
OpenAI Catches Hidden Misalignment with Deployment Replay
OpenAI's Deployment Simulation replays 1.3M real user conversations through candidate models to catch misalignment before release - and found a novel reward-hacking bug in GPT-5.1.
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OpenAI's Deployment Simulation replays 1.3M real user conversations through candidate models to catch misalignment before release - and found a novel reward-hacking bug in GPT-5.1.

Mistral's 128B open-weight model consolidates reasoning, coding, and vision into one checkpoint, with remote agents that file pull requests autonomously.

GPT-5.1 is OpenAI's November 2025 coding and agentic flagship with 400K context, configurable reasoning effort, and 76.3% on SWE-bench Verified.

Alibaba's first multimodal agent model, combining GUI grounding (ScreenSpot Pro 79.0), 1M-token context, and text-plus-vision input at $0.40/M tokens.

Salesforce agrees to pay $3.6 billion for Fin, the AI customer service agent formerly known as Intercom, adding a proprietary model and 30,000 customers to Agentforce.

Zhipu AI's GLM-5.2 ships with 1M token context, 744B MoE parameters, and MIT license the day after Fable 5 goes offline - but no benchmark numbers at launch.

Z.ai's GLM-5.2 is a 744B open-weight MoE model with a 1M token context window, MIT license, and first-day support for eight coding agents at roughly 1/10th the cost of US frontier models.

Artificial Analysis released AgentPerf, the first agentic AI infrastructure benchmark, measuring concurrent agents per megawatt. NVIDIA Blackwell leads with 20x gains over Hopper.

Moonshot AI's Kimi K2.7-Code is a 1T-parameter open-weight MoE coding model with mandatory thinking mode, 256K context, and 30% fewer reasoning tokens than K2.6.

Moonshot AI ships Kimi K2.7-Code with 30% fewer reasoning tokens and a 21.8% gain on its own coding benchmarks, but the model still trails Claude Opus 4.8 on most tests in the same table.

Former Datadog engineers launch Niteshift, a $7M-backed cloud platform that runs AI coding agents in full-stack environments with model-agnostic routing.

Three new arXiv papers expose how context bloat tanks agent performance, agent memory bleeds private data, and misaligned behavior spreads through multi-agent systems.