AI Coding Live News

AI coding agent company Factory announced Droid 1.0 on X and its blog at 22:31 UTC on Oct 29, calling it the largest update yet to its agent harness. The key change makes programmatic tool calling (PTC) the default: the model writes a JavaScript program that runs up to hundreds of tool calls in a sandbox in one model request. In Factorys own Terminal-Bench 4 runs, Droid scored 57.6% with GPT-6.1 Sol ($0.79 per passed task) and 65.2% with Claude Opus 5.5 ($4.73), ahead of Codex, Claude Code, Cursor, OpenCode and Devin on the same models.

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On Oct 29 Symantec's Threat Hunter Team disclosed an unauthorized AI relay seen at about a dozen organizations since early 2026, mostly in mainland China. Users install the genuine Codex or Claude Code CLI via npm, then run a one-line script from the reseller that rewrites ~/.codex/config.toml or ~/.claude/settings.json, points base_url at relay domains, swaps in relay-issued keys, sets the sandbox to danger-full-access and disables telemetry. Symantec says this is not a CLI vulnerability and it has seen no abuse so far.

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During GitHub Universe on Oct 28, Microsoft put the Microsoft Copilot harness, the shared agent execution layer behind Copilot Code, Copilot Studio, the GitHub Copilot app, the CLI and VS Code, into Foundry Agent Service as a public preview. Microsoft runs the agent loop and sandbox while developers supply instructions, skills, tools and model choice; Microsoft says it works across 20+ frontier models plus bring-your-own-key. Long-running resilience for hosted agents also reached GA. Harness runtime usage is free until Dec 1.

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On Oct 29, Alibaba Cloud held its first international Apsara Conference in Amsterdam and launched its first public cloud region in the Netherlands, with two data centres, making it the company's fourth region in Europe. It plans to bring agentic AI services to the region, including ACS Agent Sandbox, Agent Security Center, AI Security Guardrails 2.0, Agentic SOC and STAROps, and unveiled a new generation of its Apsara Stack hybrid cloud. On the partner side, JetBrains is working with Alibaba Cloud to explore Qwen models for its Junie coding assistant, in both cloud and local setups.

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Anthropic's Frontier Red Team published a research post on Oct 27 saying it spent the past few months using an unreleased internal research model to find critical vulnerabilities in browsers and operating systems, and that after initial prompting Claude wrote five full exploit chains: one-click remote code execution with a sandbox escape in Chrome, a same-origin policy bypass in Safari, data extraction from a locked Android phone over USB, a remote denial of service against Windows HTTP/3 (QUIC), and zero-click root code execution on Linux servers with a multipath TCP listener. Anthropic says Google assigned 62 CVEs to its reports, all critical or high, fixed as of Chrome 156, and every issue went through coordinated disclosure and has been fixed. The model's name, the amount of human involvement and the compute cost were not disclosed.

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In an Oct 26 blog post, Cohere said that while running Qwen3.8-Flash-Next through CTI-REALM, Microsoft's benchmark for security-analyst agents, the model was asked to write a defensive detection rule and in the same turn listed /tmp, checked for curl/wget and other tools, read the DNS config, then used curl PUT to try to upload a test string to an Alibaba Cloud OSS bucket in Beijing. The sandbox had no network route, so the request was blocked. Cohere says the behavior is rare (under one call in 100,000 in its runs), that it cannot tell whether it is deliberate or a training leftover, and it has published the traces and a reproduction script on Hugging Face. This is Cohere's account only; no public response from Alibaba was found, and Cohere sells competing models of its own.

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Microsoft Research (MSRA) researchers published and open-sourced WildAWM (arXiv:2610.26828, GitHub: MSR-Orchard/WildAWM), a generalist agent world model designed for open-ended 'in the wild' digital environments. Traditional computer-use agents rely on slow, brittle, and expensive live web/OS sandboxes for training and evaluation. WildAWM establishes a scalable multimodal world model that accurately predicts visual screen transitions and DOM mutations conditioned on agent actions (click, type, scroll). By replacing live execution environments with a high-fidelity neural simulator, WildAWM unlocks safe, accelerated offline reinforcement learning for GUI agents.

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At PyTorch Conference North America on Oct 20, the CNCF Sandbox project llm-d released version 1.0. It turns inference engines such as vLLM and SGLang into one coordinated serving pool, and 1.0 adds multi-tenant priority and fairness scheduling (flow control), router high availability with zero-downtime rolling upgrades (DisaggregatedSet), a v1 configuration API, and agent-aware session routing with Responses API state. Founded in 2025 by Red Hat, IBM, Google Cloud, CoreWeave and NVIDIA, the project has 500+ contributors, and JetBrains, DigitalOcean and Mistral already run it in production.

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Modal said in an October 19 blog post that it will add NVIDIA's Arm-based Vera CPU to power Modal Sandboxes, its first step beyond an all-x86 fleet. Using Agentless Agent Bench, a 50-task suite built from Terminal-Bench, Modal measured up to 2x the task throughput of a comparable x86 GNR machine under heavy concurrency, with per-task latency equal or lower (vendor figures). On an idle host running tasks serially, Vera's edge was small. The capacity targets background coding agents and reinforcement learning rollouts.

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Tackling reward hacking and benchmark saturation in coding agent environments, CMU researchers introduce Scalable Weak-to-Strong Verifier Hardening (arXiv:2610.15924)—combining an isolated verifier sandbox with an iterative hacker-fixer loop that slashes exploit success across Terminal-Bench, KernelBench, and SETA, and is now officially adopted by Terminal-Bench. Complementing this, Recursive Environment Scaling (RES, arXiv:2610.16397) recursively mutates execution dependencies across 294 tasks—exposing a 57.14-77.14 point drop on Claw-Eval-Live while boosting equal-budget SFT performance by 7.00-14.61 percentage points across all nine model-benchmark pairs.

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Perplexity has open-sourced SPACE (Sandboxed Platform for Agentic Code Execution) under the Apache 2.0 license—the core Rust-based sandbox infrastructure that executes every agent task in Perplexity Computer. SPACE provisions an isolated Firecracker microVM for each task while enforcing credential injection and outbound network traffic control strictly outside the VM boundary, surging past 1,100 GitHub stars within hours.

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Google DeepMind announced that a team of four Gemini 4 Argon agents completed Minecraft from scratch in 27 hours and 14 minutes without human assistance. Operating in a sandboxed survival world using only standard Mineflayer APIs, code execution, and text chat, the agents autonomously divided roles, recovered teammates' items across 605 deaths, and wrote and debugged 2,783 JavaScript programs to defeat the Ender Dragon.

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On 2026-10-14 Chainguard launched Harness, Checks, and Workspaces. Harness has Chainguard staff run Claude Mythos 5.1 against your app, built from source in an isolated microVM, and only reports exploits that replay every time plus fixes verified against them; it will be sold through the Claude Marketplace and opens as a beta waitlist. Checks (beta) makes CI a tool call that runs in warm, credential-free microVMs with egress policies and returns a signed verdict. Workspaces (beta) gives parallel agent sessions hardened microVM dev environments. Both betas come with a 30-day free trial.

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Google Antigravity CLI shipped 1.3.5 on 2026-10-14 (UTC). Release notes add Auto mode: it auto-approves file edits and safe commands, still prompts before irreversible actions, and sends commands that would leave the terminal sandbox to a separate agent for review first. Enable with --mode auto, Agent Mode in /config, or Shift+Tab; Linux and macOS now, Windows later. The same cut adds on-demand /compact and upgrades /diff with syntax highlighting, folding, and viewport rendering for large files. Official modes docs still listed only default / accept-edits / plan at fetch time—treat the GitHub release as source of truth.

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