If it can be done in the terminal, it should be done In the terminal.

GLM-5.2 is Fully Open, Frontier Intelligence Belongs to Everyone Today, the sudden restriction of certain frontier models is deeply regrettable. At a time when access to frontier models is abruptly cut off for non-technical reasons, we are even more convinced of one thing: science should be global. The path to AGI (Artificial General Intelligence) must never be enclosed by high walls. We have always believed that AGI should be the cornerstone for all of humanity to collaboratively explore the boundaries of intelligence and solve complex challenges, rather than a privilege monopolized by a few rules and subject to revocation at any moment. In the face of external blockades and restrictions, our attitude is one of radical openness. Frontier intelligence must remain open-source, accessible, and buildable, serving every dedicated developer. GLM-5.2 is Zhipu's most capable open-source model to date. It not only supports a truly usable 1M context window but also maintains a continuous lead in the independent completion of long-horizon tasks, providing solid foundational support for building complex agent applications. It also continues to be our main engine for creating the strongest domestic coding model. Tonight at 5:21—at this special moment—GLM-5.2 will officially be available to all GLM Coding Plan users (including Lite / Pro / Max). The API will also go live next week. A step closer to frontier intelligence for everyone. The future of AI is open, and it is for the people. ModelKey: GLM-5.2

on solana ofc

feeling motivated. might build a startup

Kimi 2.7 Code now available in Go text · image · optimized for coding similar pricing as 2.6

🚀 Introducing Gemini-SQL2, our breakthrough text-to-SQL capability powered by Gemini 3.1 Pro! We've achieved state-of-the-art results on the highly competitive BIRD benchmark, translating natural language into execution-ready SQL queries. 🧵👇

🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced! 🔷 Improved coding & agent performance over K2.6: 21.8% on Kimi Code Bench v2, 11.0% on Program Bench, and 31.5% on MLS Bench Lite. 🔷 Reasoning efficiency: Less overthinking, with 30% lower reasoning-token usage compared to K2.6. 🔷 Long-horizon coding: Improved instruction following, higher end-to-end coding task success rates. ⚡️ 6x High-Speed Mode coming soon! 🔌 Available today via Kimi API and Kimi Code. 🔗 Kimi Code: kimi.com/code 🔗 API: platform.moonshot.ai

We released North Mini Code, our first open-source coding model, just two days ago. We’re already seeing developers using it to build amazing things ⬇️

Today, I’m proud to announce Homebrew 6.0.0. Since 5.1.0: secure tap trusting, faster JSON API, Linux sandboxing, better defaults, brew bundle improvements, improved performance, initial macOS Golden Gate support. brew.sh/2026/06/11/homebrew-…

OpenCode 1.17.3 can reference other git repos or local folders 𝚛𝚎𝚏𝚎𝚛𝚎𝚗𝚌𝚎𝚜: { "𝚎𝚏𝚏𝚎𝚌𝚝": "𝚐𝚒𝚝𝚑𝚞𝚋.𝚌𝚘𝚖/𝙴𝚏𝚏𝚎𝚌𝚝-𝚃𝚂/𝚎𝚏𝚏𝚎𝚌𝚝-𝚜𝚖𝚘𝚕" } gives it full access to the effect codebase, here's how we use it

POV: Shooting a new video for @holycreedapp I will be back.

Heightmaxxing

I used to be a "backend first" guy when building full stack applications. Now I'm a "frontend first".

OpenCode Go has crossed 100,000 subscribers now doing 1.5 trillion tokens per day

Rust Tokio → Backend Engineer Rust Actix → API Engineer Rust Axum → Systems Backend Engineer Rust Diesel → Database Engineer Rust SQLx → Async Backend Engineer Rust WebAssembly → Web Performance Engineer Rust Yew → Frontend/WASM Engineer Rust Tauri → Desktop App Developer Rust egui → Native UI Engineer Rust Bevy → Game Developer Rust wgpu → Graphics Engineer Rust Embedded Rust → Embedded Systems Engineer Rust Linux Kernel → Systems Programmer one language…multiple elite engineering paths 🫡

Eyes that see everything 👀🕊️

Every obsessed person knows that mastery comes from pattern recognition.

I recommend following @holycreedapp for daily scripture-based confessions. 👍

I have started predator avoidance training with Ajax this week since he is now officially in his fledgling era. I downloaded the audio of a wild magpie alarm call and I play it when my cat enters the room. Ajax responds very well, immediately hiding or hopping onto my shoulder. We’ve done this drill four times over a few days, including in the garden. Full marks each time. I’ll keep doing this, and after enough practice he’ll understand that the cat is the danger he’s being alerted to. This is the same way his parents would teach him in the wild. He has no instinctive fear of cats. The cat avoidance training is easier because I have a cat, but repeating this process with dogs, hawks, and cars will take a bit of planning. Really makes you appreciate all the hard work that wild bird parents put in to the next generation.