GoKawiil
Tech News
Microsoft used AI agents to convert the Copilot runtime's 430,000 lines of TypeScript into 800,000 lines of Rust, a project that took about 14.5 weeks, over 135 releases, roughly $120,000 in AI token costs, and three weeks of human developer oversight to fix dozens of regressions. The Rust version now powers Copilot across VS Code, Visual Studio, the CLI, SDK, and Office apps like Excel and Outlook.
A new open-source project called Algo-Trading-Skills packages 501 reference implementations covering algorithmic trading engineering, spanning 16 technical domains and five regulatory/exchange frameworks. Each skill is backed by unit tests (over 20,000 total) and follows the agentskills.io SKILL.md standard, making it usable by Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI, and similar tools. It's released under Apache 2.0 and explicitly framed as engineering guidance, not financial or compliance advice.
Microsoft is expanding GitHub Copilot's coding agent to manage more of the software development pipeline, including setting up Windows development environments, running linters and tests, and opening pull requests for human review. GitHub also added agent support for Windows Subsystem for Linux, helping teams that build on Windows but test or deploy on Linux. Microsoft Distinguished Engineer David Fowler said on X that 'typing code is absolutely over,' pointing to a shift in what developers actually spend time doing.
Microsoft has launched Project Zenith, a stripped-down version of Windows 11 aimed at AI developers, requiring at least 64GB of unified memory and 250GB/s memory bandwidth. It will debut on AMD's Ryzen AI Halo hardware, a rival to Nvidia's DGX Spark, before expanding to other OEM devices, and ships preloaded with tools like VS Code, GitHub Copilot, Python, WSL, and .NET 10 already configured for coding.
Microsoft and hardware partners will sell high-end PCs later this year running Windows 11 Pro pre-configured under a program called Project Zenith, which tweaks default settings to reduce clutter and bundles tools like Visual Studio Code, GitHub Copilot, PowerToys and Windows Dev Skills. These machines require at least 64GB of unified memory and 250 GB/s of bandwidth to run local 30-billion-parameter AI models, with AMD Ryzen AI Halo devices launching first.
GitHub has launched Project HydraFusion, a research preview available through the /experimental flag in GitHub Copilot CLI. Instead of picking one model, HydraFusion builds an execution plan that draws on multiple AI models from different providers, using them to draft, critique, revise, or escalate tasks to stronger models as needed. Developers select it like any other model, and it automatically manages the underlying workflow while charging standard per-model token rates.
Microsoft has branded its developer-optimized Windows configuration Project Zenith, targeting new devices with 64GB or more of unified memory. AMD introduced the first such device at IFA, a compact PC built on Ryzen AI Halo chips, with more machines using other silicon expected in coming months.
Marty Lamb argues that as coding agents drive the cost of writing software toward zero, the deeper skill of understanding that code is quietly becoming optional. He warns that offloading writing, review, and testing to AI lets developers skip building the mental models that manual coding used to force on them by default.
A software engineer describes a personal experiment begun in February where they stopped writing code manually and instead relied entirely on AI coding agents like Copilot, Cursor, and Claude Code to implement changes. The account traces how tooling evolved from simple autocomplete suggestions to agents capable of editing multiple files from a single natural-language description, sharply reducing the amount of typing required.
Microsoft has shipped the first official release of the Agent Lightning Skill, a tool that helps coding agents systematically improve other AI agents. Users supply an editable agent and a benchmark, and the skill guides iterative changes to prompts, tools, workflows, models, and reasoning settings. It installs directly into Claude Code, Codex, or GitHub Copilot via a simple CLI command.