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Stampli used Codex and ChatGPT Work to compress weeks of launch production into days while design resources were committed elsewhere. The company met a fixed deadline by leveraging these OpenAI tools, per OpenAI News.
Cloudflare announced Kitesurf, a cloud-hosted browser built to run AI agents rather than human users. The company says it uses less computing power than Chromium for common automation tasks, aiming to help developers build browser-based agents more efficiently.
Meta introduced Muse Code, an AI agent designed to work with large, complex software projects. The company says the agent can handle complex coding tasks across extensive code bases.
Google announced new capabilities for Managed Agents in the Gemini API, including a 3.6 Flash release and hooks to help developers build more reliable, production-ready agents. The blog frames these as developer-focused enhancements to agent functionality and reliability.
DoorDash has begun a limited beta of dd-cli, a command‑line tool that lets developers and AI agents search stores, assemble carts, and place orders from the terminal. The move signals more services being built with agent-friendly interfaces rather than only human GUI workflows.
OpenAI outlines how to begin using ChatGPT Codex, covering project setup, thread creation, and completing initial tasks. The guide provides step-by-step instructions to help users walk through their first coding workflows with the tool.
Ollama, an open-source toolkit that helps developers run AI models locally, has raised $65 million in new funding. The project has amassed significant GitHub traction with roughly 176,000 stars and nearly 17,000 forks, and reports close to 9 million users.
Google mengumumkan ciri baharu untuk Managed Agents dalam Gemini API termasuk sokongan tugas latar dan Remote MCP bagi membina ejen produksi yang lebih boleh dipercayai. Pembaharuan ini ditujukan kepada pemaju untuk memudahkan pengurusan kerja asinkron dan sambungan jauh dalam aplikasi mereka.
Hugging Face menyatakan bahawa pendekatan 'Machine Learning as Code' kini telah tiba. Ia menekankan integrasi pembangunan ML dengan kod dan alatan untuk mempercepatkan pembangunan dan pengeluaran model.
Menurut catatan blog Hugging Face, ia menerangkan langkah asas menggabungkan pengenalan ucapan AI ke dalam enjin Unity. Artikel itu memfokuskan aliran integrasi dan penggunaan model suara dalam projek Unity.
Menurut Hugging Face Blog, "Personal Copilot" membincangkan cara melatih pembantu kod peribadi menggunakan model dan data pengguna. Blog itu juga menekankan aliran kerja dan pertimbangan teknikal untuk membina pembantu kod yang disesuaikan.
Hugging Face memperkenalkan Optimum‑NVIDIA yang mendakwa membolehkan inference LLM sangat pantas dengan hanya satu baris kod. Alat ini direka untuk mempermudah penyebaran dan mempercepatkan inferens pada perkakasan NVIDIA, menurut catatan blog Hugging Face.
