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Teams deploying AI agents in enterprise environments can now get per-session VM isolation, persistent filesystems, and governed identity out of the box — removing the need to build custom sandboxing infrastructure before going to production.
Teams building agentic systems can now iterate between SFT and RL on managed CoreWeave infrastructure without manually shuttling model artifacts, cutting the operational overhead that typically delays getting fine-tuned agents into production.
Teams building or deploying agentic AI systems should watch TPU 8i and TPU 8t as purpose-built hardware that could significantly affect inference latency and training scale for complex, multi-step agent workloads on Google Cloud.
Security and platform engineers evaluating AI coding tools for production use can reference this post as a structured breakdown of Replit's trust boundaries and layered controls.
Teams building agentic systems can use ToolSimulator to safely stress-test tool-dependent agents — including multi-turn workflows and edge cases — without risking PII exposure or unintended side effects from live API calls.
Teams iterating between SFT and RL can now run the full post-training loop — fine-tuning, evaluation, inference, and RL — inside a single W&B platform, cutting the infrastructure overhead that typically delays getting agents to production.