CoreWeave combines training and inference for more powerful AI agents

The platform integrates training and inference for AI agents using a closed feedback loop that enables learning while running in production. Serverless RL lets enterprises post-train large language models for multi-turn agentic tasks without managing GPU infrastructure, aiming for faster training and lower cost while maintaining quality. Continuously running inference includes built-in monitoring for scaling behavior and system health. W&B Weave provides observability by detecting failure modes in multi-agent workflows and supplying an evaluation framework to prevent regressions as systems scale. W&B Skills and an MCP server allow coding agents to access experiment tracking, tracing, and monitoring tools, turning generic coding agents into autonomous AI researchers that improve other agents.

"“The pace of AI has outrun the way teams build for it. Today's tradeoff: dev cycles that can't keep up, or shipping agents and discovering failure modes in production,” says Chen Goldberg, Executive Vice President of Product and Engineering at CoreWeave."

"“CoreWeave's Serverless RL, previously launched as a standalone service, enables enterprises to post-train large language models for multi-turn agentic tasks without managing GPU infrastructure themselves. According to CoreWeave, this makes training approximately 1.4 times faster and up to 40 percent cheaper, without sacrificing quality.”"

"“In addition, there is CoreWeave Inference, designed as a continuously running workload with built-in monitoring for scaling behavior and system health. W&B Weave serves as an observability layer: it detects failure modes in multi-agent workflows and provides an evaluation framework that prevents regressions as systems scale.”"

"“The fourth component consists of W&B Skills and an MCP server. This combination transforms generic coding agents into autonomous AI researchers working to improve other agents. Skills gives coding agents direct access to W&B tools for experiment tracking, tracing, and monitoring. The MCP server provides the res”"

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