Botmonster Tech

Google shut down Gemini CLI on June 18, 2026, pushing free, Pro, and Ultra users onto the closed-source, Go-based Antigravity CLI . You can keep the open-source Gemini CLI running with a paid API key, but its separate quota pool is gone. Enterprise and Code Assist Standard licenses still work unchanged.

What happened to Gemini CLI?

On June 18, 2026, Gemini CLI and the Gemini Code Assist IDE extensions stopped serving requests for free, Google AI Pro, and Ultra personal accounts. The Google Developers Blog announcement confirmed the cutoff and named the replacement: Antigravity CLI, run with the command agy.

Thirty days of COSMIC Desktop 1.0 on Pop!_OS 24.04 LTS, and I am keeping it. Switch if you are a keyboard-first developer who wants a real tiling-plus-floating hybrid, appreciates Rust-grade stability, and likes a UI that sits under 900 MB at idle. Wait a release or two if you depend on a big GNOME extension collection, niche input methods (CJK/IBus edge cases), or a heavy accessibility stack. The COSMIC Store’s catalog is still smaller than Flathub’s GNOME Circle or the KDE offerings, and only a handful of third-party cosmic-ext-* applets exist in 2026. Everyone else should at least boot the live ISO before deciding. COSMIC 1.0 is the first new Linux desktop in a decade that does not feel like a fork of something older.

For most typists, thick 1.5mm doubleshot PBT in Cherry or MT3 profile is the best all-around pick. It resists shine for years, produces a balanced clack-to-thock profile, and holds crisp legends through daily abuse. Competitive gamers who care about fast finger-to-finger transitions still prefer ABS sets like GMK for the slicker surface and lower friction, while RGB builders should choose polycarbonate sets for maximum backlight bleed. If you want the deepest thock on a gasket-mounted board and don’t mind a slippery texture, POM sets like Keyreative POM or TOFU POM sit at the premium end.

The SWE-bench Verified leaderboard in June 2026 is led by OpenAI’s GPT-5.5 at 88.7%, with Claude Opus 4.7 a step behind at 87.6% and GPT-5.3-Codex at 85.0%. Anthropic’s June flagships, Opus 4.8 and the new Fable 5, ship as the current top Claude models but have not landed on the public board yet. Pick a different benchmark and the order flips. On SWE-bench Pro, Claude Opus 4.7 leads at 64.3%. On Terminal-Bench 2.0 , Codex CLI paired with GPT-5.5 tops the chart at 82.0%, while the cheaper, faster Gemini 3.5 Flash hit 76.2% on the newer 2.1 set with output about 4x faster. LiveCodeBench favors Google. There is no single best AI coding model. There is only a best model for the kind of task you care about, and the agent scaffold around that model can shift scores by several points.

Why PV Self-Consumption Matters Right Now

A 7.4 kW wall box pulling a flat 32A through a sunny afternoon is the worst load profile for a house with rooftop solar. It ignores what the panels do. It drags power from the grid during the cheapest hours of the day. It forces the inverter to dump the surplus at whatever feed-in rate your utility feels like paying that month. Since the post-2023 collapse of feed-in tariffs across Europe, that rate is painful. Export rates in Germany, the Netherlands, and the UK now sit around 6-8 cents per kWh. Retail import hovers between 28 and 35 cents. Every exported watt is a 20-cent loss. Every imported watt while the sun is up costs the same.

Running private n8n and Ollama AI automations at home costs $0/month in software, but the hardware bill is real. The honest anchor: a used 64GB Mac Studio near EUR1,995 can replace a $90 to $125 monthly cloud bill, yet local tool-calling stays broken until you raise Ollama’s default num_ctx from 2048 to 8192.

What is the n8n and Ollama local AI stack?

Ollama is the local engine that runs language models on your own machine. It serves them over port 11434, so anything on your network can send prompts to it. The same engine powers other local builds, like an Ollama-driven terminal assistant wired into shell scripts. n8n is the workflow orchestrator. It has over 400 integrations and dedicated AI nodes, so you can chain a model into real automations.