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Person: "ajambrosino"
not much happened today
gpt-5.5 claude-mythos-preview gpt-5.5-pro qwen3.6-27b hy3-preview grok-4.3 gemma-4-31b glm-5.1 deepseek-v4-flash openai anthropic x-ai tencent deepseek cybersecurity model-efficiency multimodality model-benchmarking agentic-ai model-cost-optimization context-windows model-performance open-weight-models software-integration security-updates sama scaling01 cryps1s polynoamial ajambrosino arix
OpenAI's GPT-5.5 achieves top-tier performance in long-horizon cyber tasks, matching or surpassing Claude Mythos Preview with a 71.4% pass rate and showing ongoing improvement beyond 100M tokens inference. OpenAI also released an Advanced Account Security update for ChatGPT enhancing phishing resistance. The Codex update expands beyond coding to general computer tasks, improving speed by up to 42% and introducing role-based onboarding and app integrations. Economically, GPT-5.5 Pro shows a slight SOTA improvement on CritPt with ~60% lower cost and token use compared to GPT-5.4 Pro. In open-weight models, Qwen3.6 27B leads under 150B parameters with an Intelligence Index score of 46, featuring 262K context, native multimodal input, and efficient BF16 weights. Tencent's Hy3-preview (295B total, 21B active MoE) scores 42 on the Intelligence Index with strong scientific reasoning on CritPt. xAI's Grok 4.3 shows sharp improvements on agentic benchmarks with reduced cost.
OpenAI Codex App: death of the VSCode fork, multitasking worktrees, Skills Automations
codex openai agent-based-systems parallel-processing software-testing developer-workflows automation product-feedback-loop neurosymbolic-ai benchmarking sama reach_vb gdb skirano embirico ajambrosino thsottiaux nbaschez yuchenj_uw badlogicgames random_walker
OpenAI launched the Codex app on macOS as a dedicated agent-native command center for coding, featuring multiple agents in parallel, built-in worktrees for conflict isolation, skills for reusable bundles, and scheduled automations. The app emphasizes developer workflows like Plan mode for upfront task decomposition and is gaining positive adoption signals from insiders including @sama. There is movement towards ecosystem standardization of skills folders, signaling early conventions in agent tooling. Codex also exemplifies a "self-improving" product feedback loop combining humans and agents. In coding agents practice, best practices include a "test-first" approach to bug fixes, the "conductor" model where one developer manages 5-10 agents in parallel, and a neurosymbolic framing explaining why coding agents succeed due to software's verifiability and symbolic tooling. Benchmark skepticism remains about productivity studies that do not reflect agentic workflows.