World Wire

The DeepSeek Harness team just released dsh-superagent , an MIT-licensed research prototype. DeepSeek dsh-superagent is a proactive coding agent for one GitHub repository. It is packaged as a bundle for DeepSeek Harness . It listens to GitHub and, optionally, Feishu. It turns allowed requests into parallel work items, each in its own agent session. The release shipped alongside a design post, Exploring Super-agent Design: Towards a More Autonomous Agent System . TL;DaR What is it?: A TypeScript bundle, v0.1.0, released as 1 commit under MIT. It uses whatever model the Harness profile is set to. Runs on: Your own machine, as a dedicated DeepSeek Harness profile. Needs Node.js 22.19+ or 24+, git 2.32+, Python 3.8+, tmux and GitHub CLI 2.48+. Performance: In DeepSeek’s simulation, it finished tasks far faster under a noisy message stream than a single-session agent. Best: p95 task completion of 15.7 minutes vs 29.5 minutes for the single-session baseline (ab...

Factory has released Droid 1.0 , the largest update yet to the Factory Droid agent harness. The main change is programmatic tool calling, now on by default. The model writes a program that runs its tools. One model request can now drive hundreds of tool calls. TL;DR Size: Base prompt is 13,055 input tokens, down 37% from 20,887. Only 2 tool definitions ship up front, down from 11. Runs on: macOS and Windows desktop app, a terminal UI, and the Node SDK @factory/droid-sdk . Works with any supported model, including your own API keys. Performance: Highest pass rate of every harness Factory tested, on the same model, at lower cost. Best: 65.2% on Terminal-Bench 4 with Claude Opus 5.5, at $4.73 per passed task (self-reported). Worst: With GPT-6.1 Sol, Droid takes 10% longer per passed task than Codex. What is Droid 1.0? Droid 1.0 is a model-independent coding agent harness from Factory. Factory defines a harness as everything around the model. That me...

Vercel Labs has released agent-desktop , an open-source CLI for AI agent computer use on macOS, Windows and Linux. agent-desktop reads each app through the operating system’s accessibility tree, not through screenshots. An agent gets a JSON snapshot with a ref for every element it can act on. Version 1.0.2 shipped on October 30, 2026, under Apache-2.0. For developers, any shell-capable coding agent can now drive native apps without a vision model. TL;DR Library: Rust CLI and a C library. 60 command names, 56 operational . Runs on: macOS 13+, Windows 10 1809+ or Server 2019+, Ubuntu 24.04+ , on x64 and ARM64. Plain CPU, no GPU. Performance: Deterministic, retry-safe ref actions. No independent computer-use benchmark yet. Best: 78% to 96% fewer tokens on dense Electron apps via skeleton traversal ( self-reported ). What is agent-desktop? agent-desktop is a Rust CLI and C library from Vercel Labs for reading and operating desktop apps. It is a tool...

Anthropic, OpenAI, Cloudflare and Google now each ship an AI agent that hunts security bugs in source code. We checked the repos, docs and technical details behind each one. The key finding: all 4 tools converge on one design. One agent finds a bug, a separate agent tries to disprove it, and only survivors get a patch. The differences are in where they run, who can use them and how much proof they demand. Key Takeaways 4 labs, 1 pattern: find, independently disprove, then patch. Claude Security runs inside Claude Code; no extra API key needed. Codex Security’s CLI is Apache-2.0, but scanning still needs OpenAI access. Cloudflare’s skill is MIT, model-agnostic and the most-starred at 47.5K. Google’s Mantis reproduces bugs in a sandbox; Google says isolate it. Why 4 labs shipped the same thing in 2026 The problem every one of them is solving is noise. Google’s security team writes that sloppy AI code scanning produces hallucin...