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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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Running Windows Apps on Linux: Proton, Bottles, and the Full Compatibility Stack

Running Windows Apps on Linux: Proton, Bottles, and the Full Compatibility Stack

Use Proton for Windows games on Steam. Use Bottles for everything else: Office, Adobe apps, business tools, non-Steam games. Both run on Wine, which maps Windows API calls to Linux without a virtual machine. DXVK and VKD3D-Proton handle the DirectX side. Wine 11.0 closes most of the remaining gap to native Windows.

This guide covers the full stack in 2026: what each piece does, how to set up Proton and Bottles, how to tune DirectX translation, and what still breaks.

Automate Your Pool or Hot Tub with Home Assistant and ESPHome Sensors

Automate Your Pool or Hot Tub with Home Assistant and ESPHome Sensors

Pool and hot tub chemistry can swing from safe to damaging in a few hours. A paper strip you dip once a week will not catch it. The fix is cheap: a waterproof ESPHome sensor built around an ESP32 , reading water temperature, pH, and ORP, piped into Home Assistant for pump schedules, chemical alerts, and cover reminders. A full setup runs under $80. It replaces guesswork with a live dashboard and push alerts that fire before your heater corrodes.

CSS Subgrid Reaches 92% Baseline: Align Cards Natively

CSS Subgrid Reaches 92% Baseline: Align Cards Natively

CSS subgrid lets a nested grid inherit its parent’s track sizes. Child elements inside nested components line up with the parent layout. No flat HTML, no JavaScript height math, no hardcoded min-heights. It shipped in every major browser by late 2023, sits at about 92% global usage, and is safe on any modern web project today.

Ever fought a card grid where the buttons won’t line up because one card has a longer description? Subgrid is the fix you’ve been waiting for.

A lightning-bolt-shaped racing vehicle speeds across a landscape of terminal windows while small subagents fan out and a rocket waits on a launchpad.

Gemini 3.5 Flash: 76% on Terminal-Bench, 4x Faster Output

Google released Gemini 3.5 Flash on May 19, 2026. The fast, lower-cost tier scored 76.2% on Terminal-Bench 2.1 and, by Google’s own measure, generates output about 4 times faster than other frontier models. Flash is available today across the Gemini app, Search, and the API. Gemini 3.5 Pro is confirmed for next month.

Key Takeaways

  • Gemini 3.5 Flash launched on May 19, 2026 and is free to use in the Gemini app and Google Search.
  • It scored 76.2% on Terminal-Bench 2.1, a test of finishing real terminal tasks end to end.
  • Google says Flash produces output about 4 times faster than rival frontier models.
  • The model is built for agents that run long, multi-step jobs and call tools.
  • Gemini 3.5 Pro, the larger sibling, is confirmed for next month.

What is Gemini 3.5 Flash?

Gemini 3.5 Flash is Google’s new fast, lower-cost tier of the Gemini 3.5 family. It was announced and made generally available on May 19, 2026, according to the Google announcement post . The “Flash” name has always meant a model tuned for speed and price.

Is the StarFive VisionFive 2 the Best RISC-V SBC for Developers?

Is the StarFive VisionFive 2 the Best RISC-V SBC for Developers?

For most developers wanting hands-on RISC-V in 2026, the StarFive VisionFive 2 at $65 for the 8GB model is the most practical entry point. It runs Debian 13 (Trixie) on the JH7110 quad-core SiFive U74 at 1.5GHz, ships with an Imagination BXE-4-32 GPU that now has mainline Mesa Vulkan drivers, supports Docker and NVMe via kernel 6.6+ LTS, and delivers roughly 60-70% of a Raspberry Pi 4’s single-threaded speed. That gap is smaller than you might expect when the goal is learning RISC-V toolchain internals. The ecosystem here has matured enough that you spend time writing code, not fighting drivers.

Two identical metal engine blocks on a workbench, the second one fed by funnels of code fragments and tuned by a robotic precision arm.

Cursor Composer 2.5 vs Composer 2: What Actually Changed

Cursor Composer 2.5 is an incremental upgrade over Composer 2, not a new model. Both run on Moonshot’s open-source Kimi K2.5 checkpoint, so the entire difference is training. Composer 2.5 learned from 25x more synthetic coding tasks plus targeted reinforcement learning. Standard pricing holds at $0.50 per million input tokens.

Key Takeaways

  • Composer 2.5 and Composer 2 share the same open-source base model, so only the training changed.
  • Cursor trained Composer 2.5 on 25 times more synthetic coding tasks than the older version.
  • The standard model costs $0.50 per million input tokens and $2.50 per million output tokens.
  • A faster variant exists for $3.00 input and $15.00 output per million tokens.
  • Cursor is now building a much larger coding model from scratch with 10x more compute.

What is Cursor Composer 2.5?

Composer 2.5 is Cursor’s in-house coding model and the direct successor to Composer 2. It runs inside the Cursor editor, which slots into a crowded field of AI coding tools . The model is built for sustained work, not just quick one-shot answers.

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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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