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Person: "rhyssullivan"
not much happened today
glm-5 glm-5.2 kimi nemotron prime-intellect wandb vibrant-labs anthropic executor yc agentic-reinforcement-learning moe-models inference-optimization training-optimization rollout-orchestration persistent-agents asynchronous-agents organizational-agents agent-ux open-models coding-workflows security post-training benchmarking task-specific-rollouts samsja19 eliebakouch mervenoyann wandb claudeai claudedevs _catwu karpathy zhihu-frontier hwchase17 teknuim rhyssullivan joshua_saxe
Prime Intellect's
prime-rl v0.6.0 advances agentic reinforcement learning infrastructure supporting 1 trillion parameter MoE models with sub-5-minute step times and a 131k context GLM-5 agentic setup. The release includes optimizations in inference, training, and rollout orchestration, supporting models like GLM5, Kimi, Nemotron. Anthropic's Claude Tag exemplifies the shift to persistent, asynchronous agents embedded in organizations, already writing 65% of the product team's code and operating as background watchers and proactive task executors in workflows. The ecosystem features innovations like StarAgent, Self-Harness, Hermes Agent, and Executor's MCP gateway for operational agent fleets. GLM-5.2 gains momentum as a leading open model, especially for coding and agentic workflows, raising security concerns about enabling private offensive workflows without API logging. This highlights a broader trend of agent training becoming an infrastructure challenge, with emphasis on open post-training stacks, verifiable environments, and task-specific rollouts.