Research acceleration: The view inside OpenAI
Inside OpenAI, coding agents are reshaping AI research. Explore early data on agent usage, experiment velocity, task complexity, and research acceleration.
Inside OpenAI, coding agents are reshaping AI research. Explore early data on agent usage, experiment velocity, task complexity, and research acceleration.
In controlled offline evaluations, HydraFusion’s selective coding workflows matched or exceeded the evaluated Opus 5 baseline while reducing estimated workflow cost. Now available as a research preview in GitHub Copilot.
Learn how to run parallel agents in the GitHub Copilot app, and experience the moment it stops feeling scary and starts feeling powerful.
Google DeepMind released Gemini 3.8 Flash and Gemini 3.8 Flash Cyber. The former targets long-horizon coding and autonomous agents, priced like 3.7 Flash at $0.75 per million input tokens and $3.75 per million output tokens.
Multiverse Computing published a paper proposing Quantization-Aware Healing (QAH). After compressing GPT-OSS 120B to 60B parameters and quantising it to MXFP4, the method distils directly from the original uncompressed model rather than a reconstructed bfloat16 checkpoint.
Google DeepMind released Gemini 3.7 Flash, positioning it as its strongest workhorse model for coding and agents, just three weeks after Gemini 3.6 Flash.
The warning shots will continue until civilization wakes up
Hugging Face released ScarfBench (Self-Contained Application Refactoring Benchmark) to evaluate AI agents migrating enterprise Java applications between Spring, Jakarta EE and Quarkus.
The UK AISI alignment team and Timaeus co-founded nonprofit Sequent, arguing alignment research is unprepared for superintelligence. It plans 40–80 full-time staff within two to three years and initial fundraising of $100–150 million.
Innovations for global enterprises solving the world’s hardest problems.
The unified agent for long-horizon productivity and coding, launching with Work and Code modes. Plus, a new Vibe VS Code extension.
Introducing Mistral Medium 3.5, remote coding agents in Vibe, plus new Work mode in Le Chat for complex tasks.
Gemini 3.5 is built to help you execute complex, agentic workflows.
Explore how AlphaEvolve's Gemini-powered algorithms are driving impact across business, infrastructure, and science.
The first step towards recursive self improvement
Mistral AI released Leanstral, the first open-source coding agent for Lean 4, using a sparse architecture with 6B active parameters. Its weights are available under Apache 2.0, and it is integrated into Mistral vibe and the free labs-leanstral-2603 API endpoint.
Mistral built an autonomous agent on its open-source coding assistant Vibe to read Rails source files, generate or improve RSpec tests and run within CI/CD without human intervention.
Mistral released the terminal coding agent Mistral Vibe 2.0, powered by the Devstral 2 model family, adding custom subagents, multiple-choice clarifications, slash-command skills, unified agent modes and automatic updates.
Mistral AI released the next-generation Devstral 2 coding family, including 123B Devstral 2 under a modified MIT licence and 24B Devstral Small 2 under Apache 2.0, both open-source.
Mistral AI released Codestral 25.08 and a complete enterprise coding stack comprising Codestral, Codestral Embed, Devstral and the Mistral Code IDE plugin.
Mistral AI partnered with All Hands AI to release Devstral Medium and upgrade Devstral Small 1.1.
Mistral released Mistral Code, an AI coding assistant combining Codestral, Codestral Embed, Devstral and Mistral Medium. It supports cloud, dedicated-capacity and local air-gapped GPU deployment, keeping code within enterprise boundaries.
Mistral AI released its first code-focused embedding model, Codestral Embed, outperforming Voyage Code 3, Cohere Embed v4.0 and OpenAI's large embedding model on real-world code retrieval.
Mistral AI and All Hands AI jointly released Devstral, an agentic LLM for software engineering tasks, open-source under Apache 2.0.