux, use fio for full sequential and random I/O tests, hdparm for a quick sequential read check, and GNOME Disks for a visual one-click run. A healthy Gen5 NVMe drive (a Crucial T705, Samsung 990 EVO Plus Gen5, or WD Black SN8100) should hit 12,000-14,000 MB/s sequential reads and over 1,200,000 random 4K read IOPS. Gen4 drives top out near 7,000 MB/s sequential and 800,000-1,000,000 IOPS. If your numbers fall well short, there is usually a clear reason: heat throttling, a PCIe slot at the wrong generation, or a bad I/O scheduler setting.

5 Open Source Repos That Make Claude Code Unstoppable

5 Open Source Repos That Make Claude Code Unstoppable

Five open source repositories dropped in March 2026 that expand what Claude Code can do. Karpathy’s AutoResearch runs overnight ML experiments without you. OpenSpace makes agent skills fix and improve themselves. CLI-Anything turns GUI software into agent-ready command-line tools. Claude Peers MCP lets many Claude Code sessions coordinate on one machine. And Google Workspace CLI opens Gmail, Drive, Calendar, and Sheets to agents. All five are free, open source, and plug right into Claude Code.

ControlNet for Stable Diffusion: Sketch-to-Image, Depth Control

ControlNet for Stable Diffusion: Sketch-to-Image, Depth Control

ControlNet lets you steer Stable Diffusion with spatial inputs: hand-drawn sketches, Canny edge maps, depth images, or OpenPose skeletons. The output then follows your layout, not your prompt alone. You feed a control image next to your text prompt. The model builds artwork that matches the structure of your input. It then fills in texture, lighting, and detail from the prompt. You get pixel-level control that no prompt tweak can match.

Pi-hole and Unbound DNS: DNSSEC, QNAME Minimization, Privacy

Pi-hole and Unbound DNS: DNSSEC, QNAME Minimization, Privacy

Every DNS query your devices make tells a story. When your home network sends those queries to Google (8.8.8.8), Cloudflare (1.1.1.1), or your ISP’s resolver, that provider builds a record of every domain every device visits. Your phone, your laptop, your smart TV, your thermostat: all of it. You can fix this. Run Pi-hole as a DNS sinkhole to block ads and trackers across the whole network. Then pair it with Unbound , a local recursive resolver, so your queries go straight to the DNS root servers instead of a third-party middleman.

Smart Home Network Segmentation: VLANs and Firewall Rules

Smart Home Network Segmentation: VLANs and Firewall Rules

Placing IoT devices on a dedicated VLAN with firewall rules that block all traffic to your main network - except specific connections to your Home Assistant server - prevents a compromised smart bulb or camera from becoming a pivot point into your personal computers and NAS. This setup works with consumer-grade managed switches and either UniFi or OpenWrt routers, and takes about an hour to configure properly.

The core idea is straightforward: instead of trusting every device on your network, you divide the network into isolated segments and only allow the traffic you explicitly approve. Your smart plugs, cameras, and voice assistants get their own network segment where they can reach the internet and your home automation server, but nothing else. If one of them gets compromised, the attacker is stuck in a sandbox with no path to your laptop or file server.

Generating SVG Graphics with AI

Generating SVG Graphics with AI

For precise technical diagrams, prompt an LLM to output SVG or Mermaid.js syntax instead of pixel-based images. This creates lightweight, resolution-independent graphics that search engines can read. Vector formats offer performance and clarity that raster images simply can’t match.

Why SVG? The Case Against Raster Images for Technical Diagrams

Most bloggers use screenshots or PNG exports for diagrams. This habit seems easy but carries hidden costs. A PNG flowchart often weighs 100 KB to 400 KB. In contrast, the same SVG diagram usually stays between 5 KB and 20 KB. This huge difference improves Core Web Vitals metrics like Largest Contentful Paint. Better performance helps your search rankings.

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Most Popular

Gemma 4 vs Qwen 3.5 vs Llama 4: Which Open Model Should You Actually Use? (2026)

Gemma 4 vs Qwen 3.5 vs Llama 4: Which Open Model Should You Actually Use? (2026)

Gemma 4, Qwen 3.5, and Llama 4 compared on benchmarks, licensing, speed, and hardware so you can pick the right open model fast.

5 Open Source Repos That Make Claude Code Unstoppable

5 Open Source Repos That Make Claude Code Unstoppable

Five March 2026 repos extend Claude Code with autonomous ML, self-healing skills, GUI automation, multi-agent coordination, and Google Workspace access.

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DeepSeek V4 Tech Report: 3 Tricks That Cut Compute 73%

DeepSeek V4 ships 1.6T parameters and 1M context using only 27% of V3.2's inference FLOPs. Inside the hybrid attention, mHC residuals, and Muon optimizer.

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GPT 5.5 Reddit Reception: Goblins and the Cost Backlash

GPT-5.5 Reddit reception: viral goblin prompt leak, doubled pricing backlash, and 5.4 holdouts citing hallucination regressions in factual recall workflows.

What X and Reddit Users Are Saying about Claude Opus 4.7

What X and Reddit Users Are Saying about Claude Opus 4.7

How power users on X and Reddit reacted to Claude Opus 4.7: praise for agentic coding, token burn concerns, and teams' practical prompting habits.

Qwen3.6-35B-A3B: Alibaba's Open-Weight Coding MoE

Qwen3.6-35B-A3B: Alibaba's Open-Weight Coding MoE

Alibaba's sparse Mixture-of-Experts: 35B total parameters, 3B active per token. Q4 quantization runs on MacBook Pro M5, matches Claude Sonnet performance.

Alacritty vs. Kitty: Best High-Performance Linux Terminal

Alacritty vs. Kitty: Best High-Performance Linux Terminal

Alacritty vs Kitty in 2026: emoji and Unicode rendering, real benchmarks, latency, memory, maintainer reputation, and the right terminal for your workflow.

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