AI Coding Live News

At GitHub Universe 2026 on Oct 28, GitHub made Copilot Fusion generally available. It merges the multi-model orchestration of the Project HydraFusion research preview with Copilot auto model selection: users pick Copilot Fusion and an effort level (Standard, High or Max) in the model picker, and the system decides which models to use and whether to run a Single, Cascade or Critique workflow. GitHub says Fusion Max scored 60 on the Artificial Analysis Coding Agent Index, two points below Claude Code with Opus 5.5 Max, at about half the API cost per task, about half the tokens and about 40% less time. Each underlying model is billed at its standard rate, and paid plans get 30% off through Nov 30.

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Perplexity officially unveiled that Perplexity Computer now operates 100% locally on macOS through the native desktop application. Breaking away from cloud-dependent computer-use paradigms that ship continuous video feeds across the internet, Perplexity Computer executes both the underlying inference model and the agent orchestration runtime directly on local Mac silicon. By interfacing natively with macOS Accessibility APIs, the system eliminates network latency, guarantees complete screen privacy, and empowers autonomous desktop copilots to orchestrate multi-application workflows entirely offline.

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Alibaba researchers introduce Cowork-Gym (arXiv:2610.17670), synthesizing 64,900 interactive human-agent coworking environments paired with a stateful user simulator that dynamically edits the shared workspace; post-training a 27B Qwen model yields #1 scores on PawBench and ClawEval, outperforming 100B+ parameter models. Concurrently, Harvard and MIT researchers open-source Market-Based Post-Training (MPT, arXiv:2610.22322), enabling decentralized agent swarms to jointly learn action policies and bidding-based self-orchestration without a central coordinator.

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OpenAI announced a major upgrade to GPT-6 Astra Pro in ChatGPT for Pro users, introducing faster response times, stronger plugin and tool orchestration, and native parallel multi-agent execution where multiple agents tackle different parts of a complex task simultaneously. Concurrently, OpenAI Developers showcased how internal engineers put always-on 'dots' agents on call to autonomously triage 3 AM production incidents, launch Codex debugging threads, and clear codebase maintenance backlogs.

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Token-level LLM routing—routing easy tokens to small models and switching to frontier models for critical reasoning tokens—presents an optimal trade-off between output quality and inference cost. However, current LLM serving engines (such as vLLM and TGI) are architected for single-model execution, suffering severe step desynchronization, batch admission latency, and extreme orchestration complexity when handling high-frequency token transfers across heterogeneous models. Researchers from Tsinghua University's NICS Lab present TokenRouter (arXiv:2610.12242, accepted at NeurIPS 2026, code: github.com/thu-nics/TokenRouter), an efficient and developer-friendly serving system engineered for token-level routed LLM inference. TokenRouter introduces a 'request-centric programming and model-centric execution' paradigm, enabling developers to write routing logic intuitively per request while the runtime handles asynchronous execution across subservers. Incorporating a Delayed-Batching Scheduler parameterized via discrete-time Markov chain modeling, a decoupled tri-loop architecture, and an instant handoff-resume mechanism, TokenRouter achieves 2.01x to 64.15x higher decoding throughput compared to existing serving platforms across diverse routing workloads, with complete code open-sourced.

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At Gemini at Work 2026 (Oct 8) Google launched the Gemini agent: objectives from one prompt box spanning Q&A, knowledge work, media, and code; cloud-persistent memory with sub-agent/coworker orchestration and Gemini+Claude model choice. Private preview now.

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OpenHands (@OpenHandsAI, formerly OpenDevin) has released v1.23.0. This release significantly upgrades the multi-agent execution pipeline and sandboxed runtime, introduces automated regression evaluation suites for complex repositories, and enhances compatibility with local inference backends like vLLM and Ollama.

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JetBrains (@jetbrains) announced JetBrains Air, an open product system for agentic software development that connects IDE-side agent orchestration, team workflows, and organizational governance (formerly JetBrains Central). Air is multi-vendor: steer Claude, Codex, Gemini CLI, and JetBrains Junie inside JetBrains IDEs, and plug in other harnesses via the Agent Client Protocol (ACP). The company blog also outlines Air Teams and Air Governance.

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