AI Coding Live News

On the evening of November 2, SenseTime released the official version of SenseNova 6.8 Flash, a multimodal agent model with two main upgrades. First, long-term memory and proactive interaction: it keeps user goals and constraints across tasks and sessions and flags affected items when information changes. Second, design generation across Web, SVG, Three.js, Blender, animated PPT and motion posters, with Figma integration. It is live in SenseNova Studio, the Raccoon assistant and the SenseNova Token Plan; the official X account says the Token Plan offers a free trial of 1,500 API requests every 5 hours. SenseTime says it beats some international frontier models on agent collaboration, data analysis and presentation generation, but the announcement lists no specific scores.

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Moonshot AI's official Kimi account announced 3D Make at 03:14 UTC on Oct 30, saying Kimi connects to tools such as Blender and CAD software to create models, assemble scenes and develop games, available now on kimi.ai and Kimi Work. The companion 3D guide says K3.1 Pro was specifically trained to drive 3D software through Python scripts, so specialized tools without MCP support can join the workflow, while meshes such as people and animals are handed to diffusion services like Tripo. Plugins that need locally installed software work only in Kimi Work.

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Researchers introduced BlenderWorld (arXiv:2610.23986), the first comprehensive benchmark evaluating visual agents creating and editing 3D models from real-world references in Blender. Spanning 223 tasks across procedural geometry, Python scripting, material shaders, spatial layouts, and lighting, GPT-6 Astra leads the benchmark with a composite Score of 79.9 (and a 42.2% Perfect completion rate), followed by Opus-5 at 73.0. Open-weight flagship DeepSeek-V4.1-Flash claims 65.7, matching proprietary models while relying on active execution-and-inspection tool loops.

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Nullframe (the Moda team, YC F26) shipped Voyager, a local desktop agent harness that drives creative apps through their own scripting APIs, ships free Design/Video/DAW engines, and works with your own Claude/Codex sign-in or API keys. The launch post passed 1.48M impressions.

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Conventional single-image 3D scene reconstruction typically produces static meshes or radiance fields (NeRF/3DGS), which lack modularity, CAD interpretability, and programmatic editability. Researchers introduce LEGO-Anything, an Image-to-Code framework where a coding agent autonomously writes and executes Blender Python scripts, renders multiview checks, and iteratively refines the 3D scene program. To systematically evaluate programmatic 3D recovery, the authors release LEGO-Bench across 208 images from 104 realistic indoor and outdoor environments. Diagnosing three recurrent failure modes in agentic generation—weak layout initialization, regressive edits, and uncalibrated self-evaluation—they propose LEGO-Plugin, a training-free harness delivering up to 62.7% relative improvements across evaluated foundation models while supporting zero-shot downstream 3D spatial queries.

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