World Wire

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...

Samaya AI has released Samaya Sterling , a post-trained model for agentic financial research. Sterling is built on NVIDIA’s Nemotron 3.5 Lightning , a 30B mixture-of-experts model with 3B active parameters. On Samaya’s FrontierFinance benchmark , it scores 58.9%. Claude Fable 5.1 scores 55.9%. Each Sterling question costs $0.61, against $6.89 for Fable 5.1. For developers, the takeaway is a concrete recipe: co-train a small model with its harness, and it can win in a narrow domain. TL;DR Size: 30B total, 3B active (MoE). Base model context: up to 1M tokens. Sterling’s serving context: not disclosed. Runs on: the base model fits a single H100 80GB in BF16 (256K context). Sterling’s serving hardware: not disclosed. Performance: beats every high-quality system on the FrontierFinance leaderboard on quality per dollar (self-reported). Best: 58.9% on FrontierFinance (60.6% in high-effort mode), vs 55.9% for Claude Fable 5.1. Worst: 45.2% ...