Prentis, an AI research lab co-founded by Reid Hoffman and Mark Pincus, is raising $100 million at a $1 billion valuation to build computer-control models that automate office tasks. The startup has already signed $50 million in customer contracts and claims its Hive-32B model outperforms GPT-5.4 and Claude Opus on computer-use benchmarks while costing roughly 10 times less. The funding and early revenue reflect investor confidence that automating office workflows could become AI's most valuable use case, despite competition from OpenAI and Anthropic.
Prentis, an AI lab co-founded by Reid Hoffman and Marc Pincus focused on computer-use models, is raising $100 million at a $1 billion valuation. The startup has signed contracts worth up to $50 million with customers and claims its Hive-32B model outperforms GPT-5.4 and Claude Opus 4.6 on computer-use benchmarks while costing roughly 10 times less per task. The funding and early customer wins position Prentis to compete in the growing market for AI agents that automate office workflows.
Sakana AI released Fugu-Ultra v1.1, an orchestration engine that dynamically coordinates multiple frontier models to improve performance on coding and reasoning tasks. The update achieved benchmark improvements of up to 7.9 points over v1.0 while maintaining the same pricing, and now integrates with Claude Code to let developers access the multi-model system from their terminal. Developers using platforms like OpenRouter and Vercel can now access Fugu's coordinated model pool directly in their coding workflows without switching tools.
AWS, Google Cloud, Microsoft Azure, and Cloudflare have all launched isolated code execution sandboxes for AI agents within weeks of each other, but implemented them using different underlying technologies: AWS uses Firecracker VMs with up to eight hours of runtime, Google Cloud uses gVisor kernel interception or lightweight boundaries within Cloud Run, Azure uses Hyper-V with 400,000+ daily sessions for Copilot, and Cloudflare uses containerized VMs. Google charges no premium for Cloud Run sandboxes because they reuse allocated CPU and memory, demonstrated with 1,000 sandbox executions averaging 500 milliseconds each. The architectural differences mean vendor-specific limits persist—Lambda MicroVMs cap at eight hours and run only on Graviton in five regions, while Cloud Run sandboxes share the parent instance's resources—keeping governance and orchestration decisions separate from containment boundaries.
Security teams collecting excessive log data overwhelm analysts with alerts, and Sumo Logic proposes using AI agents to filter and correlate signals while maintaining human oversight. The company's Dojo.ai platform uses deterministic rules for real-time detection and AI reasoning on cleaned data, with every agent action traceable to prevent black-box decision-making. Organizations should tier storage by detection priority and consolidate tools rather than expand logging, as SOCs shift from human-reviewed every alert to AI-assisted triage with humans handling significant cases.
Domo released a customizable calendar agent that users can build and text to manage their schedules. The product allows direct text-based interaction with a calendar management system without specifying additional technical details. Users can now integrate calendar management into their messaging workflow rather than using traditional calendar interfaces.
OneCLI is an open-source gateway that stores API credentials centrally and injects them into requests from AI agents without exposing the actual secrets to the agents themselves. The system uses AES-256-GCM encryption, a Rust-based HTTP gateway, and a Next.js dashboard to manage credentials, access tokens, and permissions across multiple agents. This approach allows teams to manage API access in one place, rotate keys easily, and audit agent activity without giving each agent raw credentials.
Screenpipe is a local screen recording tool that captures what users see, say, and do to provide AI agents and language models with work context, processing all data on-device. The application features a custom-built AI model for removing sensitive information like credit card numbers and SSNs before any data is stored, reportedly outperforming OpenAI's, Google's, and Microsoft's filters. Users can exclude specific apps, windows, or URLs from capture, integrate with tools like Gmail and Slack, and deploy across enterprise fleets while keeping all processing local to each machine.
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