
OpenAI has unveiled a new feature for its Codex AI called 'Record and Replay.' This tool allows users to record themselves performing a repetitive task once, enabling the AI to learn and replicate the task in the future. By observing user actions on the screen, Codex can save these tasks as 'skills' that can be reused by simply providing the necessary context in a chat box. This feature aims to enhance productivity by automating mundane tasks.
Read originalEarlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
The Rundown AI · April 17, 2026 · Related
The AI Daily Brief · April 22, 2026 · Related
The AI Advantage · May 1, 2026 · Related
Matt Wolfe · May 9, 2026 · Related
OpenAI · June 2, 2026 · Related
OpenAI · June 2, 2026 · Related
TechCrunch AI · June 2, 2026 · Related
The AI Daily Brief · June 12, 2026 · Same story
The Verge AI · June 29, 2026 · Related
The Verge AI · July 15, 2026 · Related
WIRED AI · August 27, 2026 · Related
TechCrunch AI · September 29, 2026 · Related
Matt Wolfe · October 9, 2026 · Related
This release quietly introduces Code Mode, an opt-in feature where Claude writes JavaScript to call its own tools, marking a shift toward more autonomous agent-like behavior within the CLI. The update also hardens the plugin ecosystem by enforcing version ranges and adding strict TypeScript type checking for hooks, which should significantly reduce instability from third-party extensions. Beyond these features, the changelog is dominated by critical fixes for authentication drift in background sessions and memory leaks when handling large files, stabilizing the tool for heavy enterprise use.
This release quietly patches a critical memory overflow in the mtmd module that caused crashes when loading HunyuanVL models. The issue stemmed from F64 position embeddings overflowing an F32 buffer, a subtle bug that broke multimodal inference for users relying on this specific architecture. By enforcing strict F32 requirements, llama.cpp stabilizes support for Tencent's vision-language model without adding new features or changing the core API. It’s a necessary maintenance update that keeps local multimodal workflows from breaking unexpectedly.
This release quietly extends llama.cpp’s hardware coverage with ROCm 10.0 binaries for both Linux and Windows, finally bringing AMD RDNA/CDNA users into the fold without manual compilation. The standout feature is native support for Qwen3.5 models via tensor merging during conversion, a necessary step as this new architecture gains traction in the open-source community. By shipping pre-built CUDA 13 binaries alongside the older 12.x versions, the project ensures forward compatibility with newer NVIDIA GPUs out of the box. There are no new quantization algorithms or performance breakthroughs here; it is purely an infrastructure update to keep pace with the rapidly shifting landscape of model architectures and GPU drivers.