Just two weeks after Gemini 4 Argon, Google DeepMind is releasing Gemini 4 Carbon, which tops the Artificial Analysis Intelligence Index v5 with 59 points. Google says the model is built for extended agent workflows and the full cyber defense lifecycle. Because of those advanced security capabilities, access is limited to selected security experts at first. The article Google Deepmind releases Gemini 4 Carbon just two weeks after Argon with gains across the board appeared first on The Decoder.
MiniMax has open-sourced MCode Stack, the workflows and agent skills its team uses to build MiniMax Code. The MiniMax MCode Stack agent skills went public on October 28, 2026 under the MIT license. It is not a prompt collection. Each piece is a SKILL.md skill or checklist that installs directly into MiniMax Code. For developers, it turns harness engineering habits into steps an agent can actually run. TL;DR Size: 2 stacks, 17 skills (15 from Ronny, 2 from Jiachen), 5 checklists, 5 companion notes. Runs on: Any machine running MiniMax Code (Node.js 22.19+) or Claude Code. No GPU. Skills are plain Markdown. Performance: No benchmarks or eval results published. Best: long-command-check, a 10-point audit for long shell commands and background tasks. What is MiniMax MCode Stack? MCode Stack is an open-source repo of agent skills from MiniMax’s MiniMax Code team. MiniMax Code is the MiniMax’s open-source terminal coding agent, also MIT-licensed. The stack holds no MiniMax Code source code. It holds only workflows, skills and checklists. The repo pairs with a column called MCode Engineering Notes. Each note explains one idea. The repo makes that idea runnable. Published notes cover subagents, tool context, compaction versus memory and long bash commands. A note on per-turn context tax is marked upcoming. What skills are inside Ronny’s stack? MiniMax’s stack ships 15 skills, grouped by moment in the working day: Plan and split (3): subagent-split-check, engineering-small-prs, engineering-change-descriptions. Context and tools (2): tool-budget-audit, context-tax-audit. Long sessions and commands (3): long-session-check, handoff-doc, long-command-check. Review (4): independent-review, engineering-code-review, engineering-review-comments, engineering-review-feedback. Experiments and hotfixes (3): harness-experiment, trajectory-review, engineering-emergency-changes. A few ideas stand out. independent-review gives the reviewer exactly 3 inputs: the diff, the requirement and test results. It deliberately withholds the author’s conversation. The reasoning: a reviewer inheriting the author’s context repeats the author’s blind spots. subagent-split-check says to split work only when context is the measured problem. Splitting by team or question type is not a valid reason. tool-budget-audit separates 2 costs: tool definitions and tool results. Tool search mainly cuts the first. Programmatic tool calling mainly cuts the second. harness-experiment enforces 1 change per experiment. It tracks flipped tasks, requests per task, tokens, cache hit rate and wall-clock time. The long-command checklist has 10 items. It asks whether moving a command to background re-runs the process. It also asks whether unread results survive compaction. The 6 engineering-* skills are adapted from Google Engineering Practices. That material stays under CC-BY 3.0, per the stack’s NOTICE. window.addEventListener("message",function(e){var d=e.data;if(d&&d.id==="mtp-mcs"&&d.mtpEmbedHeight){var f=document.getElementById("mtp-mcs-frame");if(f)f.style.height=d.mtpEmbedHeight+"px";}}); How do you install MCode Stack? There are 3 paths, per the README: One skill: clone the repo and copy a skill folder into ~/.agents/skills/. Whole stack as a local plugin: copy stacks/ronny into MiniMax Code’s local plugin directory. Marketplace: in MiniMax Code desktop, add the MiniMax-AI/mcode-stack marketplace. This option is rolling out gradually. The same catalog works in Claude Code with /plugin marketplace add MiniMax-AI/mcode-stack. MiniMax Code also reads ~/.claude/skills/ and ~/.codex/skills/. The skills use the common SKILL.md format, so most work in other agents that support skills. How does MCode Stack compare with other skill packs? MCode Stack is narrower than both. It targets people who design agent harnesses, not only people who use agents. Superpowers covers far more harnesses today. Key Takeaways MiniMax open-sourced 17 SKILL.md skills and 5 checklists under MIT. Skills pair with MCode Engineering Notes, turning essays into runnable checks. independent-review feeds a reviewer only the diff, requirement and test results. Installs into MiniMax Code or Claude Code via a plugin marketplace. No published evals yet, so treat it as a playbook, not proof. Check out the GitHub repo and MiniMax Code. Also, feel free to follow us on Twitter and don’t forget to join our 150k+ML SubReddit and Subscribe to our Newsletter. Wait! are you on telegram? now you can join us on telegram as well. Need to partner with us for promoting your GitHub Repo OR Hugging Face Page OR Product Release OR Webinar etc.? Connect with us The post MiniMax Open-Sources MCode Stack: 15 Agent Skills Its Coding Team Uses Daily appeared first on MarkTechPost.
Google is opening up Android Studio to third-party AI agents. Through a new "Bring Your Own Agent" feature, the IDE now supports more than 40 coding agents, including Anthropic's Claude Agent and OpenAI's Codex. Google says new terminal tools also help agents finish UI tasks 77 percent faster while using up to three times fewer tokens. Android development is becoming agent-centric too. The article Google opens Android development to third-party AI agents and unveils new Gemini APIs appeared first on The Decoder.
At DevDay Exchange in Berlin, OpenAI mostly repeated what it had already announced, but it did share a few new details. The AI assistant Dots should roll out more widely in Europe "in a few weeks," and weekly Codex users in Germany have grown twentyfold since January. A clear subtext ran through the sessions and the repeated nods to ChatGPT's 1.2 billion weekly users: OpenAI wants developers to build their businesses directly on its infrastructure. The article OpenAI teases Dots for Europe, but its Berlin DevDay was really about building a platform appeared first on The Decoder.
Anthropic is adding pre-built templates to Claude for Legal. These interactive overviews and tables simplify setup for legal teams and speed up routine work like contract reviews, while more than 60 integrations let firms connect their own databases directly. The article Claude for Legal now verifies sources automatically, then hands the file to a lawyer appeared first on The Decoder.
Nvidia has released Nemotron 3.5 Transcribe, an open speech recognition model that handles transcription, speaker recognition, and translation and takes its instructions as text prompts. It leads several benchmarks and uses only a sixth of the active parameters of its strongest open rival. Nvidia is also shipping a dataset with more than 800,000 hours of speech, along with tools for fine-tuning. The article Nvidia's open Nemotron 3.5 Transcribe combines transcription, translation, and speaker recognition appeared first on The Decoder.
Artificial Analysis overhauled its Intelligence Index, causing Kimi K3.1 Pro to drop five spots in the rankings. The article New Artificial Analysis index widens the gap between open and closed models appeared first on The Decoder.
Anthropic manager Felix Rieseberg says the classic coding interview is dead because Claude now solves small programming tasks better than job candidates do. He'd rather see prototypes that show taste, empathy, and principled thinking, since in his words, "hunger beats tenure." That sounds empowering, but it pushes the bar for newcomers toward entrepreneurial thinking and assumes a hustle mentality not everyone brings to the job. The article With AI writing the code, entrepreneurial thinking is now what counts most for newcomers at Anthropic appeared first on The Decoder.
Cybersecurity startup Cathedral used AI agents to break into Anthropic's internal systems through third-party software as part of a bug bounty program. Anthropic confirmed access to sales, HR, and IT data but disputes how deep the breach went. The incident shows how vulnerable even leading AI labs are through their external software dependencies. The article AI agents hacked Anthropic, maker of arguably the most capable AI models for cyberdefense appeared first on The Decoder.
