AI Coding Live News

On Oct 26 OpenAI released GPT-6.1 Terra, an efficient model for visual reasoning, precise computer use and natural writing. It is rolling out today to Plus, Pro, Enterprise and Edu users in ChatGPT Work and Codex, and in the API as gpt-6.1-terra. Standard API pricing is $1 input, $0.05 cached input and $5 output per million tokens, which OpenAI says is 50% lower than GPT-5.6 Terra and GPT-6.1 Sol, with a 1,050,000-token context window. By OpenAI's figures it scores 15 points higher than GPT-5.6 Terra on Agents' Last Exam at medium effort for about a third of the cost, and solves 50.3% of Terminal-Bench 4.0 at max effort.

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On Oct 26 Cursor announced that its Agent SDK is generally available. An agent's system prompt is written in Markdown and its tools in TypeScript; agents can be deployed on Cursor's hosted infrastructure or run on your own machines, and built-in evals measure every change. Cursor's docs say it uses the same Cursor SDK harness that powers Bugbot, Security Review, Approval Bot and Rollouts, can be triggered from source-control events, issue trackers, Slack or schedules, and is managed under Deployed Agents after deployment. Cursor has not published pricing or benchmarks.

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On Oct 26 Apple released iOS, iPadOS, macOS, watchOS and visionOS 27.2, and Siri AI (beta), the assistant rebuilt on Apple Intelligence, now supports French, Japanese, Korean, Portuguese and Spanish in addition to English. Apple says Traditional Chinese, Norwegian, Turkish and Vietnamese will follow by the end of the year. Per the iOS 27.2 release notes, Siri AI can now recall past conversations and draw on more sources such as photos in Messages, Calendar attendees and voicemails. Siri AI is still unavailable in the EU on iOS, iPadOS and watchOS and in mainland China, and server-side features have daily usage limits; Apple says expanded access will be offered for a fee in the future.

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On Oct 26 Anthropic released the Claude for Nonprofits plugin, a set of skills and connectors built with about 30 nonprofits. It covers the full fundraising cycle (finding funders, breaking down RFPs, drafting proposals and reports, donor stewardship), marketing, hiring and board work, and starts by having Claude map where the organization keeps its records and answer questions against the organization's own AI policy. It is installed automatically at no extra cost for verified nonprofits on Team and Enterprise plans. Anthropic says more than 25,000 nonprofits use Claude, and over 75% of them have fewer than 10 seats.

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On Oct 26 Mirendil unveiled Fern, its first model, pretrained from scratch on its own Mirendil-Base (0.1-0.5T params) with a context window of up to ~10M tokens, about 0.5M lines of code or days of agent traces. Fern 0.1 got only a short round of post-training and targets AI R&D work such as auditing training data, debugging runs from logs and reading agent traces end to end. Vendor-reported: 73.4% on SWE-Bench Verified and 100% single-needle RULER retrieval at 10M, while multi-hop QA drops to 45% at 10M. Access is early-access only; no price or weights yet.

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On Oct 26 Tencent Hunyuan (Tencent Hy) open-sourced Hy-SimulMT, a real-time simultaneous interpreting model for bidirectional Chinese-English speech-to-speech translation. It translates while the speaker talks, outputs both translated text and speech, and can clone the speaker's voice in real time. Six checkpoints landed on Hugging Face (30B-A3B translation-only and source-plus-translation Interleave variants, each in BF16, FP8 and GGUF), with the model card listing Apache-2.0; GitHub ships the SimulInfer serving stack and SimulTrain training tools. Vendor-reported: about 3s StreamLAAL on RealSI long-form audio, the lowest among compared systems.

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At Oracle AI World in Las Vegas on Oct 26, Oracle announced Oracle Fusion Claw, a new execution runtime for agents, and 25 Claw-powered Agentic Applications now available across ERP, HCM, supply chain (SCM) and customer experience (CX). It also introduced Fusion Companion and Fusion Agentic Home: employees describe a goal in natural language in supported AI tools such as ChatGPT or in the native Fusion interface, and the system picks and coordinates the transactions, workflows, approvals and AI agents needed, within existing identity, permission and approval controls. Oracle has not published pricing, benchmarks or a detailed rollout schedule.

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On Oct 26 Springer Nature, one of the world's largest research publishers, announced a research partnership with Google DeepMind to co-design an AI peer review assistant. It uses DeepMind's frontier Gemini models and builds on Google's earlier agentic research tools ScholarPeer and Deep Review to help reviewers navigate manuscripts, analyse large amounts of text, charts and figures, and flag areas that may need closer attention. The system is built with Google's open-source Agent Development Kit (ADK) and runs only inside Springer Nature's private Gemini Enterprise environment, so manuscript content stays in its secure environment. A prototype is being tested; the publisher stresses 'human first, AI second' and has not given a launch date or any performance data.

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At 15:58 UTC on 2026-10-25, developer Thorsten Ball (@thorstenball) published an X article, "How I work with Agents" (post), summarizing how he works with coding agents "as of October 2026": use only the latest and strongest models, prompt for what you want rather than how to do it, make the whole development lifecycle from deploys to production logs visible to the agent, ask agents for "irrefutable proof", and review only code with a high blast radius. When we pulled it, the post had about 1,935 likes, 143 reposts, 92 replies, 3,981 bookmarks and 137K views, and it reached X's trending stories. This is a personal account of practice presented as opinion, not a verified conclusion.

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